Surgical Planning Applications Research Articles

Auto-segmentation of hemi-diaphragms in free-breathing dynamic MRI of pediatric subjects with thoracic insufficiency syndrome.

In respiratory disorders such as thoracic insufficiency syndrome (TIS), the quantitative study of the regional motion of the left hemi-diaphragm (LHD) and right hemi-diaphragm (RHD) can give detailed insights into the distribution and severity of the abnormalities in individual patients. Dynamic magnetic resonance imaging (dMRI) is a preferred imaging modality for capturing dynamic images of respiration since dMRI does not involve ionizing radiation and can be obtained under free-breathing conditions. Using 4D images constructed from dMRI of sagittal locations, diaphragm segmentation is an evident step for the said quantitative analysis of LHD and RHD in these 4D images. In this paper, we segment the LHD and RHD in three steps: recognition of diaphragm, delineation of diaphragm, and separation of diaphragm along the mid-sagittal plane into LHD and RHD. The challenges involved in dMRI images are low resolution, motion blur, suboptimal contrast resolution, inconsistent meaning of gray-level intensities for the same object across multiple scans, and low signal-to-noise ratio. We have utilized deep learning (DL) concepts such as Path Aggregation Network and Dual Attention Network for the recognition step, Dense-Net and Residual-Net in an enhanced encoder-decoder architecture for the delineation step, and a combination of GoogleNet and Recurrent Neural Network for the identification of the mid-sagittal plane in the separation step. Due to the challenging images of TIS patients attributed to their highly distorted and variable anatomy of the thorax, in such images we localize the diaphragm using the auto-segmentations of the lungs and the thoraco-abdominal skin. We achieved an average±SD mean-Hausdorff distance of ∼3±3 mm for the delineation step and a positional error of ∼3±3 mm in recognizing the mid-sagittal plane in 100 3D test images of TIS patients with a different set of ∼430 3D images of TIS patients utilized for building the models for delineation, and separation. We showed that auto-segmentations of the diaphragm are indistinguishable from segmentations by experts, in images of near-normal subjects. In addition, the algorithmic identification of the mid-sagittal plane is indistinguishable from its identification by experts in images of near-normal subjects. Motivated by applications in surgical planning for disorders such as TIS, we have shown an auto-segmentation set-up for the diaphragm in dMRI images of TIS pediatric subjects. The results are promising, showing that our system can handle the aforesaid challenges. We intend to use the auto-segmentations of the diaphragm to create the initial ground truth (GT) for newly acquired data and then refining them, to expedite the process of creating GT for diaphragm motion analysis, and to test the efficacy of our proposed method to optimize pre-treatment planning and post-operative assessment of patients with TIS and other disorders.

Transformative Potential and Healthcare Applications of 3D Printing.

Additive manufacturing, sometimes referred to as 3D printing or AM, has numerous applications in industries like manufacturing, aviation, aerospace, vehicles, and education. It has recently made considerable inroads into the healthcare industry, backed by technology breakthroughs such as fused deposition modeling, binder jetting, and inkjet printing. A variety of biomaterials, such as polycaprolactone, polycarbonate, polypropylene, and polylactic acid, have contributed to this increase. This essay delves into the revolutionary possibilities of 3D printing in healthcare, to shed light on the idea of customized medications via the improvement of efficiency and cost. Researchers are using polymers and additive manufacturing to make customized medical devices. However, obstacles including bureaucratic hurdles, technological developments, and the choice of appropriate materials and printers stand in the way of widespread implementation. To fully realize the promise of 3D printing in healthcare, these challenges must be overcome. The article highlights the revolutionary potential of 3D printing in healthcare by following its development from art and construction to customized drugs and patient-specific medical equipment. In addition to addressing issues like quality control and technological limitations, it emphasizes its wide range of applications in surgical planning, dentistry, and anatomical models. The necessity of adapting regulations and instructional programs is highlighted by discussing future trends like bioprinting and FDA-approved innovations. In order to properly utilize 3D printing in healthcare, this adaption is essential. Personalized prescriptions and increased efficacy from the incorporation of 3D printing could revolutionize the healthcare industry. But even with these advances, problems like choosing the right materials and getting over administrative roadblocks prevent widespread implementation. These challenges need to be successfully overcome for 3D printing in healthcare to reach its full potential.

In-House Virtual Planning and 3D Printed Surgical Guides for Reconstructive Rhinoplasty.

Performing rhinoplasty in patients with craniofacial malformations remains a challenge, even for experienced surgeons. Advances in 3D technology and its application in surgical planning and printing of cutting guides and splints have become important tools to improve aesthetic and functional results. To describe an in-house workflow for surgical planning and printing of cutting guides and splints for complex rhinoplasty cases. This article describes an in-house workflow for complex rhinoplasty, as used in the maxillofacial department of a children's hospital specialized in the treatment of cleft and craniofacial malformations. Customized surgical guides help the surgeon to harvest and mold potential septal and costochondral grafts more accurately, to reduce surgical time and to verify the dimensions of the sculpted nasal shape following surgical planning templates. Patient satisfaction degree according to Rhinoplasty Outcome Evaluation questionnaire was 18/24. The presented workflow represents a potential asset in obtaining more accurate and satisfactory results in complex rhinoplasties.

Horizontal Gaze Assessment: An Extensive Narrative Review

Bipedalism was a significant milestone in the evolutionary development of Homo sapiens sapiens, influencing neocortical evolution and subsequent behavioral changes. Coordinated visual and sensory inputs are crucial for posture, environmental interaction, and surgical planning, with horizontal gaze being a pivotal parameter. This narrative review aims to explore various geometric measures used to assess horizontal gaze in patients, highlighting their applications in surgical planning. A literature review was conducted in indexed databases using Mesh terms like "Cervical Vertebrae" and "Visual Fields" along with keywords such as "horizontal gaze" and "sagittal spine parameters." Among 477 initially identified articles, 41 were selected for inclusion after rigorous filtering. The most recognized method for assessing horizontal gaze is the Chin Brow Vertical Angle (CBVA), initially described in patients with ankylosing spondylitis. Clinical photography is employed as a tool for CBVA calculation, while other measures like McGregor slope and Slope of the Line of Sight have been considered as alternatives to CBVA. Each method presents its unique advantages and limitations. This review highlights the need for further research into horizontal gaze measurement methods. Developing novel approaches to determine horizontal gaze can significantly enhance surgical planning and, consequently, improve patient outcomes. The ongoing exploration of these geometric measures offers promising prospects for advancing the field and optimizing patient care.

Statistical Shape and Bone Property Models of Clinical Populations as the Foundation for Biomechanical Surgical Planning: Application to Shoulder Arthroplasty.

This work developed, validated, and compared statistical shape, statistical intensity, and statistical shape and intensity models (SSMs, SIMs, SSIMs) of scapulae from a clinical population. SSMs efficiently describe bone shape variation while SIMs describe bone material property variation, and SSIM's combine description of both variables. This work establishes these models' efficacy and whether they can be used in surgical planning. Models were developed using shoulder arthroplasty data of patients with bone erosion, which is challenging to treat and would benefit from improved surgical planning. Models were created using previously validated nonrigid registration and material property assignment processes that were optimized for scapula characteristics. The models were assessed using standard metrics, anatomical measurements, and correlation analyses. The SSM and SIM specificity and generalization error metrics were 3.4 mm and <1 mm and 184 HU and 156 HU, respectively. The SSIM did not achieve the same level of performance as the SSM and SIM in this study (e.g., shape generalization: SSIM-2.2 mm versus SSM-<1 mm). Anatomical correlation analysis showed that the SSM more effectively and efficiently described shape variation compared to the SSIM. The SSM and SIM modes of variation were not strongly correlated (e.g., rmax = 0.56 for modes explaining ≤2.1% of variance). The SSIM is outperformed by the SSM and SIM and the latter two are not strongly correlated; therefore, using the SSM and SIM in conjunction will generate synthetic bone models with realistic characteristics and thus can be used for biomechanical surgical planning applications.

Multibody dynamics modeling of human mandibular musculoskeletal system and its applications in surgical planning

Multibody dynamics modeling of human mandibular musculoskeletal system and its applications in surgical planning

A semi-automatic seed point-based method for separation of individual vertebrae in 3D surface meshes: a proof of principle study

PurposeThe purpose of this paper is to present and validate a new semi-automated 3D surface mesh segmentation approach that optimizes the laborious individual human vertebrae separation in the spinal virtual surgical planning workflow and make a direct accuracy and segmentation time comparison with current standard segmentation method.MethodsThe proposed semi-automatic method uses the 3D bone surface derived from CT image data for seed point-based 3D mesh partitioning. The accuracy of the proposed method was evaluated on a representative patient dataset. In addition, the influence of the number of used seed points was studied. The investigators analyzed whether there was a reduction in segmentation time when compared to manual segmentation. Surface-to-surface accuracy measurements were applied to assess the concordance with the manual segmentation.ResultsThe results demonstrated a statically significant reduction in segmentation time, while maintaining a high accuracy compared to the manual segmentation. A considerably smaller error was found when increasing the number of seed points. Anatomical regions that include articulating areas tend to show the highest errors, while the posterior laminar surface yielded an almost negligible error.ConclusionA novel seed point initiated surface based segmentation method for the laborious individual human vertebrae separation was presented. This proof-of-principle study demonstrated the accuracy of the proposed method on a clinical CT image dataset and its feasibility for spinal virtual surgical planning applications.

Bioprinting of radiopaque constructs for tissue engineering and understanding degradation behavior by use of Micro-CT

Bioprinting has emerged as a potential technique to fabricate tissue engineering constructs and in vitro models directly using living cells as a raw material for fabrication, conforming to the heterogeneity and architectural complexity of the tissues. In several of tissue engineering and in vitro disease modelling or surgical planning applications, it is desirable to have radiopaque constructs for monitoring and evaluation. In the present work, enhanced radiopaque constructs are generated by substituting Calcium ions with Barium ions for crosslinking of alginate hydrogels. The constructs are characterized for their structural integrity and followed by cell culture studies to evaluate their biocompatibility. This was followed by the radiopacity evaluation. The radiological images obtained by micro-CT technique was further applied to investigate the degradation behavior of the scaffolds. In conclusion, it is observed that barium crosslinking can provide a convenient means to obtain radiopaque constructs with potential for multi-faceted applications.

An Initial Effort to Create a Superficial Femoral Artery Ultrasound Phantom Using 3-Dimensional Printing

Three-dimensional (3D) printing of anatomical structures has yielded valuable models for simulation, education, and surgical planning applications. Applications for 3D printing have continued to expand to include some ultrasound applications. The goal of this effort was to evaluate if a 3D printed model of a superficial femoral artery (SFA) would have realistic ultrasound characteristics. A computed tomography scan was 3D reconstructed and segmented using TeraRecon Aquarius Intuition software (TeraRecon, Foster City, California) to obtain an atherosclerotic SFA geometry. Both the lumen geometry and calcified plaque geometry of the SFA were exported as a stereolithographic (STL) file. The STL file was printed with An Object350 Connex 3D System using 2 different materials selected based on published elastic modulus data. VeroWhite was selected for the calcified plaque and TangoPlus Clear was selected for the artery wall. After printing, the SFA model was imaged in a water bath with a Phillips IU22 duplex ultrasound console and L12-9 ultrasound probe. Ultrasound imaging of the SFA model yielded grayscale views of artery geometry. Lumen geometry of the SFA model was similar to the actual artery geometry. Ultrasound was able to discern between the 3D print materials and visualize regions with stenosis. Suboptimal ultrasound parameters of echogenicity and wave velocity noted to differ from biological tissue. Total 3D print material cost was estimated at below $20. Although the 3D printed model did not have fully accurate ultrasound characteristics, it still provided realistic imaging. With further research, 3D printed models may offer a low-cost alternative for ultrasound phantoms.

Technical and Clinical Factors Affecting Success Rate of a Deep Learning Method for Pancreas Segmentation on CT

Accurate pancreas segmentation has application in surgical planning, assessment of diabetes, and detection and analysis of pancreatic tumors. Factors that affect pancreas segmentation accuracy have not been previously reported. The purpose of this study is to identify technical and clinical factors that adversely affect the accuracy of pancreas segmentation on CT. In this IRB and HIPAA compliant study, a deep convolutional neural network was used for pancreas segmentation in a publicly available archive of 82 portal-venous phase abdominal CT scans of 53 men and 29 women. The accuracies of the segmentations were evaluated by the Dice similarity coefficient (DSC). The DSC was then correlated with demographic and clinical data (age, gender, height, weight, body mass index), CT technical factors (image pixel size, slice thickness, presence or absence of oral contrast), and CT imaging findings (volume and attenuation of pancreas, visceral abdominal fat, and CT attenuation of the structures within a 5 mm neighborhood of the pancreas). The average DSC was 78% ± 8%. Factors that were statistically significantly correlated with DSC included body mass index (r = 0.34, p < 0.01), visceral abdominal fat (r = 0.51, p < 0.0001), volume of the pancreas (r = 0.41, p = 0.001), standard deviation of CT attenuation within the pancreas (r = 0.30, p = 0.01), and median and average CT attenuation in the immediate neighborhood of the pancreas (r = -0.53, p < 0.0001 and r = -0.52, p < 0.0001). There were no significant correlations between the DSC and the height, gender, or mean CT attenuation of the pancreas. Increased visceral abdominal fat and accumulation of fat within or around the pancreas are major factors associated with more accurate segmentation of the pancreas. Potential applications of our findings include assessment of pancreas segmentation difficulty of a particular scan or dataset and identification of methods that work better for more challenging pancreas segmentations.

A noninvasive method for the determination of in vivo mitral valve leaflet strains.

Assessment of mitral valve (MV) function is important in many diagnostic, prognostic, and surgical planning applications for treatment of MV disease. Yet, to date, there are no accepted noninvasive methods for determination of MV leaflet deformation, which is a critical metric of MV function. In this study, we present a novel, completely noninvasive computational method to estimate MV leaflet in-plane strains from clinical-quality real-time three-dimensional echocardiography (rt-3DE) images. The images were first segmented to produce meshed medial-surface leaflet geometries of the open and closed states. To establish material point correspondence between the two states, an image-based morphing pipeline was implemented within a finite element (FE) modeling framework in which MV closure was simulated by pressurizing the open-state geometry, and local corrective loads were applied to enforce the actual MV closed shape. This resulted in a complete map of local systolic leaflet membrane strains, obtained from the final FE mesh configuration. To validate the method, we utilized an extant in vitro database of fiducially labeled MVs, imaged in conditions mimicking both the healthy and diseased states. Our method estimated local anisotropic in vivo strains with less than 10% error and proved to be robust to changes in boundary conditions similar to those observed in ischemic MV disease. Next, we applied our methodology to ovine MVs imaged in vivo with rt-3DE and compared our results to previously published findings of in vivo MV strains in the same type of animal as measured using surgically sutured fiducial marker arrays. In regions encompassed by fiducial markers, we found no significant differences in circumferential(P = 0.240) or radial (P = 0.808) strain estimates between the marker-based measurements and our novel noninvasive method. This method can thus be used for model validation as well as for studies of MV disease and repair.

3D Printing: current use in facial plastic and reconstructive surgery.

To review the use of three-dimensional (3D) printing in facial plastic and reconstructive surgery, with a focus on current uses in surgical training, surgical planning, clinical outcomes, and biomedical research. To evaluate the limitations and future implications of 3D printing in facial plastic and reconstructive surgery. Studies reviewed demonstrated 3D printing applications in surgical planning including accurate anatomic biomodels, surgical cutting guides in reconstruction, and patient-specific implants fabrication. 3D printing technology also offers access to well tolerated, reproducible, and high-fidelity/patient-specific models for surgical training. Emerging research in 3D biomaterial printing have led to the development of biocompatible scaffolds with potential for tissue regeneration in reconstruction cases involving significant tissue absence or loss. Major limitations of utilizing 3D printing technology include time and cost, which may be offset by decreased operating times and collaboration between departments to diffuse in-house printing costs SUMMARY: The current state of the literature shows promising results, but has not yet been validated by large studies or randomized controlled trials. Ultimately, further research and advancements in 3D printing technology should be supported as there is potential to improve resident training, patient care, and surgical outcomes.

Validation of a method for retroperitoneal tumor segmentation.

In 2005, an application for surgical planning called AYRA[Formula: see text] was designed and validated by different surgeons and engineers at the Virgen del Rocío University Hospital, Seville (Spain). However, the segmentation methods included in AYRA and in other surgical planning applications are not able to segment accurately tumors that appear in soft tissue. The aims of this paper are to offer an exhaustive validation of an accurate semiautomatic segmentation tool to delimitate retroperitoneal tumors from CT images and to aid physicians in planning both radiotherapy doses and surgery. A panel of 6 experts manually segmented 11 cases of tumors, and the segmentation results were compared exhaustively with: the results provided by a surgical planning tool (AYRA), the segmentations obtained using a radiotherapy treatment planning system (Pinnacle[Formula: see text]), the segmentation results obtained by a group of experts in the delimitation of retroperitoneal tumors and the segmentation results using the algorithm under validation. 11 cases of retroperitoneal tumors were tested. The proposed algorithm provided accurate results regarding the segmentation of the tumor. Moreover, the algorithm requires minimal computational time-an average of 90.5% less than that required when manually contouring the same tumor. A method developed for the semiautomatic selection of retroperitoneal tumor has been validated in depth. AYRA, as well as other surgical and radiotherapy planning tools, could be greatly improved by including this algorithm.

Image-based patient-specific ventricle models with fluid–structure interaction for cardiac function assessment and surgical design optimization

Recent advances in medical imaging technology and computational modeling techniques are making it possible that patient-specific computational ventricle models be constructed and used to test surgical hypotheses and replace empirical and often risky clinical experimentation to examine the efficiency and suitability of various reconstructive procedures in diseased hearts. In this paper, we provide a brief review on recent development in ventricle modeling and its potential application in surgical planning and management of Tetralogy of Fallot (ToF) patients. Aspects of data acquisition, model selection and construction, tissue material properties, ventricle layer structure and tissue fiber orientations, pressure condition, model validation and virtual surgery procedures (changing patient-specific ventricle data and perform computer simulation) were reviewed. Results from a case study using patient-specific cardiac magnetic resonance (CMR) imaging and right/left ventricle and patch (RV/LV/Patch) combination model with fluid–structure interactions (FSI) were reported. The models were used to evaluate and optimize human pulmonary valve replacement/insertion (PVR) surgical procedure and patch design and test a surgical hypothesis that PVR with small patch and aggressive scar tissue trimming in PVR surgery may lead to improved recovery of RV function and reduced stress/strain conditions in the patch area.

Three-Dimensional Hemodynamics in the Human Pulmonary Arteries Under Resting and Exercise Conditions

The biomechanical forces associated with blood flow have been shown to play a role in pulmonary vascular cell health and disease. Therefore, the quantification of human pulmonary artery hemodynamic conditions under resting and exercise states can be useful in investigating the physiology of disease development and treatment outcomes. In this study, a combined magnetic resonance imaging and computational fluid dynamics approach was used to quantify pulsatile flow fields, wall shear stress (WSS), oscillations in WSS (OSI), and energy efficiency in six subject-specific models of the human pulmonary vasculature with high spatial and temporal resolution. Averaging over all subjects, WSS was found to increase from 19.8±4.0 to 51.8±6.7 dynes/cm2, and OSI was found to decrease from 0.094±0.016 to 0.081±0.015 in the proximal pulmonary arteries between rest and exercise conditions (p<0.05). These findings demonstrate the localized, biomechanical effects of exercise. Furthermore, an average decrease of 10% in energy efficiency was noted between rest and exercise. These data indicate the amount of energy dissipation that typically occurs with exercise and may be useful in future surgical planning applications.

Minimally Invasive Spinal Surgery

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

A robust framework for soft tissue simulations with application to modeling brain tumor mass effect in 3D MR images

We present a framework for black-box and flexible simulation of soft tissue deformation for medical imaging and surgical planning applications. Our main motivation in the present work is to develop robust algorithms that allow batch processing for registration of brains with tumors to statistical atlases of normal brains and construction of brain tumor atlases. We describe a fully Eulerian formulation able to handle large deformations effortlessly, with a level-set-based approach for evolving fronts. We use a regular grid—fictitious domain method approach, in which we approximate coefficient discontinuities, distributed forces and boundary conditions. This approach circumvents the need for unstructured mesh generation, which is often a bottleneck in the modeling and simulation pipeline. Our framework employs penalty approaches to impose boundary conditions and uses a matrix-free implementation coupled with a multigrid-accelerated Krylov solver. The overall scheme results in a scalable method with minimal storage requirements and optimal algorithmic complexity. We illustrate the potential of our framework to simulate realistic brain tumor mass effects at reduced computational cost, for aiding the registration process towards the construction of brain tumor atlases.

Confocal arthroscopy-based patient-specific constitutive models of cartilaginous tissues—I: development of a microstructural model

Current development of a laser scanning confocal arthroscope within our school will enable 3D microscopic imaging of joint tissues in vivo. Such an instrument could be useful, for example, in assessing the microstructural condition of the living tissues without physical biopsy. It is envisaged also that linked to a suitable microstructural constitutive formulation, such imaging could allow non-invasive patient-specific estimation of tissue mechanical performance. Such a procedure could have applications in surgical planning and simulation, and assessment of engineered tissue replacements, where tissue biopsy is unacceptable. In this first of two papers the development of a suitable constitutive framework for generating such estimates is reported. A microstructure-based constitutive formulation for cartilaginous tissues is presented. The model extends existing fibre composite-type models and accounts for strain-rate sensitivity of the tissue mechanical response through incorporation of a viscoelastic fibre phase. Importantly, the model is constructed so as to allow direct incorporation of structural data from confocal images. A finite element implementation of the formulation suitable for incorporation within commercial codes is also presented.

Preliminary experience with medical applications of rapid prototyping by selective laser sintering

Rapid prototyping techniques, originally developed for building components from computer aided designs in the motor industry, are now being applied in medicine to build models of human anatomy from high resolution multiplanar imaging data such a computed tomography (CT). The established technique of stereolithography and the more recent selective laser sintering (SLS), both build up an object layer by layer. Models have applications in surgical planning, for the design of customised implants and for training. Preliminary experience of using the SLS technique for medical applications is described, addressing questions regarding image processing, data transfer and manufacture. Pilot models, built from nylon, included two skulls (a child with craniosynostosis and an adult with hypertelorism) and a normal femur which was modelled for use in a bioengineering test of an artificial hip. The dimensions of the models were found to be in good agreement with the CT data from which they were built—for the child's skull the difference between the model and the CT data was less than 1.0±0.5 mm in each direction. Our experience showed that, with care, a combination of existing software packages may be used for data conversion. Ideally, image data of high spatial resolution should be used. The pilot models generated sufficient clinical interest for the technique to be pursued in the orthopaedic field.

MR Imaging in the Management of Thoracic Malignancies

CT remains the modality of choice for evaluating patients with a thoracic malignancy. In specific cases MR imaging can provide useful information that cannot be obtained with CT, and thus is useful as a problem solving tool. Advantages of MR imaging include superb demonstration of vessels and vessel/mass relationships, direct multiplanar imaging capability, and the potential for tissue characterization. MR imaging is useful in staging the patient with lung cancer when vascular or mediastinal invasion is in question. Its specific applications in surgical planning include the question of chest wall invasion, brachial plexus involvement, and transgression of the diaphragm, pericardium, or lung apex. Multiplanar imaging is useful in radiation therapy planning, displaying lesion extent in a coronal or sagittal format rather than on multiple axial images. Multiplanar capability also resolves problem areas for CT such as the aortopulmonic window, subcarinal region, and lesions at the cervicothoracic or thoracoabdominal junction. Structures such as the trachea and superior vena cava can be evaluated in their plane of anatomic orientation. Routine spin-echo and fast (GRASS) imaging of mediastinal vessels is useful in the evaluation of venous thrombosis as a result of catheters or tumors. The diagnosis and follow-up are obtained without the use of intravenous contrast material or radiation. When CT cannot evaluate vessels adequately because of surgical clip artifacts or postoperative distortion of anatomy, MR imaging is useful in the determination of vessel patency as well as identification of tumor recurrence. Cardiac masses are very well demonstrated by MR imaging. A unique feature of MR imaging is its potential for tissue characterization and ability to assess disease activity. Lymphoma evaluation is an active area of research. MR imaging can evaluate the radiated patient for tumor response and recurrence. Fibrous tissue remains of low signal intensity on T2-weighted images, whereas tumor has increased signal intensity. MR imaging may detect tumor recurrence before an increase in the size of a residual lymphoma mass and before clinical recurrence is evident. The area of increased signal can also serve as a guide to the appropriate site for biopsy to confirm recurrence. In addition, MR imaging can help characterize some adrenal and liver masses, potentially helping to avoid more invasive diagnostic procedures. At the current time MR spectroscopy does not have a clinical role in thoracic malignancies, but it may be a powerful tool in the future for diagnosis and management.