Quantifying Intrafraction Motion and the Impact of Gating for Magnetic Resonance Imaging-Guided Stereotactic Radiation therapy for Prostate Cancer: Analysis of the Magnetic Resonance Imaging Arm From the MIRAGE Phase 3 Randomized Trial.

PURPOSE: Real-time intrafraction tracking/gating is an integral component of magnetic resonance imaging-guided radiation therapy (MRgRT) and may have contributed to the acute toxicity reduction during prostate stereotactic body radiation therapy observed on the MRgRT-arm of the MIRAGE (MAGNETIC RESONANCE IMAGING-GUIDED Stereotactic Body Radiotherapy for Prostate Cancer) randomized trial (NCT04384770). Herein we characterized intrafraction prostate motion and assessed gating effectiveness. METHODS AND MATERIALS: Seventy-nine patients were treated on an MR-LINAC. Real-time cine imaging was acquired at 4Hz in a sagittal plane. If >10% of the prostate area moved outside of a 3-mm gating boundary, an automatic beam hold was initiated. An in-house tool was developed to retrospectively extract gating signal for all patients and identify the tracked prostate in each cine frame for a subgroup of 40 patients. The fraction of time the prostate was within the gating window was defined as the gating duty cycle (GDC). RESULTS: A total of 391 treatments from 79 patients were analyzed. Median GDC was 0.974 (IQR, 0.916-0.983). Fifty (63.2%) and 24 (30.4%) patients had at least 1 fraction with GDC ≤0.9 and GDC ≤0.8, respectively. Incidence of low GDC fractions among patients appeared stochastic. Patients with minimum GDC <0.8 trended toward more frequent grade 2 genitourinary toxicity compared with those with minimum GDC >0.8 (38% vs 18%, P = .065). Prostate intrafraction motion was mostly along the bladder-rectum axis and predominantly in the superior-anterior direction. Motion in the inferior-posterior direction was associated with significantly higher rate of acute grade 2 genitourinary toxicity (66.7% vs 13.9%, P = .001). Gating limited mean prostate motion during treatment delivery in fractions with a GDC <0.9 (<0.8) to 2.9 mm (2.9 mm) versus 4.1 mm (4.7 mm) for ungated motion. CONCLUSIONS: Fractions with large intrafraction motion were associated with increased toxicity and their occurrence among patients appears stochastic. Real-time tracking/gating effectively mitigated this motion and is likely a major contributing factor of acute toxicity reduction associated with MRgRT.

Seizure outcomes following single-fraction versus hypofractionated radiosurgery for brain metastases: a single-center experience.

OBJECTIVE: Although seizures are a relatively common phenomenon in the setting of brain metastases (BMs), there are no discrete recommendations regarding the use of antiepileptic drugs (AEDs) in this population, either in general or in the context of treatment. The authors' aim was to better understand the underlying pathological factors as well as the therapeutic techniques that may lead to seizures following the radiosurgical treatment of BMs with the goal of guiding appropriate AED prophylaxis. METHODS: Adult patients with BMs diagnosed from 2013 to 2020 at a single academic institution and treated with radiation therapy were included in this study. The authors evaluated factors associated with the incidence of seizures throughout the disease course, with a focus on seizures in the 90-day period following stereotactic radiosurgery (SRS). RESULTS: Four hundred forty-four patients with newly diagnosed BMs were identified, 10% of whom had seizures at the time of presentation and 28% of whom had a seizure at any point during the study period. Tumor histology was significantly associated with initial seizure risk. AED use was highly variable. In the 90-day post-SRS period, the summed total planning target volume (PTV) was independently predictive of post-SRS seizures, regardless of the fractionation scheme (single fraction vs hypofractionated) and other clinical factors. The number of supratentorial BMs was not predictive of post-SRS seizures. CONCLUSIONS: PTV is a superior predictor of post-SRS seizures relative to the number of supratentorial BMs, as it serves as a volumetric proxy for intracranial disease burden. A larger PTV, alongside tumor histology and prior seizure history, should be considered in the decision-making process for AED use following radiosurgery.

A survival prediction model via interpretable machine learning for patients with oropharyngeal cancer following radiotherapy.

PURPOSE: To explore interpretable machine learning (ML) methods, with the hope of adding more prognosis value, for predicting survival for patients with Oropharyngeal-Cancer (OPC). METHODS: A cohort of 427 OPC patients (Training 341, Test 86) from TCIA database was analyzed. Radiomic features of gross-tumor-volume (GTV) extracted from planning CT using Pyradiomics, and HPV p16 status, etc. patient characteristics were considered as potential predictors. A multi-level dimension reduction algorithm consisting of Least-Absolute-Selection-Operator (Lasso) and Sequential-Floating-Backward-Selection (SFBS) was proposed to effectively remove redundant/irrelevant features. The interpretable model was constructed by quantifying the contribution of each feature to the Extreme-Gradient-Boosting (XGBoost) decision by Shapley-Additive-exPlanations (SHAP) algorithm. RESULTS: The Lasso-SFBS algorithm proposed in this study finally selected 14 features, and our prediction model achieved an area-under-ROC-curve (AUC) of 0.85 on the test dataset based on this feature set. The ranking of the contribution values calculated by SHAP shows that the top predictors that were most correlated with survival were ECOG performance status, wavelet-LLH_firstorder_Mean, chemotherapy, wavelet-LHL_glcm_InverseVariance, tumor size. Those patients who had chemotherapy, with positive HPV p16 status, and lower ECOG performance status, tended to have higher SHAP scores and longer survival; who had an older age at diagnosis, heavy drinking and smoking pack year history, tended to lower SHAP scores and shorter survival. CONCLUSION: We demonstrated predictive values of combined patient characteristics and imaging features for the overall survival of OPC patients. The multi-level dimension reduction algorithm can reliably identify the most plausible predictors that are mostly associated with overall survival. The interpretable patient-specific survival prediction model, capturing correlations of each predictor and clinical outcome, was developed to facilitate clinical decision-making for personalized treatment.

Fully automated segmentation of prostatic urethra for MR-guided radiation therapy.

PURPOSE: Accurate delineation of the urethra is a prerequisite for urethral dose reduction in prostate radiotherapy. However, even in magnetic resonance-guided radiation therapy (MRgRT), consistent delineation of the urethra is challenging, particularly in online adaptive radiotherapy. This paper presented a fully automatic MRgRT-based prostatic urethra segmentation framework. METHODS: Twenty-eight prostate cancer patients were included in this study. In-house 3D half fourier single-shot turbo spin-echo (HASTE) and turbo spin echo (TSE) sequences were used to image the Foley-free urethra on a 0.35 T MRgRT system. The segmentation pipeline uses 3D nnU-Net as the base and innovatively combines ground truth and its corresponding radial distance (RD) map during training supervision. Additionally, we evaluate the benefit of incorporating a convolutional long short term memory (LSTM-Conv) layer and spatial recurrent convolution layer (RCL) into nnU-Net. A novel slice-by-slice simple exponential smoothing (SEPS) method specifically for tubular structures was used to post-process the segmentation results. RESULTS: The experimental results show that nnU-Net trained using a combination of Dice, cross-entropy and RD achieved a Dice score of 77.1 ± 2.3% in the testing dataset. With SEPS, Hausdorff distance (HD) and 95% HD were reduced to 2.95 ± 0.17 mm and 1.84 ± 0.11 mm, respectively. LSTM-Conv and RCL layers only minimally improved the segmentation precision. CONCLUSION: We present the first Foley-free MRgRT-based automated urethra segmentation study. Our method is built on a data-driven neural network with novel cost functions and a post-processing step designed for tubular structures. The performance is consistent with the need for online and offline urethra dose reduction in prostate radiotherapy.

Automated Tumor Segmentation in Radiotherapy.

Autosegmentation of gross tumor volumes holds promise to decrease clinical demand and to provide consistency across clinicians and institutions for radiation treatment planning. Additionally, autosegmentation can enable imaging analyses such as radiomics to construct and deploy large studies with thousands of patients. Here, we review modern results that utilize deep learning approaches to segment tumors in 5 major clinical sites: brain, head and neck, thorax, abdomen, and pelvis. We focus on approaches that inch closer to clinical adoption, highlighting winning entries in international competitions, unique network architectures, and novel ways of overcoming specific challenges. We also broadly discuss the future of gross tumor volumes autosegmentation and the remaining barriers that must be overcome before widespread replacement or augmentation of manual contouring.

Relapse patterns and radiation dose exposure in IDH wild-type glioblastoma at first radiographic recurrence following chemoradiation.

PURPOSE: To quantify the radiation dose distribution and lesion morphometry (shape) at baseline, prior to chemoradiation, and at the time of radiographic recurrence in patients with glioblastoma (GBM). METHODS: The IMRT dose distribution, location of the center of mass, sphericity, and solidity of the contrast enhancing tumor at baseline and the time of tumor recurrence was quantified in 48 IDH wild-type GBM who underwent postoperative IMRT (2 Gy daily for total of 60 Gy) with concomitant and adjuvant temozolomide. RESULTS: Average radiation dose within enhancing tumor at baseline and recurrence was ≥ 60 Gy. Centroid location of the enhancing tumor shifted an average of 11.3 mm at the time of recurrence with respect to pre-IMRT location. A positive correlation was observed between change in centroid location and PFS in MGMT methylated patients (P = 0.0007) and Cox multivariate regression confirmed centroid distance from baseline was associated with PFS when accounting for clinical factors (P = 0.0189). Lesion solidity was higher at recurrence compared to baseline (P = 0.0118). Tumors that progressed > 12 weeks after IMRT were significantly more spherical (P = 0.0094). CONCLUSION: Most GBMs recur local within therapeutic IMRT doses; however, tumors with longer PFS occurred further from the original tumor location and were more solid and/or nodular.

Urethral Interfractional Geometric and Dosimetric Variations of Prostate Cancer Patients: A Study Using an Onboard MRI.

Purpose: For a cohort of prostate cancer patients treated on an MR-guided radiotherapy (MRgRT) system, we retrospectively analyzed urethral interfractional geometric and dosimetric variations based on onboard MRIs acquired at different timepoints and evaluated onboard prostatic urethra visualization for urethra-focused online adaptive RT. Methods: Twenty-six prostate cancer patients were prospectively scanned on a 0.35-T MRgRT system using an optimized T2-weighted HASTE sequence at simulation and final fraction. Two radiation oncologists (RO1 and RO2) contoured the urethras on all HASTE images. The simulation and final fraction HASTE images were rigidly registered, and urethral interobserver and interfractional geometric variation was evaluated using the 95th percentile Hausdorff distance (HD95), mean distance to agreement (MDA), center-of-mass shift (COMS), and DICE coefficient. For dosimetric analysis, simulation and final fraction HASTE images were registered to the 3D bSSFP planning MRI and 3D bSSFP final setup MRI, respectively. Both ROs' urethra contours were transferred from HASTE images for initial treatment plan optimization and final fraction dose estimation separately. Stereotactic body radiotherapy (SBRT) plans, 40 Gy in 5 fractions, were optimized to meet clinical constraints, including urethral V42Gy ≤0.03 cc, on the planning MRI. The initial plan was then forward calculated on the final setup MRI to estimate urethral dose on the final fraction and evaluate urethral dosimetric impact due to anatomy change. Results: The average interobserver HD95, MDA, COMS, and DICE were 2.85 ± 1.34 mm, 1.02 ± 0.36 mm, 3.16 ± 1.61 mm, and 0.58 ± 0.15, respectively. The average interfractional HD95, MDA, COMS, and DICE were 3.26 ± 1.54 mm, 1.29 ± 0.54 mm, 3.34 ± 2.01 mm, and 0.49 ± 0.18, respectively. All patient simulation MRgRT plans met all clinical constraints. For RO1 and RO2, 23/26 (88%) and 21/26 (81%) patients' final fraction estimated urethral dose did not meet the planned constraint. The average urethral V42Gy change was 0.48 ± 0.58 cc. Conclusion: Urethral interfractional motion and anatomic change can result in daily treatment violating urethral constraints. Onboard MRI with good visualization of the prostatic urethra can be a valuable tool to help better protect the urethra through patient setup or online adaptive RT.

Identifying the Best Candidates for Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography as the Primary Staging Approach Among Men with High-risk Prostate Cancer and Negative Conventional Imaging.

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) is an emerging imaging modality with greater sensitivity and specificity over conventional imaging for prostate cancer (PCa) staging. Using data from two prospective trials (NCT03368547 and NCT04050215), we explored predictors of overall upstaging (nodal and metastatic) by PSMA PET/CT among patients with cN0M0 National Comprehensive Cancer Network high-risk PCa on conventional imaging (n = 213). Overall, 21.1%, 8.9%, and 23.9% of patients experienced nodal, metastatic, and overall upstaging, respectively, without histologic confirmation. On multivariable analysis, Gleason grade group (GG) and percent positive core (PPC) on systematic biopsy significantly predict overall upstaging (odds ratio [OR] 2.15, 95% confidence interval [CI] 1.33-3.45; p = 0.002; and OR 1.03, 95% CI 1.01-1.04; p < 0.001). Overall upstaging was significantly more frequent among men with GG 5 disease (33.0% vs. 17.6%; p = 0.0097) and PPC ≥50% (33.0% vs 15.0%; p = 0.0020). We constructed a nomogram that predicts overall upstaging using initial prostate-specific antigen, PPC, GG, and cT stage, with coefficients estimated from a standard logistic regression model (using maximum likelihood estimation). It is internally validated with a tenfold cross-validated area under the receiver operating characteristic curve estimated at 0.74 (95% CI 0.67-0.82). In our cohort, 90% of patients who had a nomogram-estimated risk below the cutoff of 22% for overall upstaging could have been spared PSMA PET/CT as our model correctly predicted no upstaging. In other words, the predictive model only missed 10% of patients who would otherwise have benefitted from PSMA PET/CT. PATIENT SUMMARY: We analyzed predictors of overall upstaging (lymph node or/and metastasis) by prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) from conventional imaging in men with high-risk prostate cancer undergoing initial staging deemed free of disease in the lymph nodes and distant metastasis by conventional imaging techniques. We found that the pathologic grade and disease burden in a prostate biopsy are associated with upstaging. We also developed a tool that predicts the probability of upstaging according to an individual patient's characteristics. Our study may help in defining patient groups who are most likely to benefit from the addition of a PSMA PET/CT scan.

Performance of a Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography-Derived Risk-Stratification Tool for High-risk and Very High-risk Prostate Cancer.

Importance: Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) can detect low-volume, nonlocalized (ie, regional or metastatic) prostate cancer that was occult on conventional imaging. However, the long-term clinical implications of PSMA PET/CT upstaging remain unclear. Objectives: To evaluate the prognostic significance of a nomogram that models an individual's risk of nonlocalized upstaging on PSMA PET/CT and to compare its performance with existing risk-stratification tools. Design, Setting, and Participants: This cohort study included patients diagnosed with high-risk or very high-risk prostate cancer (ie, prostate-specific antigen [PSA] level >20 ng/mL, Gleason score 8-10, and/or clinical stage T3-T4, without evidence of nodal or metastatic disease by conventional workup) from April 1995 to August 2018. This multinational study was conducted at 15 centers. Data were analyzed from December 2020 to March 2021. Exposures: Curative-intent radical prostatectomy (RP), external beam radiotherapy (EBRT), or EBRT plus brachytherapy (BT), with or without androgen deprivation therapy. Main Outcomes and Measures: PSMA upstage probability was calculated from a nomogram using the biopsy Gleason score, percentage positive systematic biopsy cores, clinical T category, and PSA level. Biochemical recurrence (BCR), distant metastasis (DM), prostate cancer-specific mortality (PCSM), and overall survival (OS) were analyzed using Fine-Gray and Cox regressions. Model performance was quantified with the concordance (C) index. Results: Of 5275 patients, the median (IQR) age was 66 (60-72) years; 2883 (55%) were treated with RP, 1669 (32%) with EBRT, and 723 (14%) with EBRT plus BT; median (IQR) PSA level was 10.5 (5.9-23.2) ng/mL; 3987 (76%) had Gleason grade 8 to 10 disease; and 750 (14%) had stage T3 to T4 disease. Median (IQR) follow-up was 5.1 (3.1-7.9) years; 1221 (23%) were followed up for at least 8 years. Overall, 1895 (36%) had BCR, 851 (16%) developed DM, and 242 (5%) died of prostate cancer. PSMA upstage probability was significantly prognostic of all clinical end points, with 8-year C indices of 0.63 (95% CI, 0.61-0.65) for BCR, 0.69 (95% CI, 0.66-0.71) for DM, 0.71 (95% CI, 0.67-0.75) for PCSM, and 0.60 (95% CI, 0.57-0.62) for PCSM (P < .001). The PSMA nomogram outperformed existing risk-stratification tools, except for similar performance to Staging Collaboration for Cancer of the Prostate (STAR-CAP) for PCSM (eg, DM: PSMA, 0.69 [95% CI, 0.66-0.71] vs STAR-CAP, 0.65 [95% CI, 0.62-0.68]; P < .001; Memorial Sloan Kettering Cancer Center nomogram, 0.57 [95% CI, 0.54-0.60]; P < .001; Cancer of the Prostate Risk Assessment groups, 0.53 [95% CI, 0.51-0.56]; P < .001). Results were validated in secondary cohorts from the Surveillance, Epidemiology, and End Results database and the National Cancer Database. Conclusions and Relevance: These findings suggest that PSMA upstage probability is associated with long-term, clinically meaningful end points. Furthermore, PSMA upstaging had superior risk discrimination compared with existing tools. Formerly occult, PSMA PET/CT-detectable nonlocalized disease may be the main driver of outcomes in high-risk patients.

Evaluation of T2-Weighted MRI for Visualization and Sparing of Urethra with MR-Guided Radiation Therapy (MRgRT) On-Board MRI.

PURPOSE: To evaluate urethral contours from two optimized urethral MRI sequences with an MR-guided radiotherapy system (MRgRT). METHODS: Eleven prostate cancer patients were scanned on a MRgRT system using optimized urethral 3D HASTE and 3D TSE. A resident radiation oncologist contoured the prostatic urethra on the patients' planning CT, diagnostic 3T T2w MRI, and both urethral MRIs. An attending radiation oncologist reviewed/edited the resident's contours and additionally contoured the prostatic urethra on the clinical planning MRgRT MRI (bSSFP). For each image, the resident radiation oncologist, attending radiation oncologist, and a senior medical physicist qualitatively scored the prostatic urethra visibility. Using MRgRT 3D HASTE-based contouring workflow as baseline, prostatic urethra contours drawn on CT, diagnostic MRI, clinical bSSFP and 3D TSE were evaluated relative to the contour on 3D HASTE using 95th percentile Hausdorff distance (HD95), mean-distance-to-agreement (MDA), and DICE coefficient. Additionally, prostatic urethra contrast-to-noise-ratios (CNR) were calculated for all images. RESULTS: For two out of three observers, the urethra visibility score for 3D HASTE was significantly higher than CT, and clinical bSSFP, but was not significantly different from diagnostic MRI. The mean HD95/MDA/DICE values were 11.35 ± 3.55 mm/5.77 ± 2.69 mm/0.07 ± 0.08 for CT, 7.62 ± 2.75 mm/3.83 ± 1.47 mm/0.12 ± 0.10 for CT + diagnostic MRI, 5.49 ± 2.32 mm/2.18 ± 1.19 mm/0.35 ± 0.19 for 3D TSE, and 6.34 ± 2.89 mm/2.65 ± 1.31 mm/0.21 ± 0.12 for clinical bSSFP. The CNR for 3D HASTE was significantly higher than CT, diagnostic MRI, and clinical bSSFP, but was not significantly different from 3D TSE. CONCLUSION: The urethra's visibility scores showed optimized urethral MRgRT 3D HASTE was superior to the other tested methodologies. The prostatic urethra contours demonstrated significant variability from different imaging and workflows. Urethra contouring uncertainty introduced by cross-modality registration and sub-optimal imaging contrast may lead to significant treatment degradation when urethral sparing is implemented to minimize genitourinary toxicity.

A Framework for Sharing Radiation Dose Distribution Maps in the Electronic Medical Record for Improving Multidisciplinary Patient Management.

Radiation oncology practices use a suite of dedicated software and hardware that are not common to other medical subspecialties, making radiation treatment history inaccessible to colleagues. A radiation dose distribution map is generated for each patient internally that allows for visualization of the dose given to each anatomic structure volumetrically; however, this crucial information is not shared systematically to multidisciplinary medical, surgery, and radiology colleagues. A framework was developed in which dose distribution volumes are uploaded onto the medical center's picture archiving and communication system (PACS) to rapidly retrieve and review exactly where, when, and to what dose a lesion or structure was treated. The ability to easily visualize radiation therapy information allows radiology clinics to incorporate radiation dose into image interpretation without direct access to radiation oncology planning software and data. Tumor board discussions are simplified by incorporating radiation therapy information collectively in real time, and daily onboard imaging can also be uploaded while a patient is still undergoing radiation therapy. Placing dose distribution information into PACS facilitates central access into the electronic medical record and provides a succinct visual summary of a patient's radiation history for all medical providers. More broadly, the radiation dose map provides greater visibility and facilitates incorporation of a patient's radiation history to improve oncologic decision making and patient outcomes. Keywords: Brain/Brain Stem, CNS, MRI, Neuro-Oncology, Radiation Effects, Radiation Therapy, Radiation Therapy/Oncology, Radiosurgery, Skull Base, Spine, Technology Assessment Supplemental material is available for this article. © RSNA, 2021 See also commentary by Khandelwal and Scarboro in this issue.