With training in both radiology and neurology, Dr. Jolesz had been envisioning ways that neurological conditions could benefit from the types of targeted, precise treatments that image-guidance provides.

The challenge was to develop the imaging systems that could support these types of techniques. Jolesz began collaborating with a team of engineers from GE Healthcare in to build the first MRI scanner for use during surgical procedures.

The system had two magnets on each side of a patient table, giving surgeons access to the patient who remained situated in the MRI scanner. In , the Food and Drug Administration approved the first image-guided procedure: MRI-guided focused ultrasound MRgFUS treatment of uterine fibroids.

Specialists have since used the technique to treat breast and brain tumors and relieve pain from bone metastasis. For over a century, a leader in patient care, medical education and research, with expertise in virtually every specialty of medicine and surgery. Stay Informed.

Connect with us. skip to Cookie Notice Skip to contents. Home Research AMIGO Suite What Is Image-Guided Therapy? Back to AMIGO Suite. Image-guided biopsy uses ultrasound, MRI, or mammography imaging guidance to take samples of an abnormality. In MRI-guided breast biopsy, magnetic resonance imaging is used to help guide the radiologist's instruments to the site of the abnormal growth.

Doctors use MRI guidance in biopsy procedures that use:. You will need to change into a hospital gown. This is to prevent artifacts appearing on the final images and to comply with safety regulations related to the strong magnetic field.

Guidelines about eating and drinking before an MRI vary between specific exams and facilities. Take food and medications as usual unless your doctor tells you otherwise.

Some MRI exams use an injection of contrast material. The doctor may ask if you have asthma or allergies to contrast material, drugs, food, or the environment. MRI exams commonly use a contrast material called gadolinium. Doctors can use gadolinium in patients who are allergic to iodine contrast.

A patient is much less likely to be allergic to gadolinium than to iodine contrast. However, even if the patient has a known allergy to gadolinium, it may be possible to use it after appropriate pre-medication. For more information on allergic reactions to gadolinium contrast, please consult the ACR Manual on Contrast Media.

Tell the technologist or radiologist if you have any serious health problems or recent surgeries. Some conditions, such as severe kidney disease, may mean that you cannot safely receive gadolinium.

You may need a blood test to confirm your kidneys are functioning normally. Women should always tell their doctor and technologist if they are pregnant. MRI has been used since the s with no reports of any ill effects on pregnant women or their unborn babies. However, the baby will be in a strong magnetic field.

Therefore, pregnant women should not have an MRI in the first trimester unless the benefit of the exam clearly outweighs any potential risks. Pregnant women should not receive gadolinium contrast unless absolutely necessary.

See the MRI Safety During Pregnancy page for more information about pregnancy and MRI. Prior to a needle biopsy, tell your doctor about all the medications you take, including herbal supplements. List any allergies, especially to anesthesia.

Your doctor may advise you to stop taking aspirin, blood thinners, or certain herbal supplements three to five days before your procedure.

This will help decrease your risk of bleeding. There are other important guidelines for patients to follow prior to undergoing MR imaging. For a list of these and a review of all preparations that should be made prior to MR imaging, please see MRI of the Breast.

The traditional MRI unit is a large cylinder-shaped tube surrounded by a circular magnet. You will lie on a table that slides into a tunnel towards the center of the magnet.

Some MRI units, called short-bore systems , are designed so that the magnet does not completely surround you. Some newer MRI machines have a larger diameter bore, which can be more comfortable for larger patients or those with claustrophobia.

They are especially helpful for examining larger patients or those with claustrophobia. Open MRI units can provide high quality images for many types of exams. Open MRI may not be used for certain exams. For more information, consult your radiologist.

Most MRI-guided breast biopsies are currently performed in closed MRI systems with a specially modified exam table. This moveable examination table allows your breasts to hang freely into cushioned openings, which contain wire coils that send and receive radio waves to help create the MR images.

This procedure may use other sterile equipment, including syringes, sponges, forceps, scalpels and a specimen cup or microscope slide. Unlike x-ray and computed tomography CT exams, MRI does not use radiation. Instead, radio waves re-align hydrogen atoms that naturally exist within the body. This does not cause any chemical changes in the tissues.

As the hydrogen atoms return to their usual alignment, they emit different amounts of energy depending on the type of tissue they are in. The scanner captures this energy and creates a picture using this information. In most MRI units, the magnetic field is produced by passing an electric current through wire coils.

Other coils are inside the machine and, in some cases, are placed around the part of the body being imaged. These coils send and receive radio waves, producing signals that are detected by the machine.

The electric current does not come into contact with the patient. A computer processes the signals and creates a series of images, each of which shows a thin slice of the body.

The radiologist can study these images from different angles. MRI is often able to tell the difference between diseased tissue and normal tissue better than x-ray, CT, and ultrasound.

Using MRI guidance to calculate the position of the abnormal tissue and to verify the placement of the needle, the radiologist inserts the biopsy needle through the skin, advances it into the lesion and removes tissue samples.

If a surgical biopsy is being performed, MRI may be used to guide a wire into the mass to help the surgeon locate the area for excision. Image-guided, minimally invasive procedures such as MR-guided breast biopsies are most often performed by a specially trained breast radiologist.

In most cases, you will lie face down on a moveable exam table. The doctor will position the affected breast into an opening in the table. A nurse or technologist will insert an intravenous IV line into a vein in your hand or arm and the contrast material gadolinium will be given intravenously.

Your breast will be gently compressed between two compression plates similar to those used in a diagnostic MRI exam , one of which is marked with a grid structure. Using computer software, the radiologist measures the position of the lesion with respect to the grid and calculates the position and depth of the needle placement.

The doctor will inject a local anesthetic into the skin and more deeply into the breast to numb it. The doctor will make a very small nick in the skin at the site where they will insert the biopsy needle.

The radiologist then inserts the needle, advances it to the location of the abnormality and MR imaging is performed to verify its position. Depending on the type of MRI unit being used, you may remain in place or be moved out of the center or bore of the MRI scanner.

The doctor removes tissue samples using a vacuum-assisted device VAD. Vacuum pressure pulls tissue from the breast through the needle into the sampling chamber.

Without withdrawing and reinserting the needle, it rotates positions and collects additional samples. Typically, the doctor will collect eight to 10 samples of tissue from around the lesion. If a surgical biopsy is to be performed, the doctor will insert a wire into the suspicious area as a guide for the surgeon.

The doctor may place a small marker at the biopsy site so they can locate it in the future if necessary. Once the biopsy is complete, the doctor or nurse will apply pressure to stop any bleeding.

They will cover the opening in the skin with a dressing. No sutures are needed. You will be awake during your biopsy and should have little discomfort. Many women report little pain and no scarring on the breast. However, certain patients, including those with dense breast tissue or abnormalities near the chest wall or behind the nipple, may be more sensitive during the procedure.

Some women find that the major discomfort of the procedure is from lying on their stomach for the length of the procedure. Strategically placed cushions can ease this discomfort.

When you receive the local anesthetic to numb the skin, you will feel a pin prick from the needle followed by a mild stinging sensation from the local anesthetic. You will likely feel some pressure when the doctor inserts the biopsy needle and during tissue sampling. This is normal. As tissue samples are taken, you may hear clicks or buzzing sounds from the sampling instrument.

These are normal. If you experience swelling and bruising following your biopsy, your doctor may tell you to take an over-the-counter pain reliever and to use a cold pack. Temporary bruising is normal. Call your doctor if you experience excessive swelling, bleeding, drainage, redness, or heat in the breast.

If a marker is left inside the breast to mark the location of the biopsied lesion, it will cause no pain, disfigurement, or harm. Biopsy markers are MRI compatible and will not cause metal detectors to alarm.

Avoid strenuous activity for at least 24 hours after the biopsy. Your doctor will outline more detailed post-procedure care instructions for you. A pathologist examines the removed specimen and makes a final diagnosis.

Depending on the facility, the radiologist or your referring physician will share the results with you. The radiologist will also evaluate the results of the biopsy to make sure that the pathology and image findings explain one another.

In some instances, even if cancer is not diagnosed, surgical removal of the entire biopsy site and imaging abnormality may be recommended if the pathology does not match the imaging findings. You may need a follow-up exam. If so, your doctor will explain why.

Sometimes a follow-up exam further evaluates a potential issue with more views or a special imaging technique.

To overcome this barrier, we developed a method to convert an FE mesh of the lung to a phantom CT image. Through the generation of the phantom image, we were able to isolate the geometry of the lung and large airways. A series of high-quality phantom images generated from the FE mesh deformed through in-silico experiments simulating the respiratory cycle will allow for the validation and evaluation of image-registration algorithms.

The method presented in this study will serve as an essential step towards the implementation of dynamic imaging and image registration in clinical settings to assess regional deformation in patients as a diagnostic and risk-stratification tool.

Comprehensive examination of personalized microwave ablation: exploring the effects of blood perfusion rate and metabolic heat on treatment responses.

Author s : Amirreza Heshmat, Caleb S. O'Connor, Jun Hong, Jessica Albuquerque Marques Silva, Iwan Paolucci, Aaron K. Jones, Bruno C. Odisio, Kristy K. Brock, The Univ. The Penne bioheat equation explains heat distribution in tissues, including factors like blood perfusion rate BPR and metabolic heat MH.

We employed 3D patient-specific models and sensitivity analysis to examine how BPR and MH affect MWA results. Numerical simulations using a triaxial antenna and 65 Watts power on tumors demonstrated that lower BPR led to less damage and complete tumor destruction.

Models without MH had less liver damage. The study highlights the importance of tailored ablation parameters for personalized treatments, revealing the impact of BPR and MH on MWA outcomes.

Comparative analysis of non-rigid registration techniques for liver surface registration. Author s : Bipasha Kundu, Zixin Yang, Richard Simon, Cristian A. Linte, Rochester Institute of Technology United States.

To address limited access to liver registration methods, we compare the robustness of three open-source optimization-based nonrigid registration methods and one data-driven method to a reduced visibility ratio reduced partial views of the surface and an increasing deformation level mean displacement , reported as the root mean square error RMSE between the pre- and intra-operative liver surface meshed following registration.

The Gaussian Mixture Model-Finite Element Model GMM-FEM method consistently yields a lower post-registration error than the other three tested methods in the presence of both reduced visibility ratio and increased intra-operative surface displacement, therefore offering a potentially promising solution for pre- to intra-operative nonrigid liver surface registration.

Auditory nerve fiber localization using a weakly supervised non-rigid registration U-Net. Author s : Hannah G.

Mason, Ziteng Liu, Jack H. CIs induce hearing sensation by stimulating auditory nerve fibers ANFs using an electrode array that is surgically implanted into the cochlea. After the device is implanted, an audiologist programs the CI processor to optimize hearing performance. Without knowing which ANFs are being stimulated by each electrode, audiologists must rely solely on patient performance to inform programming adjustments.

Patient-specific neural stimulation modeling has been proposed to assist audiologists, but requires accurate localization of ANFs. In this paper, we propose an automatic neural-network-based method for atlas-based localization of the ANFs. Our results show that our method is able to produce smooth ANF predictions that are more realistic than those produced by a previously proposed semi-manual localization method.

Accurate and realistic ANF localizations are critical for constructing patient-specific ANF stimulation models for model guided CI programming.

A comparison of onboard and offboard user interfaces for handheld robots. Author s : Ethan Wilke, Jesse F. d'Almeida, Jason Shrand, Tayfun Ertop, Nicholas L. Kavoussi, Amy Reed, Duke Herrell, Robert J. Webster, Vanderbilt Univ. Several research groups have shown that robots can be made so small and light that they can become hand-held tools.

This hand-held paradigm enables robots to fit much more seamlessly into existing clinical workflows. In this paper, we compare an onboard user interface approach against the traditional offboard approach. In the latter, the surgeon positions the robot, and a support arm holds it in place while the surgeon operates the manipulators using the offboard surgeon console.

The surgeon can move back and forth between the robot and the console as often as desired. Three experiments were conducted, and results show that the onboard interface enables statistically significantly faster performance in a point-touching task performed in a virtual reality environment.

Author s : Connor Mitchell, Robarts Research Institute Canada ; Shuwei Xing, Robarts Research Institute Canada , Western Univ. Canada ; Derek W. Cool, London Health Sciences Ctr.

Canada , Robarts Research Institute Canada ; David Tessier, Robarts Research Institute Canada ; Aaron Fenster, Robarts Research Institute Canada , Western Univ.

For this procedure, the radiologist must compare the pre-operative with the post-operative CT to determine the presence of residual tumors. Distinguishing between malignant and benign kidney tumors poses a significant challenge. To automate this tumor coverage evaluation step and assist the radiologist in identifying kidney tumors, we proposed a coarse-to-fine U-Net-based model to segment kidneys and masses.

We used the TotalSegmentator tool to obtain an approximate segmentation and region of interest of the kidneys, which was inputted into our 3D segmentation network trained using the nnUNet library to fully segment the kidneys and masses within them. Our model achieved an aggregated DICE score of 0.

Our results indicate the model will be useful for tumour identification and evaluation. Automating creation of high-fidelity holographic hand animations for surgical skills training using mixed reality headsets. Author s : Regina W. Leung, Ge Shi, Western Univ.

Canada ; Christina A. Using this methodology, we successfully developed a 3D holographic animation of one-handed knot ties used in surgery. With regards to the quality of the produced animation, our qualitative pilot study demonstrated comparable successful learning of knot-ties from the holographic animation to in-person demonstration.

Furthermore, participants found learning knot-ties from the holographic animation to be easier, more effective, were more confident in mastery of the skill in comparison to in-person demonstration, and also found the animation comparable to real hands showing promise for application in surgical skills training applications.

A robust system for capture and archival of high-definition stereoendoscopic video. Author s : Michael A. Kokko, Ryan J.

Capturing stereo video for the purpose of offline reconstruction requires dedicated hardware, a mechanism for temporal synchronization, and video processing tools that perform accurate clip extraction, frame extraction, and lossless compression for archival.

This work describes a minimal hardware setup comprising entirely off-the-shelf components for capturing video from the da Vinci and similar 3D-enabled surgical systems. Software utilities are also provided for synchronizing data collection and accurately handling captured video files.

End-to-end testing demonstrates that all processing functions clipping, frame cropping, compression, un-compression, and frame extraction operate losslessly, and can be combined to generate reconstruction-ready stereo pairs from raw surgical video. Author s : Soyoung Park, Sahaja Acharya, Matthew Ladra, The Johns Hopkins Univ.

School of Medicine United States ; Junghoon Lee, Johns Hopkins Univ. For pediatric cancer patients, reducing ionizing radiation from CT scans is preferred for which MRI-based RT planning and assessment is truly beneficial.

For accurate pediatric CT image synthesis, we investigated a 3D conditional generative adversarial network cGAN -based transfer learning approach due to the lack of sufficient pediatric data compared to adult data.

Our model was first trained using adult data with downscaling to simulate pediatric data, followed by fine-tuning on a smaller number of pediatric data. The proposed 3D cGAN-based transfer learning was able to accurately synthesize pediatric CT images from MRI, allowing us to realize pediatric MR-only RT planning, QA, and treatment assessment.

Monocular microscope to CT registration using pose estimation of the incus for augmented reality cochlear implant surgery.

Author s : Yike Zhang, Eduardo Davalos Anaya, Ange Lou, Dingjie Su, Jack H. Augmented reality AR surgery may improve CI procedures and hearing outcomes.

Typically, AR solutions for image-guided surgery rely on optical tracking systems to register pre-op planning information to the display so that hidden anatomy or other information can be overlayed co-registered with the view of the surgical scene.

In this work, our goal is to develop a method that permits direct 2D-to-3D registration of the microscope video to the pre-operative CT scan without the need for external tracking equipment.

Our proposed solution involves surface-mapping a portion of the incus in the video and determining the pose of this structure relative to the surgical microscope by solving the perspective-n-point pose computation to achieve 2D-to-3D registration.

This registration can then be applied to pre-operative segmentation of other hidden anatomy as well as the planned electrode insertion trajectory to co-register this information for AR display. Initial implementation of robot-integrated specimen imaging in transoral robotic surgery.

Kokko, Thayer School of Engineering at Dartmouth United States ; Andrew Y. Lee, Geisel School of Medicine, Dartmouth College United States ; Joseph A. When margins are positive, it is critical that resection specimens be accurately oriented in anatomical context for gross and microscopic evaluation, and also that surgeons, pathologists, and other care team members share an accurate spatial awareness of margin locations.

With clinical interest in digital pathology on the rise, this work outlines a proposed framework for generating 3D specimen models intraoperatively via robot-integrated stereovision, and using these models to visualize involved margins in both ex vivo flattened and in situ conformed configurations.

Preliminary pilot study results suggest that stereo specimen imaging can be easily integrated into the transoral robotic surgery workflow, and that the expected accuracy of raw reconstructions is around 1. Ongoing data collection and technical development will support a full system evaluation.

Using artificial intelligence to classify point-of-care ultrasound images. Author s : Owen Anderson, Biomedical Imaging Resource Core, Mayo Clinic United States ; Garrett Regan, Songnan Wen, Deepa Mandale, Tasneem Naqvi, David R.

Holmes, Mayo Clinic United States. Such a device can now perform an echocardiogram while connected to a smartphone. While the accessibility of performing a test has been greatly improved, expertise is still required to provide usable results and diagnoses. The goal of this study is to improve the clinical utility of mobile ultrasound echocardiograms with AI machine learning.

By integrating artificial intelligence into this workflow, feedback can be given to the provider during its operation to maximize the usability of the ultrasound data and allow more tests to be performed properly.

The Intel GETi framework was used to create computer vision models that could quantify the readability of frames taken from an echocardiogram. These models determine the quality and the orientation of each frame.

Feedback from these models can alert the user to proper positioning and technique to gather good ultrasound data. Testing accuracy can also be improved with.

Tuesday Morning Keynotes. Unlocking the value of 3D printing medical devices in hospitals and universities Keynote Presentation. Author s : Frank J. Rybicki, The Univ. of Arizona College of Medicine United States. This talk describes those patients, how their medical images undergo Computer Aided Design CAD , and how that data reaches a Final Anatomic Realization, one of which is 3D printing.

The talk includes medical oversight, data generation, and a specific, durable definition of value for medical devices that are 3D printed in hospitals.

The talk also includes clinical appropriateness, and how it folds into accreditation for 3D printing in hospitals and universities. Up to the minute information on reimbursement for medical devices that are 3D printed in hospitals and universities will be presented.

Clinical AI model translation and deployment: creating a scalable, standardized, and responsible AI lifecycle framework in healthcare Keynote Presentation. Author s : David S. McClintock, Mayo Clinic United States.

However, amongst that excitement, one topic that has lacked direction is how healthcare institutions, from small clinical practices to large health systems, should approach AI model deployment.

Unlike typical healthcare IT implementations, AI models have special considerations that must be addressed prior to moving them into clinical practice. This talk will review the major issues surrounding clinical AI implementations and present a scalable, standardized, and responsible framework for AI deployment that can be adopted by many different healthcare organizations, departments, and functional areas.

Session Chairs: Cristian A. Linte , Rochester Institute of Technology United States , William E. Higgins , The Pennsylvania State Univ.

Democratizing surgical skills via surgical data science Invited Paper. Author s : Stefanie Speidel, Nationales Centrum für Tumorerkrankungen Dresden Germany. Although a lot of data is available, the human ability to use these possibilities especially in a complex and time-critical situation such as surgery is limited and is extremely dependent on the experience of the surgical staff.

This talks focuses on AI-assisted surgery with a specific focus on analysis of intraoperative video data. The goal is to democratize surgical skills and enhance the collaboration between surgeons and cyber-physical systems by quantifying surgical experience and make it accessible to machines.

Several examples to optimize the therapy of the individual patient along the surgical treatment path are given. Finally, remaining challenges and strategies to overcome them are discussed. Dual-camera laparoscopic imaging with super-resolution reconstruction for intraoperative hyperspectral image guidance.

Author s : Ling Ma, Kelden T. Pruitt, Baowei Fei, The Univ. of Texas at Dallas United States. Hyperspectral imaging HSI is an emerging medical imaging modality, which has proved useful for intraoperative image guidance. Snapshot hyperspectral cameras are ideal for intraoperative laparoscopic imaging because of their compact size and light weight, but low spatial resolution can be a limitation.

In this work, we developed a dual-camera laparoscopic imaging system that comprises of a high-resolution color camera and a snapshot hyperspectral camera, and we employ super-resolution reconstruction to fuse the images from both cameras to generate high-resolution hyperspectral images.

The experiment results show that our method can significantly improve the resolution of hyperspectral images without compromising the image quality or spectral signatures.

The proposed super-resolution reconstruction method is promising to promote the employment of high-speed hyperspectral imaging in laparoscopic surgery. Dense surface reconstruction using a learning-based vSLAM model for laparoscopic surgery. Author s : James Yu, The Univ. of Texas at Dallas United States ; Kelden T.

Pruitt, Nati Nawawithan, The Univ. at Dallas United States ; Baowei Fei, The Univ. While previous works have utilized pre-operative imaging such as computed tomography or magnetic resonance images, registration methods still lack the ability to accurately register deformable anatomical structures across modalities and dimensionalities.

This is especially true of minimally invasive abdominal surgeries due to limitations of the monocular laparoscope. Surgical scene reconstruction is a critical component towards AR-guided surgical interventions and other AR applications such as remote assistance or surgical simulation.

In this work, we show how to generate a dense 3D reconstruction with camera pose estimations and depth maps from video obtained with a monocular laparoscope utilizing a state-of-the-art deep-learning-based visual simultaneous localization and mapping vSLAM model.

The proposed method can robustly reconstruct surgical scenes using real-time data and provide camera pose estimations without stereo or other sensors, which increases its usability and is less intrusive.

AVA: automated viewability analysis for ureteroscopic intrarenal surgery. Author s : Daiwei Lu, Yifan Wu, Xing Yao, Vanderbilt Univ. United States ; Nicholas L. Kavoussi, Vanderbilt Univ.

United States ; Ipek Oguz, Vanderbilt Univ. This contributes to a high recurrence rate for both kidney stone and UTUC patients.

We introduce an automated patient-specific analysis for determining viewability in the renal collecting system using pre-operative CT scans. WS-SfMLearner: self-supervised monocular depth and ego-motion estimation on surgical videos with unknown camera parameters. Author s : Ange Lou, Jack H.

However, it is difficult and time consuming to create depth map ground truth datasets in surgical videos due in part to inconsistent brightness and noise in the surgical scene. Therefore, building an accurate and robust self-supervised depth and camera ego-motion estimation system is gaining more attention from the computer vision community.

Although several self-supervision methods alleviate the need for ground truth depth maps and poses, they still need known camera intrinsic parameters, which are often missing or not recorded. Moreover, the camera intrinsic prediction methods in existing works depend heavily on the quality of datasets.

In this work, we aim to build a self-supervised depth and ego-motion estimation system which can predict not only accurate depth maps and camera pose, but also camera intrinsic parameters. We propose a cost-volume-based supervision approach to give the system auxiliary supervision for camera parameters prediction.

Session Chairs: Pierre Jannin , Lab. Traitement du Signal et de l'Image France , Junghoon Lee , Johns Hopkins Univ. End-to-End 3D neuroendoscopic video reconstruction for robot-assisted ventriculostomy.

Author s : Prasad Vagdargi, Ali Uneri, Stephen Z. Liu, Craig K. Jones, Alejandro Sisniega, Johns Hopkins Univ. United States ; Junghoon Lee, The Johns Hopkins Univ.

School of Medicine United States ; Patrick A. United States ; William S. Anderson, Mark Luciano, The Johns Hopkins Univ. School of Medicine United States ; Gregory D. Hager, Johns Hopkins Univ. We introduce a vision-based navigation solution using NeRFs for 3D neuroendoscopic reconstruction on the Robot-Assisted Ventriculoscopy RAV platform.

An end-to-end 3D reconstruction method using posed images was developed and integrated with RAV. System performance was evaluated in terms of geometric accuracy, precision and runtime across multiple clinically feasible trajectories, achieving accurate sub-mm projected error.

Clinical neuroendoscopic video reconstruction and registration was successfully achieved with sub-mm geometric accuracy and high precision. Intraoperative stereovision cortical surface segmentation using fast segment anything model.

Author s : Chengpei Li, Dartmouth College United States ; Xiaoyao Fan, Kristen L. Chen, Ryan B. Duke, Thayer School of Engineering at Dartmouth United States ; Linton T. A biomechanical model updates pre-op MR images using intraoperative stereovision iSV for accuracy.

Traditional methods require manual cortical surface segmentation from iSV, demanding expertise and time. This study introduces the Fast Segment Anything Model FastSAM , a deep learning approach, for automatic segmentation from iSV. FastSAM's performance was compared with manual segmentation and a U-Net model in a patient case, focusing on segmentation accuracy Dice coefficient and image updating accuracy target registration errors; TRE.

FastSAM and manual segmentation had similar TREs 2. FastSAM's performance aligns with manual segmentation in accuracy, suggesting its potential to replace manual methods for efficiency and reduced user dependency.

Joint MR to CT synthesis and segmentation for MR-only pediatric brain radiation therapy planning. Author s : Lina Mekki, Sahaja Acharya, Matthew Ladra, Junghoon Lee, Johns Hopkins Univ.

RT plans are typically optimized using CT, thus exposing patients to ionizing radiation. Manual contouring of organs-at-risk OARs is time-consuming, particularly difficult due to the small size of brain structures, and suffers from inter-observer variability. While numerous methods have been proposed to solve MR to CT image synthesis or OAR segmentation separately, there exist only a handful of methods tackling both problems jointly, even less specifically developed for pediatric brain cancer RT.

We propose a multi-task convolutional neural network to jointly synthesize CT from MRI and segment OARs eyes, optic nerves, optic chiasm, brainstem, temporal lobes, and hippocampi for pediatric brain RT planning.

Effect of the prior distribution on a Bayesian model or errors of type for transcranial magnetic stimulation. Author s : John S. Baxter, Pierre Jannin, Univ. de Rennes 1 France.

If the target may be highly ambiguous, different experts may fundamentally select different targets, believing them to refer to the same region, a phenomenon called an error of type. This paper investigates the effects of changing the prior distribution on a Bayesian model for errors of type specific to transcranial magnetic stimulation TMS planning.

Our results show that a particular prior can be chosen which is analytically solvable, removes spurious modes, and returns estimates that are coherent with the TMS literature.

This is a step towards a fully rigorous model that can be used in system evaluation and machine learning. An adaptable model for estimating patient-specific electrical properties of the implanted cochlea.

Author s : Erin L. Bratu, Vanderbilt Univ. United States ; Katelyn A. Berg, Andrea J. DeFreese, Rene H. Gifford, Vanderbilt Univ. United States ; Jack H. One limitation of these models is the large amount of data required to create them, with the resulting model being highly optimized to these single sets of measurements.

Thus, it is desirable to create a new model of equal or better quality that does not require this data to create the model and that is adaptable to new sets of clinical data. In this work, we present a methodology for one component of such a model, which uses simulations of voltage spread in the cochlea to estimate patient-specific electric potentials.

Session 6: Joint Session with Conferences and Session Chairs: Purang Abolmaesumi , The Univ. of British Columbia Canada , Josquin Foiret , Stanford Univ. Real-time vasculature segmentation during laparoscopic liver resection using attention-enriched U-Net model in intraoperative ultrasound videos.

Author s : Muhammad Awais, Mais Altaie, Caleb S. O'Connor, Austin H. Castelo, Hop S. Tran Cao, Kristy K. We propose an AI-driven solution to enhance real-time vessel identification inferior vena cava IVC , right hepatic vein RHV , left hepatic vein LHV , and middle hepatic vein MHV using a visual saliency approach that integrates attention blocks into a novel U-Net model with integrated attention blocks.

The study encompasses a dataset of IOUS video recordings from 12 patients, acquired during liver surgeries. Employing leave-one-out cross-validation, the model achieves mean dice scores of 0.

This innovative approach holds the potential to revolutionize liver surgery by enabling precise vessel segmentation, with future prospects including broader vasculature segmentation and real-time application in the operating room.

An automated system for registration and fusion of 3D ultrasound images during cervical brachytherapy procedures. Author s : Tiana Trumpour, Robarts Research Institute Canada ; Jamiel Nasser, Univ.

of Waterloo Canada ; Jessica R. Rodgers, Univ. of Manitoba Canada ; Jeffrey Bax, Lori Gardi, Robarts Research Institute Canada ; Lucas C. Mendez, Kathleen Surry, London Regional Cancer Program Canada ; Aaron Fenster, Robarts Research Institute Canada.

Radiation is delivered using specialized applicators or needles that are inserted within the patient using medical imaging guidance. However, advanced imaging modalities may be unavailable in underfunded healthcare centers, suggesting a need for accessible imaging techniques during brachytherapy procedures.

This work focuses on the development and validation of a spatially tracked mechatronic arm for 3D trans-abdominal and trans-rectal ultrasound imaging. The arm will allow automated acquisition and inherent registration of two 3D ultrasound images, resulting in a fused image volume of the whole female pelvic region.

The results of our preliminary testing demonstrate this technique as a suitable alternative to advanced imaging for providing visual information to clinicians during brachytherapy applicator insertions, potentially aiding in improved patient outcomes.

Percutaneous nephrostomy needle guidance using real-time 3D anatomical visualization with live ultrasound segmentation. Author s : Andrew S. Kim, Chris Yeung, Queen's Univ. Canada ; Robert Szabo, Óbuda Univ. Hungary ; Kyle Sunderland, Rebecca Hisey, David Morton, Queen's Univ.

Canada ; Ron Kikinis, Brigham and Women's Hospital United States ; Babacar Diao, Univ. Cheikh Anta Diop Senegal ; Parvin Mousavi, Tamas Ungi, Gabor Fichtinger, Queen's Univ. Current percutaneous nephrostomy needle guidance methods can be difficult, expensive, or not portable.

We propose an open-source based real-time 3D anatomical visualization aid for needle guidance with live ultrasound segmentation and 3D volume reconstruction using deep learning and free, open-source software.

Participants performed needle insertions with visualization aid and conventional ultrasound needle guidance. Visualization aid guidance showed a significantly higher accuracy, while needle insertion time and success rate were not statistically significant at our sample size.

We found that real-time 3D anatomical visualization aid for needle guidance produced increased accuracy and an overall mostly positive experience. Mirror-based ultrasound system for exploring hand gesture classification through convolutional neural network and vision transformer.

Author s : Keshav Bimbraw, Haichong K. Zhang, Worcester Polytechnic Institute United States. Hand gesture recognition with ultrasound has gained interest in prosthetic control and human-computer interaction. Traditional methods used for hand gesture estimation involve placing an ultrasound probe perpendicular to the forearm causing discomfort and interference with arm movement.

To address this, a novel approach utilizing acoustic reflection is proposed wherein a convex ultrasound probe is strategically positioned in parallel alignment with the forearm, and a mirror is placed at a degree angle for transmission and reception of ultrasound waves.

This positioning enhances stability and reduces arm strain. CNNs and ViT are employed for feature extraction and classification. The system's performance is compared to the traditional perpendicular method, demonstrating comparable results. The experimental outcomes showcase the potential of the system for efficient hand gesture recognition.

Design and evaluation of an educational system for ultrasound-guided interventional procedures. Author s : Purnima Rajan, Martin Hossbach, Pezhman Foroughi, Alican Demir, Christopher Schlichter, Clear Guide Medical United States ; Karina Gattamorta, Shayne Hauglum, School of Nursing and Health Studies, Univ.

of Miami United States. The system consists of an ultrasound needle guidance system which overlays virtual needle trajectories on the ultrasound screen, and custom anatomical phantoms tailored to specific anesthesiology procedures.

The system utilizes artificial intelligence-based optical needle tracking. It serves two main functions: skill evaluation, providing feedback to students and instructors, and as a learning tool, guiding students in achieving correct needle trajectories.

The system was evaluated in a study with nursing students, showing significant improvements in guided procedures compared to non-guided ones. Live Demonstrations Workshop.

Session Chairs: Karen Drukker , The Univ. of Chicago United States , Lubomir M. Hadjiiski , Michigan Medicine United States , Horst Karl Hahn , Fraunhofer-Institut für Digitale Medizin MEVIS Germany. Publicly Available Data and Tools to Promote Machine Learning: an interactive workshop exploring MIDRC.

Session Chairs: Weijie Chen , U. Food and Drug Administration United States , Heather M. Whitney , The Univ. of Chicago United States. Chair welcome and introduction. Additive manufacturing: the promise and the challenge. Author s : David W. Holdsworth, Western Univ.

The regulatory environment for medical devices is geared towards conventional manufacturing techniques, making it challenging to certify 3D-printed devices.

Additive manufacturing may still not be competitive when scaled up for industrial production, and the need for post-processing may negate some of the benefits. The promises and the challenges of additive manufacturing will be explored in the context of medical imaging device design.

Point-of-care manufacturing at Mayo Clinic. Author s : Jonathan M. Morris, Mayo Clinic United States. Using additive manufacturing we focus on five distinct areas. First to create diagnostic anatomic models for each surgical subspecialty from diagnostic imaging.

Second to manufacture custom patient-specific sterilizable osteotomy cutting guides for ENT, OMFS, Orthopedics, and Orthopedic Oncology. Third to build simulators and phantoms using a combination of special effects and 3Dprinting.

Fourth using 3D printers to create custom phantoms, phantom holders, and other custom medical devices such as pediatric airway devices, proton beam appliances, and custom jigs and fixtures for the department and hospital. Finally to transfer the digital twins into virtual and augmented reality environments for preoperative surgical planning and immersive educational tools.

Mayo Clinic has scaled this endeavor to all three of its main campuses including Jacksonville Fl and Scottsdale AZ to complete the enterprise approach. In doing so we have been able to advance patient care locally as well as assist in building the national IT, regulatory, billing, RSAN 3D SIG, and quality control infrastructure needed to assure scaling across this and other countries.

Author s : Alex Grenning, The Jacobs Institute, Inc. Test fixtures define the goal posts for device evaluation. It is important for test fixtures to accurately represent the critical conditions of operation and be supported with justification for regulatory review.

This presentation explores the role of 3D printing and model design workflows in producing anatomically relevant text fixtures which can be used to guide, and more importantly accelerate the device development process.

The Jacobs Institute is a one-of-a-kind, not-for-profit vascular medical technology innovation center. Author s : Devarsh Vyas, Benjamin Johnson, 3D Systems Corp. Common uses for AM include the printing of patient-specific surgical implants and instruments derived from imaging data and the manufacturing of metal implants and instruments with features that are impossible to fabricate using traditional subtractive manufacturing.

In addition to reducing costs, patient-specific solutions—such as customized surgical plans and personalized implants—aim to improve surgical outcomes for patients and give surgeons more options and more flexibility in the OR.

With advancement in technology, implants are 3D printed in various materials and at various manufacturing sites including at the point-of-care. Panel Discussion.

Establishing Ground Truth in Radiology and Pathology. Wednesday Morning Keynotes. The journey to better breast cancer detection: a trilogy Keynote Presentation.

Author s : Robert M. Nishikawa, Univ. of Pittsburgh United States. Technology assessment metrics were used to develop mammography systems, first with screen-film mammography and then to digital mammography and digital breast tomosynthesis.

To optimize these systems clinically, it became necessary to determine what type of information a radiologist needed to make a correct diagnosis. Image perception studies helped define what spatial frequencies were necessary to detect breast cancers and how different sources of noise affected detectability.

Finally, observer performance studies were used to show that advances in the imaging system led to better detection and diagnoses by radiologists. In parallel to these developments, these three concepts were used to develop computer-aided diagnosis systems.

In this talk, I will highlight how image perception, observer performance, and technology assessment were leveraged to produce technologies that allow radiologists to be highly effective in detecting breast cancer. A tale of two imaging informatics translational licensing models: commercial and open source Keynote Presentation.

Author s : Gordon J. Harris, Massachusetts General Hospital United States. Session Chairs: John S. Baxter , Univ. de Rennes 1 France , Satish E. Viswanath , Case Western Reserve Univ. Advances in model-guided interventions Invited Paper.

Author s : Michael I. This reality motivates many questions, both exhilarating and provocative. The assertion in this talk is that treatment platform technologies of the future will need to be intentionally designed for the dual purpose of treatment and discovery.

Exemplar surgical and interventional technologies will be discussed that involve complex biophysical models, methods of automation and procedural field surveillance, efforts toward data-driven procedures and therapy forecasting, and approaches integrating disease phenotypic biomarkers.

The common thread to the work is the use of computational models driven by sparse procedural data as a constraining environment to enable guidance and therapy delivery.

Optimal hyperparameter selection in deformable image registration using information criterion and band-limited modal reconstruction.

Author s : Jon S. United States ; Morgan J. Ringel, Vanderbilt Univ. United States ; Jayasree Chakraborty, William R. Jarnagin, Memorial Sloan-Kettering Cancer Ctr. However, these procedures may not produce results that optimally generalize to inter- and intra-dataset variabilities. We present a parameter estimation framework based on the Akaike Information Criterion AIC that permits dynamic runtime adaptation of model parameters by maximizing the informativeness of the registration model against the specific data constraints available to the registration.

This parameter adaptation framework is implemented in a frequency band-limited reconstruction approach to efficiently resolve modal harmonics of soft tissue deformation in image registration.

Our approach automatically selects optimal model complexity via AIC to match informational constraints via a parallel-computed ensemble model that achieves excellent TRE without the need for any hyperparameter tuning.

GhostMorph: a computationally efficient model for deformable inter-subject registration. Author s : Mingzhe Hu, Xiaofeng Yang, Shaoyan Pan, Emory Univ. GhostMorph addresses the computational challenges inherent in medical image registration, particularly in deformable registration where complex local and global deformations are prevalent.

During image-guided surgery, the procedure is guided by preoperative or intraoperative imaging. Part of the wider field of computer-assisted surgery , image-guided surgery can take place in hybrid operating rooms using intraoperative imaging.

A hybrid operating room is a surgical theatre that is equipped with advanced medical imaging devices such as fixed C-Arms, CT scanners or MRI scanners. Most image-guided surgical procedures are minimally invasive. A field of medicine that pioneered and specializes in minimally invasive image-guided surgery is interventional radiology.

A hand-held surgical probe is an essential component of any image-guided surgery system as it provides the surgeon with a map of the designated area. Existing IGS systems use different tracking techniques including mechanical, optical, ultrasonic, and electromagnetic. When fluorescence modality is adopted to such devices, the technique is also called fluorescence image-guided surgery.

Image-guided surgery using medical ultrasound utilises sounds waves and as such does not require the protection and safety precautions necessary with ionising radiation modalities such as fluoroscopy , CT, X-Ray and tomography.

Optical topographic imaging using structured light and machine vision stereoscopic cameras has been applied in neurosurgical navigation systems to reduce the use of intraoperative ionising radiation as well.

Modern image-guided surgery systems are often combined with robotics. The various applications of navigation for neurosurgery have been widely used and reported for almost two decades.

Image-guided surgery was originally developed for treatment of brain tumors using stereotactic surgery and radiosurgery that are guided by computed tomography CT , magnetic resonance imaging MRI and positron emission tomography PET via technologies such as the N-localizer [11] and Sturm-Pastyr localizer.

Image-guided surgery systems are also used in spine surgery to guide the placement of implants and avoid damaging the nearby neurovascular structures. A mini-optical navigation system has been developed that makes real-time measurements to guide surgeons during total hip arthroplasty procedures.

Image-guided surgery based on MRI is used to guide prostatic biopsy. Contents move to sidebar hide. Article Talk. Common early side effects include fatigue and skin problems. Skin in the treatment area may become sensitive, red, irritated, or swollen. Other changes include dryness, itching, peeling, and blistering.

Late side effects may occur months or years following treatment. While they are often permanent, they are rare. They include:. There is a slight risk of developing cancer from radiation therapy.

After treatment, your radiation oncologist will regularly check for complications and recurrent or new cancers. IGRT allows doctors to maximize the cancer-destroying capabilities of radiation treatment. At the same time, it allows them to minimize its effect on healthy tissues and any treatment side effects.

Please type your comment or suggestion into the text box below. Note: we are unable to answer specific questions or offer individual medical advice or opinions. org is not a medical facility. Please contact your physician with specific medical questions or for a referral to a radiologist or other physician.

To locate a medical imaging or radiation oncology provider in your community, you can search the ACR-accredited facilities database.

This website does not provide cost information. The costs for specific medical imaging tests, treatments and procedures may vary by geographic region. Web page review process: This Web page is reviewed regularly by a physician with expertise in the medical area presented and is further reviewed by committees from the Radiological Society of North America RSNA and the American College of Radiology ACR , comprising physicians with expertise in several radiologic areas.

Outside links: For the convenience of our users, RadiologyInfo. org provides links to relevant websites. org , RSNA and ACR are not responsible for the content contained on the web pages found at these links.

Toggle navigation. What is Image-Guided Radiation Therapy and how is it used? Who will be involved in this procedure? What equipment is used? Who operates the equipment? Is there any special preparation needed for an IGRT?

How is the procedure performed? What will I feel during and after an IGRT procedure? The image-guidance process will add additional time to each treatment session. Medical imaging prior to or during treatment is painless.

Depending on the area under treatment, other early side effects may include: hair loss in the treatment area mouth problems and difficulty swallowing eating and digestion problems diarrhea nausea and vomiting headaches soreness and swelling in the treatment area urinary and bladder changes Late side effects may occur months or years following treatment.

They include: brain changes spinal cord changes lung changes kidney changes colon and rectal changes infertility joint changes lymphedema mouth changes secondary cancer There is a slight risk of developing cancer from radiation therapy.

Chemoembolization - Liver. Dialysis Fistulagram. Embolization - Kidney. Nonsurgical Tumor Treatment. Are You a Candidate? Tumor Ablation Procedure Information. Selective Internal Radiation Therapy for Liver. Prostate Artery Embolization. Aneurysm - What is It. Case Study: Aneurysm Coiling. AVM Embolization.

Balloon Occlusion Test. Balloon Occlusion Test Procedure Information. Cerebral Embolization Patient Information.

Cerebral Tumor Embolization. Cerebral Tumor Emboilization Patient Information. Discogram Procedure Information. Epidural Steroid Injection. Epidural Steroid Injection Procedure Information. Ethanol Ablation. Facet Block or Selective Nerve Root Block. Interventional Stroke Treatments.

Lumbar Puncture. Myelogram - What is it? Myelogram Procedure Information. Nerve Root Block. Nerve Root Block Patient Information.

Neurointervention Endovascular Radiology. Spinal Compression Fractures. Types of Spinal Fractures. Kyphoplasty Procedure Information. Case Studies. Spinal Taps. Interventional Cancer Treatments. Magnetic Resonance Imaging MRI. MRI With Anesthesia.

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MR Guided Breast Needle-Core Biopsy Procedure Information. MRI Guided Breast Needle Localization. MRI Cardiac. MRI Chest. MR Cholangiogram. MR Enterography. MRI MRA MRV Head.

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MRI Spine - Lumbar or Thoracic. MRI Thyroid or Parathyroid. Musculoskeletal Radiology. Botox Injection for Peripheral Nerve Entrapment: Post-Op Care. CT-Guided Bone Biopsy. CT-Guided Soft-Tissue Biopsy. Calcific Tendonitis Aspiration: Post-Op Care. Joint Injections and Aspirations.

Pain Treatment and Therapy Program. Perineural Injection for Pain Relief: Post-Op Care. Platelet Rich Plasma - PRP - Therapy. Platelet Rich Plasma Therapy. PRP Plantar Fasciitis. PRP for Small Rotator Cuff Tear Shoulder. PRP for Tennis Elbow.

PRP Wrist Extensor carpi ulnaris - ECU tear. Radiofrequency Ablation. Nuclear Medicine and Molecular Imaging. I MIBG Scan. Amyvid PET: Patient Information. Nuclear Medicine Bone Scan. Brain SPECT. Brain SPECT Scan. Ceretec Brain SPECT. DaTscan Procedure Information.

FDG-PET Scan. Gallium Scan. Hepatobiliary Gallbladder Scan. Nuclear Lung Scan. Nuclear Renal Scan. PET Brain. Sestamibi SPECT.

Theranostics for Neuroendocrine Tumors. Thyroid Uptake and Scan. Nuclear Cardiology. Pediatric Imaging. Ultrasound Exam. Abdominal Ultrasound. Abdominal Ultrasound with Doppler. Breast Ultrasound.

Breast Ultrasound Patient Information. Carotid Duplex Scanning. Pelvic Ultrasound. Prostate or Transrectal Ultrasound. Renal Ultrasound. Testicular Ultrasound. Thyroid Ultrasound. Transcranial Doppler Ultrasound. Transcranial Doppler TCD Ultrasound.

Transvaginal Ultrasound. Ultrasound Biopsy. Ultrasound-Guided Liver Biopsy. Ultrasound-Guided Prostate Biopsy. Ultrasound-Guided Thyroid Biopsy. Vascular Ultrasound. Abdominal Aorta Screening Ultrasound. Aorta Iliac Ultrasound.

Arterial Duplex Ultrasound - Legs. Bypass Graft - Legs Ultrasound. Carotid Duplex Ultrasound. Digital Evaluation. Doppler Allen's Test Ultrasound. EVAR - Ultrasound of Aorta after Endovascular Repair of Aortic Aneurysm.

Femoral Vascular Ultrasound. Inferior Vena Cava and Iliac Veins. Intraoperative Duplex Ultrasound. Intravascular Ultrasound. Popliteal Vascular Ultrasound. Renal Artery Stenosis. Renal Transplant Duplex Ultrasound. Saphenous Vein Mapping Ultrasound. Steal: Dialysis Access Arm and Hand Circulation.

Thoracic Outlet. Transcranial Imaging Ultrasound. Upper Extremity Arterial. Upper Extremity DVT. Upper Extremity Vein Mapping. Varicose Vein Surgery Pre-Op Survey. Varicose Vein Survey Post-Op Evaluation. Vasospasm Digital. Venous Duplex Ultrasound - Legs.

Whole Body Imaging. X-Ray and Fluoroscopy. Chest X-Ray. Fistulagram - Abdominal. Lower Extremity X-Ray. Sitz Marker Study. Spine X-Ray. Upper Extremity X-Ray. Parking for 8th Floor Interventional Procedures. Patient Guide. Pre-Registration Questionnaire Forms.

Evening and Weekend Appointments. Companions and Service Animals. Frequently Asked Questions FAQs. Upload Your Outside Images Before You Arrive. How To Get a Copy of Your Imaging Study. Preparing for Your Exam. Alphabetical List of Explanations and Preparations for Exams and Procedures.

Preparing For Your Cardiac Exam. Preparing for Your Image-Guided Procedure. Preparing Your Child for an Imaging Study. General CT Preparation. CT Colonography. General Interventional Radiology Preparation. MRI Preparations.

Magnetic Resonance Imaging Preparations - Abdomen. Magnetic Resonance Imaging Preparations - Abdominal MRI with Deluxe Screening. Magnetic Resonance Imaging Preparations - Abdomen with Elastography. Magnetic Resonance Imaging Preparations - Abdomen with Feraheme.

Magnetic Resonance Imaging Preparations - Abdomen with MRCP. MRI Cardiac Stress Test Preparation. Magnetic Resonance Imaging Preparations - Liver with Spectroscopy. Image-guided therapy, a central concept of 21st century medicine, is the use of any form of medical imaging to plan, perform, and evaluate surgical procedures and therapeutic interventions.

Image-guided therapy techniques help to make surgeries less invasive and more precise, which can lead to shorter hospital stays and fewer repeated procedures.

While the number of specific procedures that use image-guidance is growing, these procedures comprise two general categories: traditional surgeries that become more precise through the use of imaging and newer procedures that use imaging and special instruments to treat conditions of internal organs and tissues without a surgical incision.

The cross-sectional digital imaging modalities Magnetic Resonance Imaging MRI and Computed Tomography CT are the most commonly used modalities of image-guided therapy.

These procedures are also supported by ultrasound, angiography, surgical navigation equipment, tracking tools, and integration software.

Radiologist and former co-Director of the AMIGO suite Ferenc A. Jolesz, MD, established the Image-Guided Therapy Program at BWH in the early 90s. With training in both radiology and neurology, Dr. Jolesz had been envisioning ways that neurological conditions could benefit from the types of targeted, precise treatments that image-guidance provides.

The challenge was to develop the imaging systems that could support these types of techniques. Jolesz began collaborating with a team of engineers from GE Healthcare in to build the first MRI scanner for use during surgical procedures.

The system had two magnets on each side of a patient table, giving surgeons access to the patient who remained situated in the MRI scanner.

In , the Food and Drug Administration approved the first image-guided procedure: MRI-guided focused ultrasound MRgFUS treatment of uterine fibroids.