Modality-Agnostic Learning for Medical Image Segmentation Using Multi-modality Self-distillation

Medical image segmentation of tumors and organs at risk is a time-consuming yet critical process in the clinic that utilizes multi-modality imaging (e.g, different acquisitions, data types, and sequences) to increase segmentation precision. In this paper, we propose a novel framework, Modality-Agnostic learning through Multi-modality Self-dist-illation (MAG-MS), to investigate the impact of input modalities on medical image segmentation. MAG-MS distills knowledge from the fusion of multiple modalities and applies it to enhance representation learning for individual modalities. Thus, it provides a versatile and efficient approach to handle limited modalities during testing. Our extensive experiments on benchmark datasets demonstrate the high efficiency of MAG-MS and its superior segmentation performance than current state-of-the-art methods. Furthermore, using MAG-MS, we provide valuable insight and guidance on selecting input modalities for medical image segmentation tasks

FMEA of MR-Only Treatment Planning in the Pelvis

Purpose: To evaluate the implementation of a magnetic resonance (MR)-only workflow (ie, implementing MR simulation as the primary planning modality) using failure mode and effects analysis (FMEA) in comparison with a conventional multimodality (MR simulation in conjunction with computed tomography simulation) workflow for pelvis external beam planning. Methods and Materials: To perform the FMEA, a multidisciplinary 9-member team was assembled and developed process maps, identified potential failure modes (FMs), and assigned numerical values to the severity (S), frequency of occurrence (O), and detectability (D) of those FMs. Risk priority numbers (RPNs) were calculated via the product of S, O, and D as a metric for evaluating relative patient risk. An alternative 3-digit composite number (SOD) was computed to emphasize high-severity FMs. Fault tree analysis identified the causality chain leading to the highest-severity FM. Results: Seven processes were identified, 3 of which were shared between workflows. Image fusion and target delineation subprocesses using the conventional workflow added 9 and 10 FMs, respectively, with 6 RPNs \u3e100. By contrast, synthetic computed tomography generation introduced 3 major subprocesses and propagated 46 unique FMs, 15 with RPNs \u3e100. For the conventional workflow, the largest RPN scores were introduced by image fusion (RPN range, 120-192). For the MR-only workflow, the highest RPN scores were from inaccuracies in target delineation resulting from misinterpretation of MR images (RPN = 240) and insufficient management of patient- and system-level distortions (RPN = 210 and 168, respectively). Underestimation (RPN = 140) or overestimation (RPN = 192) of bone volume produced higher RPN scores. The highest SODs for both workflows were related to changes in target location because of internal anatomy changes (conventional = 961, MR-only = 822). Conclusions: FMEA identified areas for mitigating risk in MR-only pelvis RTP, and SODs identified high-severity process modes. Efforts to develop a quality management program to mitigate high FMs are underway

Development and evaluation of a novel MR-compatible pelvic end-to-end phantom

MR-only treatment planning and MR-IGRT leverage MRI\u27s powerful soft tissue contrast for high-precision radiation therapy. However, anthropomorphic MR-compatible phantoms are currently limited. This work describes the development and evaluation of a custom-designed, modular, pelvic end-to-end (PETE) MR-compatible phantom to benchmark MR-only and MR-IGRT workflows. For construction considerations, subject data were assessed for phantom/skeletal geometry and internal organ kinematics to simulate average male pelvis anatomy. Various materials for the bone, bladder, and rectum were evaluated for utility within the phantom. Once constructed, PETE underwent CT-SIM, MR-Linac, and MR-SIM imaging to qualitatively assess organ visibility. Scans were acquired with various bladder and rectal volumes to assess component interactions, filling capabilities, and filling reproducibility via volume and centroid differences. PETE simulates average male pelvis anatomy and comprises an acrylic body oval (height/width = 23.0/38.1 cm) and a cast-mold urethane skeleton, with silicone balloons simulating bladder and rectum, a silicone sponge prostate, and hydrophilic poly(vinyl alcohol) foam to simulate fat/tissue separation between organs. Access ports enable retrofitting the phantom with other inserts including point/film-based dosimetry options. Acceptable contrast was achievable in CT-SIM and MR-Linac images. However, the bladder was challenging to distinguish from background in CT-SIM. The desired contrast for T1-weighted and T2-weighted MR-SIM (dark and bright bladders, respectively) was achieved. Rectum and bone exhibited no MR signal. Inputted volumes differed by(CT-SIM) and bladder (MR-SIM) volumes. Increasing bladder and rectal volumes induced organ displacements and shape variations. Reproduced volumes differed b

Quantifying inter-fraction cardiac substructure displacement during radiotherapy via magnetic resonance imaging guidance

Emerging evidence suggests cardiac substructures are highly radiosensitive during radiation therapy for cancer treatment. However, variability in substructure position after tumor localization has not been well characterized. This study quantifies inter-fraction displacement and planning organ at risk volumes (PRVs) of substructures by leveraging the excellent soft tissue contrast of magnetic resonance imaging (MRI). Eighteen retrospectively evaluated patients underwent radiotherapy for intrathoracic tumors with a 0.35 T MRI-guided linear accelerator. Imaging was acquired at a 17–25 s breath-hold (resolution 1.5 × 1.5 × 3 mm3). Three to four daily MRIs per patient (n = 71) were rigidly registered to the planning MRI-simulation based on tumor matching. Deep learning or atlas-based segmentation propagated 13 substructures (e.g., chambers, coronary arteries, great vessels) to daily MRIs and were verified by two radiation oncologists. Daily centroid displacements from MRI-simulation were quantified and PRVs were calculated. Across substructures, inter-fraction displacements for 14% in the left–right, 18% in the anterior-posterior, and 21% of fractions in the superior-inferior were \u3e 5 mm. Due to lack of breath-hold compliance, ~4% of all structures shifted \u3e 10 mm in any axis. For the chambers, median displacements were 1.8, 1.9, and 2.2 mm in the left–right, anterior-posterior, and superior-inferior axis, respectively. Great vessels demonstrated larger displacements (\u3e 3 mm) in the superior-inferior axis (43% of shifts) and were only 25% (left–right) and 29% (anterior-posterior) elsewhere. PRVs from 3 to 5 mm were determined as anisotropic substructure-specific margins. This exploratory work derived substructure-specific safety margins to ensure highly effective cardiac sparing. Findings require validation in a larger cohort for robust margin derivation and for applications in prospective clinical trials

Optimization of a novel large field of view distortion phantom for MR-only treatment planning

PURPOSE: MR-only treatment planning requires images of high geometric fidelity, particularly for large fields of view (FOV). However, the availability of large FOV distortion phantoms with analysis software is currently limited. This work sought to optimize a modular distortion phantom to accommodate multiple bore configurations and implement distortion characterization in a widely implementable solution. METHOD AND MATERIALS: To determine candidate materials, 1.0 T MR and CT images were acquired of twelve urethane foam samples of various densities and strengths. Samples were precision-machined to accommodate 6 mm diameter paintballs used as landmarks. Final material candidates were selected by balancing strength, machinability, weight, and cost. Bore sizes and minimum aperture width resulting from couch position were tabulated from the literature (14 systems, 5 vendors). Bore geometry and couch position were simulated using MATLAB to generate machine-specific models to optimize the phantom build. Previously developed software for distortion characterization was modified for several magnet geometries (1.0 T, 1.5 T, 3.0 T), compared against previously published 1.0 T results, and integrated into the 3D Slicer application platform. RESULTS: All foam samples provided sufficient MR image contrast with paintball landmarks. Urethane foam (compressive strength ∼1000 psi, density ~20 lb/ft3 ) was selected for its accurate machinability and weight characteristics. For smaller bores, a phantom version with the following parameters was used: 15 foam plates, 55 × 55 × 37.5 cm3 (L×W×H), 5,082 landmarks, and weight ~30 kg. To accommodate \u3e 70 cm wide bores, an extended build used 20 plates spanning 55 × 55 × 50 cm3 with 7,497 landmarks and weight ~44 kg. Distortion characterization software was implemented as an external module into 3D Slicer\u27s plugin framework and results agreed with the literature. CONCLUSION: The design and implementation of a modular, extendable distortion phantom was optimized for several bore configurations. The phantom and analysis software will be available for multi-institutional collaborations and cross-validation trials to support MR-only planning

Performance of deep learning synthetic CTs for MR-only brain radiation therapy

PURPOSE: To evaluate the dosimetric and image-guided radiation therapy (IGRT) performance of a novel generative adversarial network (GAN) generated synthetic CT (synCT) in the brain and compare its performance for clinical use including conventional brain radiotherapy, cranial stereotactic radiosurgery (SRS), planar, and volumetric IGRT. METHODS AND MATERIALS: SynCT images for 12 brain cancer patients (6 SRS, 6 conventional) were generated from T1-weighted postgadolinium magnetic resonance (MR) images by applying a GAN model with a residual network (ResNet) generator and a convolutional neural network (CNN) with 5 convolutional layers as the discriminator that classified input images as real or synthetic. Following rigid registration, clinical structures and treatment plans derived from simulation CT (simCT) images were transferred to synCTs. Dose was recalculated for 15 simCT/synCT plan pairs using fixed monitor units. Two-dimensional (2D) gamma analysis (2%/2 mm, 1%/1 mm) was performed to compare dose distributions at isocenter. Dose-volume histogram (DVH) metrics (D(95%) , D(99%) , D(0.2cc,) and D(0.035cc) ) were assessed for the targets and organ at risks (OARs). IGRT performance was evaluated via volumetric registration between cone beam CT (CBCT) to synCT/simCT and planar registration between KV images to synCT/simCT digital reconstructed radiographs (DRRs). RESULTS: Average gamma passing rates at 1%/1mm and 2%/2mm were 99.0 ± 1.5% and 99.9 ± 0.2%, respectively. Excellent agreement in DVH metrics was observed (mean difference ≤0.10 ± 0.04 Gy for targets, 0.13 ± 0.04 Gy for OARs). The population averaged mean difference in CBCT-synCT registrations were \u3c0.2 mm and 0.1 degree different from simCT-based registrations. The mean difference between kV-synCT DRR and kV-simCT DRR registrations was \u3c0.5 mm with no statistically significant differences observed (P \u3e 0.05). An outlier with a large resection cavity exhibited the worst-case scenario. CONCLUSION: Brain GAN synCTs demonstrated excellent performance for dosimetric and IGRT endpoints, offering potential use in high precision brain cancer therapy

Application of Continuous Positive Airway Pressure for Thoracic Respiratory Motion Management: An Assessment in a Magnetic Resonance Imaging-Guided Radiation Therapy Environment

PURPOSE: Patient tolerability of magnetic resonance (MR)-guided radiation treatment delivery is limited by the need for repeated deep inspiratory breath holds (DIBHs). This volunteer study assessed the feasibility of continuous positive airway pressure (CPAP) with and without DIBH for respiratory motion management during radiation treatment with an MR-linear accelerator (MR-linac). METHODS AND MATERIALS: MR imaging safety was first addressed by placing the CPAP device in an MR-safe closet and configuring a tube circuit via waveguide to the magnet bore. Reproducibility and linearity of the final configuration were assessed. Six healthy volunteers underwent thoracic imaging in a 0.35T MR-linac, with one free breathing (FB) and 2 DIBH acquisitions being obtained at 5 pressures from 0 to 15 cm-H(2)O. Lung and heart volumes and positions were recorded; repeatability was assessed by comparing 2 consecutive DIBH scans. Blinded reviewers graded images for motion artifact using a 3-point grading scale. Participants completed comfort and perception surveys before and after imaging sessions. RESULTS: Compared with FB alone, FB-10, FB-12, and FB-15 cm H(2)O significantly increased lung volumes (+23%, +34%, +44%; all P \u3c.05) and inferiorly displaced the heart (0.86 cm, 0.96 cm, 1.18 cm; all P \u3c . 05). Lung volumes were significantly greater with DIBH-0 cm H(2)O compared with FB-15 cm H(2)O (+105% vs +44%, P = .01), and DIBH-15 cm H(2)O yielded additional volume increase (+131% vs +105%, P = .01). Adding CPAP to DIBH decreased lung volume differences between consecutive breath holds (correlation coefficient 0.97 at 15 cm H(2)O vs 0.00 at 0 cm H(2)O). The addition of 15 cm H(2)O CPAP reduced artifact scores (P = .03) compared with FB; all DIBH images (0-15 cm H(2)O) had less artifact (P \u3c .01). CONCLUSIONS: This work demonstrates the feasibility of integrating CPAP in an MR-linac environment in healthy volunteers. Extending this work to a larger patient cohort is warranted to further establish the role of CPAP as an alternative and concurrent approach to DIBH in MR-guided radiation therapy

Characterizing Sensitive Cardiac Substructure Excursion Due to Respiration

PURPOSE: Whole-heart dose metrics are not as strongly linked to late cardiac morbidities as radiation doses to individual cardiac substructures. Our aim was to characterize the excursion and dosimetric variation throughout respiration of sensitive cardiac substructures for future robust safety margin design. METHODS AND MATERIALS: Eleven patients with cancer treatments in the thorax underwent 4-phase noncontrast 4-dimensional computed tomography (4DCT) with T2-weighted magnetic resonance imaging in end-exhale. The end-exhale phase of the 4DCT was rigidly registered with the magnetic resonance imaging and refined with an assisted alignment surrounding the heart from which 13 substructures (chambers, great vessels, coronary arteries, etc) were contoured by a radiation oncologist on the 4DCT. Contours were deformed to the other respiratory phases via an intensity-based deformable registration for radiation oncologist verification. Measurements of centroid and volume were evaluated between phases. Mean and maximum dose to substructures were evaluated across respiratory phases for the breast (n = 8) and thoracic cancer (n = 3) cohorts. RESULTS: Paired t tests revealed reasonable maintenance of geometric and anatomic properties (P \u3c .05 for 4/39 volume comparisons). Maximum displacements \u3e5 mm were found for 24.8%, 8.5%, and 64.5% of the cases in the left-right, anterior-posterior, and superior-inferior axes, respectively. Vector displacements were largest for the inferior vena cava and the right coronary artery, with displacements up to 17.9 mm. In breast, the left anterior descending artery D(mean) varied 3.03 ± 1.75 Gy (range, 0.53-5.18 Gy) throughout respiration whereas lung showed patient-specific results. Across all patients, whole heart metrics were insensitive to breathing phase (mean and maximum dose variations \u3c0.5 Gy). CONCLUSIONS: This study characterized the intrafraction displacement of the cardiac substructures through the respiratory cycle and highlighted their increased dosimetric sensitivity to local dose changes not captured by whole heart metrics. Results suggest value of cardiac substructure margin generation to enable more robust cardiac sparing and to reduce the effect of respiration on overall treatment plan quality