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.

Cardiac motion and its dosimetric impact during radioablation for refractory ventricular tachycardia.

INTRODUCTION: Cardiac radioablation (CR) is a noninvasive treatment option for patients with refractory ventricular tachycardia (VT) during which high doses of radiation, typically 25 Gy, are delivered to myocardial scar. In this study, we investigate motion from cardiac cycle and evaluate the dosimetric impact in a cohort of patients treated with CR. METHODS: This retrospective study included eight patients treated at our institution who had respiratory-correlated and ECG-gated 4DCT scans acquired within 2 weeks of CR. Deformable image registration was applied between maximum systole (SYS) and diastole (DIAS) CTs to assess cardiac motion. The average respiratory-correlated CT (AVGresp ) was deformably registered to the average cardiac (AVGcardiac ), SYS, and DIAS CTs, and contours were propagated using the deformation vector fields (DVFs). Finally, the original treatment plan was recalculated on the deformed AVGresp CT for dosimetric assessment. RESULTS: Motion magnitudes were measured as the mean (SD) value over the DVFs within each structure. Displacement during the cardiac cycle for all chambers was 1.4 (0.9) mm medially/laterally (ML), 1.6 (1.0) mm anteriorly/posteriorly (AP), and 3.0 (2.8) mm superiorly/inferiorly (SI). Displacement for the 12 distinct clinical target volumes (CTVs) was 1.7 (1.5) mm ML, 2.4 (1.1) mm AP, and 2.1 (1.5) SI. Displacements between the AVGresp and AVGcardiac scans were 4.2 (2.0) mm SI and 5.8 (1.4) mm total. Dose recalculations showed that cardiac motion may impact dosimetry, with dose to 95% of the CTV dropping from 27.0 (1.3) Gy on the AVGresp to 20.5 (7.1) Gy as estimated on the AVGcardiac . CONCLUSIONS: Cardiac CTV motion in this patient cohort is on average below 3 mm, location-dependent, and when not accounted for in treatment planning may impact target coverage. Further study is needed to assess the impact of cardiac motion on clinical outcomes.

18F-fluciclovine-PET/CT imaging versus conventional imaging alone to guide postprostatectomy salvage radiotherapy for prostate cancer (EMPIRE-1): a single centre, open-label, phase 2/3 randomised controlled trial.

BACKGROUND: Molecular imaging is increasingly used to guide treatment decisions and planning in prostate cancer. We aimed to evaluate the role of 18F-fluciclovine-PET/CT in improving cancer control compared with conventional imaging (bone scan and either CT or MRI) alone for salvage postprostatectomy radiotherapy. METHODS: In EMPIRE-1, a single-centre, open-label, phase 2/3 randomised controlled trial, patients with prostate cancer with detectable PSA after prostatectomy and negative conventional imaging (no extrapelvic or bone findings) were randomly assigned in a 1:1 ratio to radiotherapy directed by conventional imaging alone or to conventional imaging plus 18F-fluciclovine-PET/CT. Computer-generated randomisation was stratified by PSA concentration, adverse pathology indicators, and androgen deprivation therapy intent. In the 18F-fluciclovine-PET/CT group, radiotherapy decisions were rigidly determined by PET findings, which were also used for target delineation. The primary endpoint was 3 year event-free survival, with events defined as biochemical or clinical recurrence or progression, or initiation of systemic therapy, using univariate and multivariable analyses in patients who received radiotherapy. This trial is registered with ClinicalTrials.gov, NCT01666808 and is closed to new participants. FINDINGS: From Sept 18, 2012, to March 4, 2019, 165 patients were randomly assigned, with median follow-up of 3·52 years (95% CI 2·98-3·95). PET findings resulted in four patients in the 18F-fluciclovine-PET/CT group having radiotherapy aborted; these patients were excluded from survival analyses. Median survival was not reached (95% CI 35·2-not reached; 33% of 81 patients had events) in the conventional imaging group compared with not reached (95% CI not reached-not reached; 20% of 76 patients) in the 18F-fluciclovine-PET/CT group, and 3 year event-free survival was 63·0% (95% CI 49·2-74·0) in the conventional imaging group versus 75·5% (95% CI 62·5-84·6) for 18F-fluciclovine-PET/CT (difference 12·5; 95% CI 4·3-20·8; p=0·0028). In adjusted analyses, study group (hazard ratio 2·04 [95% CI 1·06-3·93], p=0·0327) was significantly associated with event-free survival. Toxicity was similar in both study groups, with the most common adverse events being late urinary frequency or urgency (37 [46%] of 81 patients in the conventional imaging group and 31 [41%] of 76 in the PET group), and acute diarrhoea (11 [14%] in the conventional imaging group and 16 [21%] in the PET group). INTERPRETATION: Inclusion of 18F-fluciclovine-PET into postprostatectomy radiotherapy decision making and planning significantly improved survival free from biochemical recurrence or persistence. Integration of novel PET radiotracers into radiotherapy decisions and planning for prostate cancer patients warrants further study. FUNDING: National Institutes of Health/National Cancer Institute, Blue Earth Diagnostics, and Winship Cancer Institute of Emory University.

The Contribution of Thoracic Radiation Dose Volumes to Subsequent Development of Cardiovascular Disease in Cancer Survivors.

BACKGROUND: Although radiation therapy (RT) has been recognized for contributing to cardiovascular disease (CVD), it is unknown whether specific doses received by cardiovascular tissues influence development. OBJECTIVE: In this pilot study, we examined the contribution of RT dose distribution on the development of CVD events in patients with cancer within 5 years of RT. METHODS: A retrospective case-controlled design was used matching 28 cases receiving thoracic RT who subsequently developed an adverse CVD event with 28 controls based upon age, gender, and cancer type. Dose volume histograms of nongated computed tomography scans received during RT characterized the dose delivered to the heart. Heart chambers were segmented using an atlas approach, and radiomics features for the segmentation as well as planning dose in each chamber were tabulated for analysis. RESULT: No significant differences were observed in the RT dose statistics between groups, preexisting CVD, nor significant differences of RT doses delivered to distinct chambers of the heart. Cases were found to have greater CVD risk factors at the time of cancer diagnosis. Morphological significant differences for perimeter on border ( P = .043), equivalent spherical radius ( P = .050), and elongation ( P = .038) were observed, with preexisting CVD having the highest values (ie, larger hearts). CONCLUSION: Traditional CVD risk factors were more prevalent in the cases who developed CVD. No differences were observed in doses of RT. Of note, we observed significant differences in heart morphology and mass in known diseased hearts on the pretreatment scans. These new metrics may have implications for the measurement and quantification of CVD.

Onboard cone-beam CT-based replan evaluation for head and neck proton therapy.

PURPOSE: Quality assurance computed tomography (QACT) is the current clinical practice in proton therapy to evaluate the needs for replan. QACT could falsely indicate replan because of setup issues that would be solved on the treatment machine. Deforming the treatment planning CT (TPCT) to the pretreatment CBCT may eliminate this issue. We investigated the performance of replan evaluation based on deformed TPCT (TPCTdir) for proton head and neck (H&N) therapy. METHODS AND MATERIALS: Twenty-eight H&N datasets along with pretreatment CBCT and QACT were used to validate the method. The changes in body volume were analyzed between the no-replan and replan groups. The dose on the TPCTdir, the deformed QACT (QACTdir), and the QACT were calculated by applying the clinical plans to these image sets. Dosimetric parameters' changes, including ΔD95, ΔDmean, and ΔD1 for the clinical target volumes (CTVs) were calculated. Receiver operating characteristic curves for replan evaluation based on ΔD95 on QACT and TPCTdir were calculated, using ΔD95 on QACTdir as the reference. A threshold for replan based on ΔD95 on TPCTdir is proposed. The specificities for the proposed method were calculated. RESULTS: The changes in the body contour were 95.8 ± 83.8 cc versus 305.0 ± 235.0 cc (p < 0.01) for the no-replan and replan groups, respectively. The ΔD95, ΔDmean, and ΔD1 are all comparable for all the evaluations. The differences between TPCTdir and QACTdir evaluations were 0.30% ± 0.86%, 0.00 ± 0.22 Gy, and -0.17 ± 0.61 Gy for CTV ΔD95, ΔDmean, and ΔD1, respectively. The corresponding differences between the QACT and QACTdir were 0.12% ± 1.1%, 0.02 ± 0.32 Gy, and -0.01 ± 0.71 Gy. CTV ΔD95 > 2.6% in TPCTdir was chosen as the threshold to trigger QACT/replan. The corresponding specificity was 94% and 98% for the clinical practice and the proposed method, respectively. CONCLUSIONS: The replan evaluation based on TPCTdir provides better specificity than that based on the QACT.

3D whole-brain metabolite imaging to improve characterization of low-to-intermediate grade gliomas.

PURPOSE: MRI is the standard imaging modality used for diagnosis, treatment planning, and post-treatment management of gliomas. Contrast-enhanced T1-weighted (CE-T1w) MRI is used to plan biopsy and radiation for grade IV gliomas but is less effective for grade II and III gliomas (i.e., low-to-intermediate grade gliomas) which may have minimal or no enhancement. Magnetic resonance spectroscopic imaging (MRSI) is an advanced MRI technique that has been shown, to improve diagnostic yield of biopsy and target delineation for grade IV glioma. The purpose of this study is to determine if MRSI can improve characterization and tissue sampling of low-to-intermediate grade gliomas. METHODS: Prospective grade II and grade III glioma patients were enrolled to undergo whole brain high-resolution MRSI prior to tissue sampling. Choline/N-acetyl-aspartate (Cho/NAA) maps were overlaid on anatomic imaging and imported into stereotactic biopsy software. Patients were treated with standard-of-care surgery and radiation. Volumes of spectroscopically abnormal tissue were generated and compared with anatomic imaging and areas of enhancing recurrence on follow-up imaging. RESULTS: Ten patients had pathologic diagnosis of grade II (n = 4) or grade III (n = 6) with a median follow-up of 27.3 months. Five patients had recurrence, and regions of recurrence were found to overlap with metabolically abnormal regions on MRSI at the time of diagnosis. CONCLUSION: MRSI in low-to-intermediate grade glioma patients is predictive of areas of subsequent recurrence. Larger studies are needed to determine if MRSI can be used to guide surgical and radiation treatment planning in these patients.

A convolutional neural network to filter artifacts in spectroscopic MRI.

PURPOSE: Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tissue metabolism without the need for ionizing radiation or injected contrast agent. Magnetic resonance spectroscopic imaging has been shown to be a viable imaging modality for studying several neuropathologies. However, a key hurdle in the routine clinical adoption of MRSI is the presence of spectral artifacts that can arise from a number of sources, possibly leading to false information. METHODS: A deep learning model was developed that was capable of identifying and filtering out poor quality spectra. The core of the model used a tiled convolutional neural network that analyzed frequency-domain spectra to detect artifacts. RESULTS: When compared with a panel of MRS experts, our convolutional neural network achieved high sensitivity and specificity with an area under the curve of 0.95. A visualization scheme was implemented to better understand how the convolutional neural network made its judgement on single-voxel or multivoxel MRSI, and the convolutional neural network was embedded into a pipeline capable of producing whole-brain spectroscopic MRI volumes in real time. CONCLUSION: The fully automated method for assessment of spectral quality provides a valuable tool to support clinical MRSI or spectroscopic MRI studies for use in fields such as adaptive radiation therapy planning.

Automated Verification of IGRT-based Patient Positioning.

A system for automated quality assurance in radiotherapy of a therapist's registration was designed and tested in clinical practice. The approach compliments the clinical software's automated registration in terms of algorithm configuration and performance, and constitutes a practical approach for ensuring safe patient setups. Per our convergence analysis, evolutionary algorithms perform better in finding the global optima of the cost function with discrepancies from a deterministic optimizer seen sporadically.

Automated population-based planning for whole brain radiation therapy.

Treatment planning for whole-brain radiation treatment is technically a simple process, but in practice it takes valuable clinical time of repetitive and tedious tasks. This report presents a method that automatically segments the relevant target and normal tissues, and creates a treatment plan in only a few minutes after patient simulation. Segmentation of target and critical structures is performed automatically through morphological operations on the soft tissue and was validated by comparing with manual clinical segmentation using the Dice coefficient and Hausdorff distance. The treatment plan is generated by searching a database of previous cases for patients with similar anatomy. In this search, each database case is ranked in terms of similarity using a customized metric designed for sensitivity by including only geometrical changes that affect the dose distribution. The database case with the best match is automatically modified to replace relevant patient info and isocenter position while maintaining original beam and MLC settings. Fifteen patients with marginally acceptable treatment plans were used to validate the method. In each of these cases the anatomy was accurately segmented, but the beams and MLC settings led to a suboptimal treatment plan by either underdosing the brain or excessively irradiating critical normal tissues. For each case, the anatomy was automatically segmented with the proposed method, and the automated and anual segmentations were then compared. The mean Dice coefficient was 0.97, with a standard deviation of 0.008 for the brain, 0.85 ± 0.009 for the eyes, and 0.67 ± 0.11 for the lens. The mean Euclidian distance was 0.13 ± 0.13 mm for the brain, 0.27± 0.31 for the eye, and 2.34 ± 7.23 for the lens. Each case was then subsequently matched against a database of 70 validated treatment plans and the best matching plan (termed autoplanned), was compared retrospectively with the clinical plans in terms of brain coverage and maximum doses to critical structures. Maximum doses were reduced by a maximum of 8.37 Gy for the left eye (mean 2.08), 11.67 for the right eye (1.90) and, respectively, 25.44 (5.59) for the left lens and 24.40 (4.85) for the right lens. Time to generate the autoplan, including the segmentation, was 3-4min. Automated database- based matching is an alternative to classical treatment planning that improves quality while providing a cost-effective solution to planning through modifying previous validated plans to match a current patient's anatomy.

Quantitative dosimetry for yttrium-90 radionuclide therapy: tumor dose predicts fluorodeoxyglucose positron emission tomography response in hepatic metastatic melanoma.

PURPOSE: To assess a new method for generating patient-specific volumetric dose calculations and analyze the relationship between tumor dose and positron emission tomography (PET) response after radioembolization of hepatic melanoma metastases. METHODS AND MATERIALS: Yttrium-90 ((90)Y) bremsstrahlung single photon emission computed tomography (SPECT)/computed tomography (CT) acquired after (90)Y radioembolization was convolved with published (90)Y Monte Carlo estimated dose deposition kernels to create a three-dimensional dose distribution. Dose-volume histograms were calculated for tumor volumes manually defined from magnetic resonance imaging or PET/CT imaging. Tumor response was assessed by absolute reduction in maximum standardized uptake value (SUV(max)) and total lesion glycolysis (TLG). RESULTS: Seven patients with 30 tumors treated with (90)Y for hepatic metastatic melanoma with available (90)Y SPECT/CT and PET/CT before and after treatment were identified for analysis. The median (range) for minimum, mean, and maximum dose per tumor volume was 16.9 Gy (5.7-43.5 Gy), 28.6 Gy (13.8-65.6 Gy) and 36.6 Gy (20-124 Gy), respectively. Response was assessed by fluorodeoxyglucose PET/CT at a median time after treatment of 2.8 months (range, 1.2-7.9 months). Mean tumor dose (P = .03) and the percentage of tumor volume receiving ≥ 50 Gy (P < .01) significantly predicted for decrease in tumor SUV(max), whereas maximum tumor dose predicted for decrease in tumor TLG (P < .01). CONCLUSIONS: Volumetric dose calculations showed a statistically significant association with metabolic tumor response. The significant dose-response relationship points to the clinical utility of patient-specific absorbed dose calculations for radionuclide therapy.

Prior-knowledge treatment planning for volumetric arc therapy using feature-based database mining.

Treatment planning for volumetric arc therapy (VMAT) is a lengthy process that requires many rounds of optimizations to obtain the best treatment settings and optimization constraints for a given patient's geometry. We propose a feature-selection search engine that explores previously treated cases of similar anatomy, returning the optimal plan configurations and attainable DVH constraints. Using an institutional database of 83 previously treated cases of prostate carcinoma treated with volumetric-modulated arc therapy, the search procedure first finds the optimal isocenter position with an optimization procedure, then ranks the anatomical similarity as the mean distance between targets. For the best matching plan, the planning information is reformatted to the DICOM format and imported into the treatment planning system to suggest isocenter, arc directions, MLC patterns, and optimization constraints that can be used as starting points in the optimization process. The approach was tested to create prospective treatment plans based on anatomical features that match previously treated cases from the institution database. By starting from a near-optimal solution and using previous optimization constraints, the best matching test only required simple optimization steps to further decrease target inhomogeneity, ultimately reducing time spend by the therapist in planning arcs' directions and lengths.

Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search.

Segmentation of organs at risk (OARs) remains one of the most time-consuming tasks in radiotherapy treatment planning. Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large interpatient variations are present. We show that significant changes are needed to autosegment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple presegmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts. These segmentations are compacted in a probabilistic map of organ shape using the STAPLE algorithm. Final segmentation is obtained by adjusting the probability map for each organ type, using customized combinations of delineation filters exploiting prior knowledge of organ characteristics. Validation is performed by comparing automated and manual segmentation using the Dice coefficient, measured at an average of 0.971 for the aorta, 0.869 for the trachea, 0.958 for the lungs, 0.788 for the heart, 0.912 for the liver, 0.884 for the kidneys, 0.888 for the vertebrae, 0.863 for the spleen, and 0.740 for the spinal cord. Accurate atlas segmentation for abdominal and thoracic regions can be achieved with the usage of a multi-atlas and perstructure refinement strategy. To improve clinical workflow and efficiency, the algorithm was embedded in a software service, applying the algorithm automatically on acquired scans without any user interaction.

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.

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.

Lung SBRT treatment planning: a study of VMAT arc selection guided by collision check software.

To evaluate the effects of arc geometry on lung stereotactic body radiation therapy (SBRT) plan quality, using collision check software to select safe beam angles. Thirty lung SBRT cases were replanned 10Gy x 5 using 4 volumetric modulated arc therapy (VMAT) geometries: coplanar lateral (cpLAT), coplanar oblique (cpOBL), noncoplanar lateral (ncpLAT) and noncoplanar oblique (ncpOBL). Lateral arcs spanned 180° on the affected side whereas the 180° oblique arcs crossed midline to spare healthy tissues. Couch angles were separated by 30° on noncoplanar plans. Clearance was verified with Radformation CollisionCheck software. Optimization objectives were the same across the four plans for each case. Planning target volume (PTV) coverage was set to 95% and then plans were evaluated for dose conformity, healthy tissue doses, and monitor units. Clinically treated plans were used to benchmark the results. The volumes of the 25%, 50% and 75% isodoses were smaller with noncoplanar than coplanar arcs. The volume of the 50% isodose line relative to the PTV (CI50%) was as follows: clinical 3.75±0.72, cpLAT 3.39 ± 0.37, cpOBL 3.36 ± 0.34, ncpLAT 3.02 ± 0.21 and ncpOBL 3.02 ± 0.22. The Wilcoxon signed rank test with Bonferroni correction showed p < 0.005 in all CI50% comparisons except between the cpLat and cpObl arcs and between the ncpLat and ncpObl arcs. The best lung sparing was achieved using ncpObl arcs, which was statistically significant (p < 0.001) compared with the other four plans at V12.5Gy, V13.5Gy and V20Gy. Chest wall V30Gy was significantly better using noncoplanar arcs in comparison to the other plan types (p < 0.001). The best heart sparing at V10Gy from the ncpOBL arcs was significant compared with the clinical and cpLat plans (p < 0.005). Arc geometry has a substantial effect on lung SBRT plan quality. Noncoplanar arcs were superior to coplanar arcs at compacting the dose distribution at the 25%, 50% and 75% isodose levels, thereby reducing the dose to healthy tissues. Further healthy tissue sparing was achieved using oblique arcs that minimize the pathlength through healthy tissues and avoid organs at risk. The dosimetric advantages of the noncoplanar and oblique arcs require careful beam angle selection during treatment planning to avoid collisions during treatment, which may be facilitated by commercial software.

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.

Applying a Radiation Therapy Volume Analysis Pipeline to Determine the Utility of Spectroscopic MRI-Guided Adaptive Radiation Therapy for Glioblastoma.

Accurate radiation therapy (RT) targeting is crucial for glioblastoma treatment but may be challenging using clinical imaging alone due to the infiltrative nature of glioblastomas. Precise targeting by whole-brain spectroscopic MRI, which maps tumor metabolites including choline (Cho) and N-acetylaspartate (NAA), can quantify early treatment-induced molecular changes that other traditional modalities cannot measure. We developed a pipeline to determine how spectroscopic MRI changes during early RT are associated with patient outcomes to provide insight into the utility of adaptive RT planning. Data were obtained from a study (NCT03137888) where glioblastoma patients received high-dose RT guided by the pre-RT Cho/NAA twice normal (Cho/NAA ≥ 2x) volume, and received spectroscopic MRI scans pre- and mid-RT. Overlap statistics between pre- and mid-RT scans were used to quantify metabolic activity changes after two weeks of RT. Log-rank tests were used to quantify the relationship between imaging metrics and patient overall and progression-free survival (OS/PFS). Patients with lower Jaccard/Dice coefficients had longer PFS (p = 0.045 for both), and patients with lower Jaccard/Dice coefficients had higher OS trending towards significance (p = 0.060 for both). Cho/NAA ≥ 2x volumes changed significantly during early RT, putting healthy tissue at risk of irradiation, and warranting further study into using adaptive RT planning.

A Novel Approach to Determining Tumor Progression Using a Three-Site Pilot Clinical Trial of Spectroscopic MRI-Guided Radiation Dose Escalation in Glioblastoma.

Glioblastoma (GBM) is a fatal disease, with poor prognosis exacerbated by difficulty in assessing tumor extent with imaging. Spectroscopic MRI (sMRI) is a non-contrast imaging technique measuring endogenous metabolite levels of the brain that can serve as biomarkers for tumor extension. We completed a three-site study to assess survival benefits of GBM patients when treated with escalated radiation dose guided by metabolic abnormalities in sMRI. Escalated radiation led to complex post-treatment imaging, requiring unique approaches to discern tumor progression from radiation-related treatment effect through our quantitative imaging platform. The purpose of this study is to determine true tumor recurrence timepoints for patients in our dose-escalation multisite study using novel methodology and to report on median progression-free survival (PFS). Follow-up imaging for all 30 trial patients were collected, lesion volumes segmented and graphed, and imaging uploaded to our platform for visual interpretation. Eighteen months post-enrollment, the median PFS was 16.6 months with a median time to follow-up of 20.3 months. With this new treatment paradigm, incidence rate of tumor recurrence one year from treatment is 30% compared to 60-70% failure under standard care. Based on the delayed tumor progression and improved survival, a randomized phase II trial is under development (EAF211).

Towards automated planning for unsealed source therapy.

The purpose of this study was to develop and validate a technique for unsealed source radiotherapy planning that combines the segmentation and registration tasks of single-photon emission tomography (SPECT) and computed tomography (CT) datasets. The segmentation task is automated by an atlas registration approach that takes advantage of a hybrid scheme using a diffeomorphic demons algorithm to warp a standard template to the patient's CT. To overcome the lack of common anatomical features between the CT and SPECT datasets, registration is achieved through a narrow band approach that matches liver contours in the CT with the gradients of the SPECT dataset. Deposited dose is then computed from the SPECT dataset using a convolution operation with tracer-specific deposition kernels. Automatic segmentation showed good agreement with manual contouring, measured using the dice similarity coefficient and ranging from 0.72 to 0.87 for the liver, 0.47 to 0.93 for the kidneys, and 0.74 to 0.83 for the spinal cord. The narrow band registration achieved variations of less 0.5 mm translation and 1° rotation, as measured with convergence analysis. With the proposed combined segmentation-registration technique, the uncertainty of soft-tissue target localization is greatly reduced, ensuring accurate therapy planning.

A measure to evaluate deformable registration fields in clinical settings.

Deformable registration has migrated from a research topic to a widely used clinical tool that can improve radiotherapeutic treatment accuracy by tracking anatomical changes. Although various mathematical formulations have been reported in the literature and implemented in commercial software, we lack a straightforward method to verify a given solution in routine clinical use. We propose a metric using concepts derived from vector analysis that complements the standard evaluation tools to identify unrealistic wrappings in a displacement field. At the heart of the proposed procedure is identification of vortexes in the displacement field that do not correspond to underlying anatomical changes. Vortexes are detected and their intensity quantified using the CURL operator and presented as a vortex map overlaid on the original anatomy for rapid identification of problematic regions. We show application of the proposed metric on clinical scenarios of adaptive radiotherapy and treatment response assessment, where the CURL operator quantitatively detected errors in the displacement field and identified problematic regions that were invisible to classical voxel-based evaluation methods. Unrealistic warping not visible to standard voxel-based solution assessment can produce erroneous results when the deformable solution is applied on a secondary dataset, such as dose matrix in adaptive therapy or PET data for treatment response assessment. The proposed metric for evaluating deformable registration provides increased usability and accuracy of detecting unrealistic deformable registration solutions when compared to standard intensity-based approaches. It is computationally efficient and provides a valuable platform for the clinical acceptance of image-guided radiotherapy.