Biochemical Relapse-Free Survival in Postprostatectomy Patients Receiving 18F-Fluciclovine-Guided Prostate Bed-Only Radiation: Post Hoc Analysis of a Prospective Randomized Trial.

PURPOSE: Whole-pelvis (WP) radiation therapy (radiation) improved biochemical relapse-free survival (bRFS) compared with prostate bed (PB)-only radiation in the Radiation Therapy Oncology Group 0534, but was performed in an era prior to positron emission tomography (PET) staging. Separately, 18F-fluciclovine PET/CT-guided postprostatectomy radiation improved 3-year bRFS versus radiation guided by conventional imaging alone. We hypothesized that patients who were changed from WP to PB-only radiation after PET would have bRFS that was: (a) no higher than patients initially planned for PB-only radiation; and (b) lower than patients planned for WP radiation without PET guidance. METHODS AND MATERIALS: We conducted a post hoc analysis of a prospective, randomized trial comparing conventional (arm 1) versus PET-guided (arm 2) postprostatectomy radiation. In arm 2, pre-PET treatment field decisions were recorded and post-PET fields were defined per protocol; pathologic node negative (pN0) without pelvic or extrapelvic PET uptake received PB-only radiation. Three-year bRFS was compared in patients planned for WP with change to PB-only radiation (arm 2 [WP:PB]) vs arm 2 patients planned for PB-only with final radiation to PB-only (arm 2 [PB:PB]) and arm 1 pN0 patients treated with WP radiation (arm 1 [WP]) using the Z test and log-rank test. Demographics were compared using the chi-square test, Fisher exact test, or analysis of variance, as appropriate. RESULTS: We identified 10 arm 2 (WP:PB), 31 arm 2 (PB:PB) and 11 arm 1 (WP) patients. Androgen deprivation was used in 50.0% of arm 2 (WP:PB) and 3.2% of arm 2 (PB:PB) patients, P < .01. Median preradiation prostate-specific antigen was higher in arm 2 (WP:PB) vs arm 2 (PB:PB) patients (0.4 vs 0.2 ng/mL, P = .03); however, there were no significant differences in T stage, Gleason score, or margin positivity. Three-year bRFS was 80% in arm 2 (WP:PB) vs 87.4% in arm 2 (PB:PB), P = .47, respectively. Arm 1(WP) patients had significantly worse 3-year (23%) bRFS vs arm 2 (WP:PB), P < .01. CONCLUSIONS: Patients initially planned for WP radiation with field decision change to PB-only radiation after PET showed (1) no significant difference in 3-year bRFS compared with patients initially planned for PB-only radiation; and (2) improved bRFS compared with patients receiving WP radiation without PET guidance. PET-guided volume de-escalation in selected patients may be 1 approach to mitigating toxicity without compromising outcomes.

The Utility of Spectroscopic MRI in Stereotactic Biopsy and Radiotherapy Guidance in Newly Diagnosed Glioblastoma.

Current diagnostic and therapeutic approaches for gliomas have limitations hindering survival outcomes. We propose spectroscopic magnetic resonance imaging as an adjunct to standard MRI to bridge these gaps. Spectroscopic MRI is a volumetric MRI technique capable of identifying tumor infiltration based on its elevated choline (Cho) and decreased N-acetylaspartate (NAA). We present the clinical translatability of spectroscopic imaging with a Cho/NAA ≥ 5x threshold for delineating a biopsy target in a patient diagnosed with non-enhancing glioma. Then, we describe the relationship between the undertreated tumor detected with metabolite imaging and overall survival (OS) from a pilot study of newly diagnosed GBM patients treated with belinostat and chemoradiation. Each cohort (control and belinostat) were split into subgroups using the median difference between pre-radiotherapy Cho/NAA ≥ 2x and the treated T1-weighted contrast-enhanced (T1w-CE) volume. We used the Kaplan-Meier estimator to calculate median OS for each subgroup. The median OS was 14.4 months when the difference between Cho/NAA ≥ 2x and T1w-CE volumes was higher than the median compared with 34.3 months when this difference was lower than the median. The T1w-CE volumes were similar in both subgroups. We find that patients who had lower volumes of undertreated tumors detected via spectroscopy had better survival outcomes.

Implementation of a Novel Chart Rounds Application to Facilitate Peer Review in a Virtual Academic Environment.

Purpose: Peer review in the form of chart rounds is a critical component of quality assurance and safety in radiation therapy treatments. Radiation therapy departments have undergone significant changes that impose challenges to meaningful review, including institutional growth and increasing use of virtual environment. We discuss the implementation of a novel chart rounds (NCR) format and application adapted to modern peer review needs at a single high-volume multisite National Cancer Institute designated cancer center. Methods and Materials: A working group was created to improve upon the prior institutional chart rounds format (standard chart rounds or SCR). Using a novel in-house application and format redesign, an NCR was created and implemented to accomplish stated goals. Data regarding the SCR and NCR system were then extracted for review. Results: SCR consisted of 2- 90-minute weekly sessions held to review plans across all disease sites, review of 49 plans per hour on average. NCR uses 1-hour long sessions divided by disease site, enabling additional time to be spent per patient (11 plans per hour on average) and more robust discussion. The NCR application is able to automate a list of plans requiring peer review from the institutional treatment planning system. The novel application incorporates features that enable efficient and accurate review of plans in the virtual setting across multiple sites. A systematic scoring system is integrated into the application to record feedback. Over 5 months of use of the NCR, 1160 plans have been reviewed with 143 scored as requiring minor changes, 32 requiring major changes and 307 with comments. Major changes triggered treatment replan. Feedback from scoring is incorporated into physician workflow to ensure changes are addressed. Conclusion: The presented NCR format and application enables standardized and highly reliable peer review of radiation therapy plans that is robust across a variety of complex planning scenarios and could be implemented globally.

Total scalp irradiation: A study comparing multiple types of bolus and VMAT optimization techniques.

PURPOSE: To investigate bolus design and VMAT optimization settings for total scalp irradiation. METHODS: Three silicone bolus designs (flat, hat, and custom) from .decimal were evaluated for adherence to five anthropomorphic head phantoms. Flat bolus was cut from a silicone sheet. Generic hat bolus resembles an elongated swim cap while custom bolus is manufactured by injecting silicone into a 3D printed mold. Bolus placement time was recorded. Air gaps between bolus and scalp were quantified on CT images. The dosimetric effect of air gaps on target coverage was evaluated in a treatment planning study where the scalp was planned to 60 Gy in 30 fractions. A noncoplanar VMAT technique based on gEUD penalties was investigated that explored the full range of gEUD alpha values to determine which settings achieve sufficient target coverage while minimizing brain dose. ANOVA and the t-test were used to evaluate statistically significant differences (threshold = 0.05). RESULTS: The flat bolus took 32 ± 5.9 min to construct and place, which was significantly longer (p < 0.001) compared with 0.67 ± 0.2 min for the generic hat bolus or 0.53 ± 0.10 min for the custom bolus. The air gap volumes were 38 ± 9.3 cc, 32 ± 14 cc, and 17 ± 7.0 cc for the flat, hat, and custom boluses, respectively. While the air gap differences between the flat and custom boluses were significant (p = 0.011), there were no significant dosimetric differences in PTV coverage at V57Gy or V60Gy. In the VMAT optimization study, a gEUD alpha of 2 was found to minimize the mean brain dose. CONCLUSIONS: Two challenging aspects of total scalp irradiation were investigated: bolus design and plan optimization. Results from this study show opportunities to shorten bolus fabrication time during simulation and create high quality treatment plans using a straightforward VMAT template with simple optimization settings.

Lesion segmentation on 18F-fluciclovine PET/CT images using deep learning.

Background and purpose: A novel radiotracer, 18F-fluciclovine (anti-3-18F-FACBC), has been demonstrated to be associated with significantly improved survival when it is used in PET/CT imaging to guide postprostatectomy salvage radiotherapy for prostate cancer. We aimed to investigate the feasibility of using a deep learning method to automatically detect and segment lesions on 18F-fluciclovine PET/CT images. Materials and methods: We retrospectively identified 84 patients who are enrolled in Arm B of the Emory Molecular Prostate Imaging for Radiotherapy Enhancement (EMPIRE-1) trial. All 84 patients had prostate adenocarcinoma and underwent prostatectomy and 18F-fluciclovine PET/CT imaging with lesions identified and delineated by physicians. Three different neural networks with increasing levels of complexity (U-net, Cascaded U-net, and a cascaded detection segmentation network) were trained and tested on the 84 patients with a fivefold cross-validation strategy and a hold-out test, using manual contours as the ground truth. We also investigated using both PET and CT or using PET only as input to the neural network. Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), center-of-mass distance (CMD), and volume difference (VD) were used to quantify the quality of segmentation results against ground truth contours provided by physicians. Results: All three deep learning methods were able to detect 144/155 lesions and 153/155 lesions successfully when PET+CT and PET only, respectively, served as input. Quantitative results demonstrated that the neural network with the best performance was able to segment lesions with an average DSC of 0.68 ± 0.15 and HD95 of 4 ± 2 mm. The center of mass of the segmented contours deviated from physician contours by approximately 2 mm on average, and the volume difference was less than 1 cc. The novel network proposed by us achieves the best performance compared to current networks. The addition of CT as input to the neural network contributed to more cases of failure (DSC = 0), and among those cases of DSC > 0, it was shown to produce no statistically significant difference with the use of only PET as input for our proposed method. Conclusion: Quantitative results demonstrated the feasibility of the deep learning methods in automatically segmenting lesions on 18F-fluciclovine PET/CT images. This indicates the great potential of 18F-fluciclovine PET/CT combined with deep learning for providing a second check in identifying lesions as well as saving time and effort for physicians in contouring.