Where Does Auto-Segmentation for Brain Metastases Radiosurgery Stand Today?

Detection and segmentation of brain metastases (BMs) play a pivotal role in diagnosis, treatment planning, and follow-up evaluations for effective BM management. Given the rising prevalence of BM cases and its predominantly multiple onsets, automated segmentation is becoming necessary in stereotactic radiosurgery. It not only alleviates the clinician's manual workload and improves clinical workflow efficiency but also ensures treatment safety, ultimately improving patient care. Recent strides in machine learning, particularly in deep learning (DL), have revolutionized medical image segmentation, achieving state-of-the-art results. This review aims to analyze auto-segmentation strategies, characterize the utilized data, and assess the performance of cutting-edge BM segmentation methodologies. Additionally, we delve into the challenges confronting BM segmentation and share insights gleaned from our algorithmic and clinical implementation experiences.

Single-Fraction Versus Fractionated Preoperative Radiosurgery for Resected Brain Metastases: A PROPS-BM International Multicenter Cohort Study.

PURPOSE: Preoperative stereotactic radiosurgery (SRS) is a feasible alternative to postoperative SRS for resected brain metastases (BM). Most reported studies of preoperative SRS used single-fraction SRS (SF-SRS). The goal of this study was to compare outcomes and toxicity of preoperative SF-SRS with multifraction (3-5 fractions) SRS (MF-SRS) in a large international multicenter cohort (Preoperative Radiosurgery for Brain Metastases-PROPS-BM). METHODS AND MATERIALS: Patients with BM from solid cancers, of which at least 1 lesion was treated with preoperative SRS followed by planned resection, were included from 8 institutions. SRS to synchronous intact BM was allowed. Exclusion criteria included prior or planned whole brain radiation therapy. Intracranial outcomes were estimated using cumulative incidence with competing risk of death. Propensity score matched (PSM) analyses were performed. RESULTS: The study cohort included 404 patients with 416 resected index lesions, of which SF-SRS and MF-SRS were used for 317 (78.5%) and 87 patients (21.5%), respectively. Median dose was 15 Gy in 1 fraction for SF-SRS and 24 Gy in 3 fractions for MF-SRS. Univariable analysis demonstrated that SF-SRS was associated with higher cavity local recurrence (LR) compared with MF-SRS (2-year: 16.3% vs 2.9%; P = .004), which was also demonstrated in multivariable analysis. PSM yielded 81 matched pairs (n = 162). PSM analysis also demonstrated significantly higher rate of cavity LR with SF-SRS (2-year: 19.8% vs 3.3%; P = .003). There was no difference in adverse radiation effect, meningeal disease, or overall survival between cohorts in either analysis. CONCLUSIONS: Preoperative MF-SRS was associated with significantly reduced risk of cavity LR in both the unmatched and PSM analyses. There was no difference in adverse radiation effect, meningeal disease, or overall survival based on fractionation. MF-SRS may be a preferred option for neoadjuvant radiation therapy of resected BMs. Additional confirmatory studies are needed. A phase 3 randomized trial of single-fraction preoperative versus postoperative SRS (NRG-BN012) is ongoing (NCT05438212).

BIOGUIDE-X: A First-in-Human Study of the Performance of Positron Emission Tomography-Guided Radiation Therapy.

PURPOSE: Positron emission tomography (PET)-guided radiation therapy is a novel tracked dose delivery modality that uses real-time PET to guide radiation therapy beamlets. The BIOGUIDE-X study was performed with sequential cohorts of participants to (1) identify the fluorodeoxyglucose (FDG) dose for PET-guided therapy and (2) confirm that the emulated dose distribution was consistent with a physician-approved radiation therapy plan. METHODS AND MATERIALS: This prospective study included participants with at least 1 FDG-avid targetable primary or metastatic tumor (2-5 cm) in the lung or bone. For cohort I, a modified 3 + 3 design was used to determine the FDG dose that would result in adequate signal for PET-guided therapy. For cohort II, PET imaging data were collected on the X1 system before the first and last fractions among patients undergoing conventional stereotactic body radiation therapy. PET-guided therapy dose distributions were modeled on the patient's computed tomography anatomy using the collected PET data at each fraction as input to an "emulated delivery" and compared with the physician-approved plan. RESULTS: Cohort I demonstrated adequate FDG activity in 6 of 6 evaluable participants (100.0%) with the first injected dose level of 15 mCi FDG. In cohort II, 4 patients with lung tumors and 5 with bone tumors were enrolled, and evaluable emulated delivery data points were collected for 17 treatment fractions. Sixteen of the 17 emulated deliveries resulted in dose distributions that were accurate with respect to the approved PET-guided therapy plan. The 17th data point was just below the 95% threshold for accuracy (dose-volume histogram score = 94.6%). All emulated fluences were physically deliverable. No toxicities were attributed to multiple FDG administrations. CONCLUSIONS: PET-guided therapy is a novel radiation therapy modality in which a radiolabeled tumor can act as its own fiducial for radiation therapy targeting. Emulated therapy dose distributions calculated from continuously acquired real-time PET data were accurate and machine-deliverable in tumors that were 2 to 5 cm in size with adequate FDG signal characteristics.

Modeling gamma knife radiosurgical toxicity for multiple brain metastases.

BACKGROUND AND PURPOSE: Radiation oncology protocols for single fraction radiosurgery recommend setting dosing criteria based on assumed risk of radionecrosis, which can be predicted by the 12 Gy normal brain volume (V12). In this study, we show that tumor surface area (SA) and a simple power-law model using only preplan variables can estimate and minimize radiosurgical toxicity. MATERIALS AND METHODS: A 245-patient cohort with 1217 brain metastases treated with single or distributed Gamma Knife sessions was reviewed retrospectively. Univariate and multivariable linear regression models and power-law models determined which modeling parameters best predicted V12. The V12 power-law model, represented by a product of normalized Rx dose Rxn, and tumor longest axial dimension LAD (V12 âˆ¼ Rxn1.5*LAD2), was independently validated using a secondary 63-patient cohort with 302 brain metastases. RESULTS: Surface area was the best univariate linear predictor of V12 (adjR2 = 0.770), followed by longest axial dimension (adjR2 = 0.755) and volume (adjR2 = 0.745). The power-law model accounted for 90% variance in V12 for 1217 metastatic lesions (adjR2 = 0.906) and 245 patients (adjR2 = 0.896). The average difference ΔV12 between predicted and measured V12s was (0.28 ± 0.55) cm3 per lesion and (1.0 ± 1.2) cm3 per patient. The power-law predictive capability was validated using a secondary 63-patient dataset (adjR2 = 0.867) with 302 brain metastases (adjR2 = 0.825). CONCLUSION: Surface area was the most accurate univariate predictor of V12 for metastatic lesions. We developed a preplan model for brain metastases that can help better estimate radionecrosis risk, determine prescription doses given a target V12, and provide safe dose escalation strategies without the use of any planning software.

Risk Factors for Progression and Toxic Effects After Preoperative Stereotactic Radiosurgery for Patients With Resected Brain Metastases.

Importance: Preoperative stereotactic radiosurgery (SRS) has been demonstrated as a feasible alternative to postoperative SRS for resectable brain metastases (BMs) with potential benefits in adverse radiation effects (AREs) and meningeal disease (MD). However, mature large-cohort multicenter data are lacking. Objective: To evaluate preoperative SRS outcomes and prognostic factors from a large international multicenter cohort (Preoperative Radiosurgery for Brain Metastases-PROPS-BM). Design, Setting, and Participants: This multicenter cohort study included patients with BMs from solid cancers, of which at least 1 lesion received preoperative SRS and a planned resection, from 8 institutions. Radiosurgery to synchronous intact BMs was allowed. Exclusion criteria included prior or planned whole-brain radiotherapy and no cranial imaging follow-up. Patients were treated between 2005 and 2021, with most treated between 2017 and 2021. Exposures: Preoperative SRS to a median dose to 15 Gy in 1 fraction or 24 Gy in 3 fractions delivered at a median (IQR) of 2 (1-4) days before resection. Main Outcomes and Measures: The primary end points were cavity local recurrence (LR), MD, ARE, overall survival (OS), and multivariable analysis of prognostic factors associated with these outcomes. Results: The study cohort included 404 patients (214 women [53%]; median [IQR] age, 60.6 [54.0-69.6] years) with 416 resected index lesions. The 2-year cavity LR rate was 13.7%. Systemic disease status, extent of resection, SRS fractionation, type of surgery (piecemeal vs en bloc), and primary tumor type were associated with cavity LR risk. The 2-year MD rate was 5.8%, with extent of resection, primary tumor type, and posterior fossa location being associated with MD risk. The 2-year any-grade ARE rate was 7.4%, with target margin expansion greater than 1 mm and melanoma primary being associated with ARE risk. Median OS was 17.2 months (95% CI, 14.1-21.3 months), with systemic disease status, extent of resection, and primary tumor type being the strongest prognostic factors associated with OS. Conclusions and Relevance: In this cohort study, the rates of cavity LR, ARE, and MD after preoperative SRS were found to be notably low. Several tumor and treatment factors were identified that are associated with risk of cavity LR, ARE, MD, and OS after treatment with preoperative SRS. A phase 3 randomized clinical trial of preoperative vs postoperative SRS (NRG BN012) has began enrolling (NCT05438212).

Evaluation of fan-beam kilovoltage computed tomography image quality on a novel biological-guided radiotherapy platform.

Background and Purpose: A recently developed biology-guided radiotherapy platform, equipped with positron emission tomography (PET) and computed tomography (CT), provides both anatomical and functional image guidance for radiotherapy. This study aimed to characterize performance of the kilovoltage CT (kVCT) system on this platform using standard quality metrics measured on phantom and patient images, using CT simulator images as reference. Materials and Methods: Image quality metrics, including spatial resolution/modular transfer function (MTF), slice sensitivity profile (SSP), noise performance and image uniformity, contrast-noise ratio (CNR) and low-contrast resolution, geometric accuracy, and CT number (HU) accuracy, were evaluated on phantom images. Patient images were evaluated mainly qualitatively. Results: On phantom images the MTF10% is about 0.68 lp/mm for kVCT in PET/CT Linac. The SSP agreed with nominal slice thickness within 0.7 mm. The diameter of the smallest visible target (1% contrast) is about 5 mm using medium dose mode. The image uniformity is within 2.0 HU. The geometric accuracy tests passed within 0.5 mm. Relative to CT simulator images, the noise is generally higher and the CNR is lower in PET/CT Linac kVCT images. The CT number accuracy is comparable between the two systems with maximum deviation from the phantom manufacturer range within 25 HU. On patient images, higher spatial resolution and image noise are observed on PET/CT Linac kVCT images. Conclusions: Major image quality metrics of the PET/CT Linac kVCT were within vendor-recommended tolerances. Better spatial resolution but higher noise and better/comparable low contrast visibility were observed as compared to a CT simulator when images were acquired with clinical protocols.

Impact of CDKN2A/B, MTAP, and TERT Genetic Alterations on Survival in IDH Wild Type Glioblastomas.

PURPOSE: Poor outcomes in IDH wild-type (IDHwt) glioblastomas indicate the need to determine which genetic alterations can indicate poor survival and guidance of patient specific treatment options. We sought to identify the genetic alterations in these patients that predict for survival when adjusting particularly for treatments and other genetic alterations. METHODS: A cohort of 167 patients with pathologically confirmed IDHwt glioblastomas treated at our institution was retrospectively reviewed. Next generation sequencing was performed for each patient to determine tumor genetic alterations. Multivariable cox proportional hazards analysis for overall survival (OS) was performed to control for patient variables. RESULTS: CDKN2A, CDKN2B, and MTAP deletion predict for worse OS independently of other genetic alterations and patient characteristics (hazard ratio [HR] 2.192, p = 0.0017). Patients with CDKN2A copy loss (HR 2.963, p = 0.0037) or TERT mutated (HR 2.815, p = 0.0008) glioblastomas exhibited significant associations between radiation dose and OS, while CDKN2A and TERT wild type patients did not. CDKN2A deleted patients with NF1 mutations had worse OS (HR 1.990, p = 0.0540), while CDKN2A wild type patients had improved OS (HR 0.229, p = 0.0723). Patients with TERT mutated glioblastomas who were treated with radiation doses < 45 Gy (HR 3.019, p = 0.0010) but not those treated with ≥ 45 Gy exhibited worse OS compared to those without TERT mutations. CONCLUSION: In IDHwt glioblastomas, CDKN2A, CDKN2B, and MTAP predict for poor prognosis. TERT and CDKN2A mutations are associated with worse survival only when treated with lower radiation doses, thus potentially providing a genetic marker that can inform clinicians on proper dose-fractionation schemes.

Ensemble learning for glioma patients overall survival prediction using pre-operative MRIs.

Objective: Gliomas are the most common primary brain tumors. Approximately 70% of the glioma patients diagnosed with glioblastoma have an averaged overall survival (OS) of only ∼16 months. Early survival prediction is essential for treatment decision-making in glioma patients. Here we proposed an ensemble learning approach to predict the post-operative OS of glioma patients using only pre-operative MRIs.Approach: Our dataset was from the Medical Image Computing and Computer Assisted Intervention Brain Tumor Segmentation challenge 2020, which consists of multimodal pre-operative MRI scans of 235 glioma patients with survival days recorded. The backbone of our approach was a Siamese network consisting of twinned ResNet-based feature extractors followed by a 3-layer classifier. During training, the feature extractors explored traits of intra and inter-class by minimizing contrastive loss of randomly paired 2D pre-operative MRIs, and the classifier utilized the extracted features to generate labels with cost defined by cross-entropy loss. During testing, the extracted features were also utilized to define distance between the test sample and the reference composed of training data, to generate an additional predictor via K-NN classification. The final label was the ensemble classification from both the Siamese model and the K-NN model.Main results: Our approach classifies the glioma patients into 3 OS classes: long-survivors (>15 months), mid-survivors (between 10 and 15 months) and short-survivors (<10 months). The performance is assessed by the accuracy (ACC) and the area under the curve (AUC) of 3-class classification. The final result achieved an ACC of 65.22% and AUC of 0.81.Significance: Our Siamese network based ensemble learning approach demonstrated promising ability in mining discriminative features with minimal manual processing and generalization requirement. This prediction strategy can be potentially applied to assist timely clinical decision-making.

Socioeconomic and demographic determinants of radiation treatment and outcomes in glioblastoma patients.

Introduction: Poor outcomes in glioblastoma patients, despite advancing treatment paradigms, indicate a need to determine non-physiologic prognostic indicators of patient outcome. The impact of specific socioeconomic and demographic patient factors on outcomes is unclear. We sought to identify socioeconomic and demographic patient characteristics associated with patient survival and tumor progression, and to characterize treatment options and healthcare utilization. Methods: A cohort of 169 patients with pathologically confirmed glioblastomas treated at our institution was retrospectively reviewed. Multivariable cox proportional hazards analysis for overall survival (OS) and cumulative incidence of progression was performed. Differences in treatment regimen, patient characteristics, and neuro-oncology office use between different age and depressive disorder history patient subgroups were calculated two-sample t-tests, Fisher's exact tests, or linear regression analysis. Results: The median age of all patients at the time of initiation of radiation therapy was 60.5 years. The median OS of the cohort was 13.1 months. Multivariable analysis identified age (Hazard Ratio 1.02, 95% CI 1.00-1.04) and total resection (Hazard Ratio 0.52, 95% CI 0.33-0.82) as significant predictors of OS. Increased number of radiation fractions (Hazard Ratio 0.90, 95% CI 0.82-0.98), depressive disorder history (Hazard Ratio 0.59, 95% CI 0.37-0.95), and total resection (Hazard Ratio 0.52, 95% CI 0.31-0.88) were associated with decreased incidence of progression. Notably, patients with depressive disorder history were observed to have more neuro-oncology physician office visits over time (median 12 vs. 16 visits, p = 0.0121). Patients older than 60 years and those with Medicare (vs. private) insurance were less likely to receive as many radiation fractions (p = 0.0014) or receive temozolomide concurrently with radiation (Odds Ratio 0.46, p = 0.0139). Conclusion: Older glioblastoma patients were less likely to receive as diverse of a treatment regimen as their younger counterparts, which may be partially driven by insurance type. Patients with depressive disorder history exhibited reduced incidence of progression, which may be due to more frequent health care contact during neuro-oncology physician office visits.

Neutrophilia and post-radiation thrombocytopenia predict for poor prognosis in radiation-treated glioma patients.

Introduction: Poor outcomes in glioma patients indicate a need to determine prognostic indicators of survival to better guide patient specific treatment options. While preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) have been suggested as prognostic systemic inflammation markers, the impact of post-radiation changes in these cell types is unclear. We sought to identify which hematologic cell measurements before, during, or after radiation predicted for patient survival. Methods: A cohort of 182 patients with pathologically confirmed gliomas treated at our institution was retrospectively reviewed. Patient blood samples were collected within one month before, during, or within 3 months after radiation for quantification of hematologic cell counts, for which failure patterns were evaluated. Multivariable cox proportional hazards analysis for overall survival (OS) and progression-free survival (PFS) was performed to control for patient variables. Results: Multivariable analysis identified pre-radiation NLR > 4.0 (Hazard ratio = 1.847, p = 0.0039) and neutrophilia prior to (Hazard ratio = 1.706, p = 0.0185), during (Hazard ratio = 1.641, p = 0.0277), or after (Hazard ratio = 1.517, p = 0.0879) radiation as significant predictors of worse OS, with similar results for PFS. Post-radiation PLR > 200 (Hazard ratio = 0.587, p = 0.0062) and a percent increase in platelets after radiation (Hazard ratio = 0.387, p = 0.0077) were also associated with improved OS. Patients receiving more than 15 fractions of radiation exhibited greater post-radiation decreases in neutrophil and platelet counts than those receiving fewer. Patients receiving dexamethasone during radiation exhibited greater increases in neutrophil counts than those not receiving steroids. Lymphopenia, changes in lymphocyte counts, monocytosis, MLR, and changes in monocyte counts did not impact patient survival. Conclusion: Neutrophilia at any time interval surrounding radiotherapy, pre-radiation NLR, and post-radiation thrombocytopenia, but not lymphocytes or monocytes, are predictors of poor patient survival in glioma patients.

Volumetric Modulated Arc Therapy Enabled Total Body Irradiation (VMAT-TBI): Six-year Clinical Experience and Treatment Outcomes.

Total body irradiation is an important part of the conditioning regimens frequently used to prepare patients for allogeneic hematopoietic stem cell transplantation (SCT). Volumetric-modulated arc therapy enabled total body irradiation (VMAT-TBI), an alternative to conventional TBI (cTBI), is a novel radiotherapy treatment technique that has been implemented and investigated in our institution. The purpose of this study is to (1) report our six-year clinical experience in terms of treatment planning strategy and delivery time and (2) evaluate the clinical outcomes and toxicities in our cohort of patients treated with VMAT-TBI. This is a retrospective single center study. Forty-four patients at our institution received VMAT-TBI and chemotherapy conditioning followed by allogeneic SCT between 2014 and 2020. Thirty-two patients (73%) received standard-dose TBI (12-13.2 Gy in 6-8 fractions twice daily), whereas 12 (27%) received low-dose TBI (2-4 Gy in one fraction). Treatment planning, delivery, and treatment outcome data including overall survival (OS), relapse-free survival (RFS), and toxicities were analyzed. The developed VMAT-TBI planning strategy consistently generated plans satisfying our dose constraints, with planning target volume coverage >90%, mean lung dose ∼50% to 75% of prescription dose, and minimal hotspots in critical organs. Most of the treatment deliveries were <100 minutes (range 33-147, mean 72). The median follow-up was 26 months. At the last follow-up, 34 of 44 (77%) of patients were alive, with 1- and 2-year OS of 90% and 79% and RFS of 88% and 71%, respectively. The most common grade 3+ toxicities observed were mucositis (31 patients [71%]) and nephrotoxicity (6 patients [13%]), both of which were deemed multifactorial in cause. Four patients (9%) in standard-dose cohort developed grade 3+ pneumonitis, with 3 cases in the setting of documented respiratory infection and only 1 (2%) deemed likely related to radiation alone. VMAT-TBI provides a safe alternative to cTBI. The dose modulation capability of VMAT-TBI may lead to new treatment strategies, such as simultaneous boost and further critical organ sparing, for better malignant cell eradication, immune suppression, and lower toxicities.

Deep-learning and radiomics ensemble classifier for false positive reduction in brain metastases segmentation.

Stereotactic radiosurgery (SRS) is now the standard of care for brain metastases (BMs) patients. The SRS treatment planning process requires precise target delineation, which in clinical workflow for patients with multiple (>4) BMs (mBMs) could become a pronounced time bottleneck. Our group has developed an automated BMs segmentation platform to assist in this process. The accuracy of the auto-segmentation, however, is influenced by the presence of false-positive segmentations, mainly caused by the injected contrast during MRI acquisition. To address this problem and further improve the segmentation performance, a deep-learning and radiomics ensemble classifier was developed to reduce the false-positive rate in segmentations. The proposed model consists of a Siamese network and a radiomic-based support vector machine (SVM) classifier. The 2D-based Siamese network contains a pair of parallel feature extractors with shared weights followed by a single classifier. This architecture is designed to identify the inter-class difference. On the other hand, the SVM model takes the radiomic features extracted from 3D segmentation volumes as the input for twofold classification, either a false-positive segmentation or a true BM. Lastly, the outputs from both models create an ensemble to generate the final label. The performance of the proposed model in the segmented mBMs testing dataset reached the accuracy (ACC), sensitivity (SEN), specificity (SPE) and area under the curve of 0.91, 0.96, 0.90 and 0.93, respectively. After integrating the proposed model into the original segmentation platform, the average segmentation false negative rate (FNR) and the false positive over the union (FPoU) were 0.13 and 0.09, respectively, which preserved the initial FNR (0.07) and significantly improved the FPoU (0.55). The proposed method effectively reduced the false-positive rate in the BMs raw segmentations indicating that the integration of the proposed ensemble classifier into the BMs segmentation platform provides a beneficial tool for mBMs SRS management.

Preoperative Radiosurgery for Resected Brain Metastases: The PROPS-BM Multicenter Cohort Study.

PURPOSE: Preoperative radiosurgery (SRS) is a feasible alternative to postoperative SRS, with potential benefits in adverse radiation effect (ARE) and leptomeningeal disease (LMD) relapse. However, previous studies are limited by small patient numbers and single-institution designs. Our aim was to evaluate preoperative SRS outcomes and prognostic factors from a large multicenter cohort (Preoperative Radiosurgery for Brain Metastases [PROPS-BM]). METHODS AND MATERIALS: Patients with brain metastases (BM) from solid cancers who had at least 1 lesion treated with preoperative SRS and underwent a planned resection were included from 5 institutions. SRS to synchronous intact BM was allowed. Radiographic meningeal disease (MD) was categorized as either nodular or classical "sugarcoating" (cLMD). RESULTS: The cohort included 242 patients with 253 index lesions. Most patients (62.4%) had a single BM, 93.7% underwent gross total resection, and 98.8% were treated with a single fraction to a median dose of 15 Gray to a median gross tumor volume of 9.9 cc. Cavity local recurrence (LR) rates at 1 and 2 years were 15% and 17.9%, respectively. Subtotal resection (STR) was a strong independent predictor of LR (hazard ratio, 9.1; P < .001). One and 2-year rates of MD were 6.1% and 7.6% and of any grade ARE were 4.7% and 6.8% , respectively. The median overall survival (OS) duration was 16.9 months and the 2-year OS rate was 38.4%. The majority of MD was cLMD (13 of 19 patients with MD; 68.4%). Of 242 patients, 10 (4.1%) experienced grade ≥3 postoperative surgical complications. CONCLUSIONS: To our knowledge, this multicenter study represents the largest cohort treated with preoperative SRS. The favorable outcomes previously demonstrated in single-institution studies, particularly the low rates of MD and ARE, are confirmed in this expanded multicenter analysis, without evidence of an excessive postoperative surgical complication risk. STR, though infrequent, is associated with significantly worse cavity LR. A randomized trial between preoperative and postoperative SRS is warranted and is currently being designed.

Dosimetric Comparisons of Simulation Techniques for Left-Sided Breast Cancer in the COVID-19 Era: Techniques to Reduce Viral Transmission and Respect the Therapeutic Ratio.

Background The COVID-19 pandemic challenges our ability to safely treat breast cancer patients and requires revisiting current techniques to evaluate optimal strategies. Potential long-term sequelae of breast radiation have been addressed by deep inspiration breath-hold (DIBH), prone positioning, and four-dimensional computed tomography (4DCT) average intensity projection (AveIP)-based planning techniques. Dosimetric comparisons to determine the optimal technique to minimize the normal tissue dose for left-sided breast cancers have not been performed. Methods Ten patients with left-sided, early-stage breast cancer undergoing whole breast radiation were simulated in the prone position, supine with DIBH, and with a free-breathing 4DCT scan. The target and organs at risk (OAR) contours were delineated in all scans. Target volume coverage and OAR doses were assessed. One-way analysis of variance (ANOVA) and Kruskal-Wallis one-way ANOVA were used to detect differences in dosimetric parameters among the different treatment plans. Significance was set as p < 0.05. Results We demonstrate differences in heart and lung dose by the simulation technique. The mean heart doses in the prone, DIBH, and AveIP plans were 129 cGy, 154 cGy, and 262 cGy, respectively (p=0.02). The lung V20 in the prone, DIBH, and AveIP groups was 0.5%, 10.3% and 9.5%, respectively (p <0.001). Regardless of technique, lumpectomy planning target volume (PTV) coverage did not differ between the three plans with 95% of the lumpectomy PTV volume covered by 100.4% in prone plans, 98.5% in AveIP plans, and 99.3% in DIBH plans (p=0.7). Conclusions Prone positioning provides dosimetric advantages as compared to DIBH. When infection risks are considered as in the current coronavirus disease 2019 (COVID-19) pandemic, prone plans have advantages in reducing the risk of disease transmission. In instances where prone positioning is not feasible, obtaining an AveIP simulation may be useful in more accurately assessing heart and lung toxicity and informing a risk/benefit discussion of DIBH vs free breath-hold techniques.

Expanded Radiosurgery Capabilities Utilizing Gamma Knife Icon™.

The indications and techniques for the treatment of intracranial lesions continue to evolve with the advent of novel technologies. The Gamma Knife Icon™ (GK Icon™) is the most recent model available from Elekta, providing a frameless solution for stereotactic radiosurgery. At our institution, 382 patients with 3,213 separate intracranial lesions have been treated with frameless stereotactic radiotherapy using the GK Icon. The wide range of diagnoses include brain metastases, meningiomas, arteriovenous malformations, acoustic neuromas, pituitary adenomas, and several other histologies. The ability to perform both frame and frameless treatments on the GK Icon has significantly increased our daily volume by almost 50% on a single machine. Although the frameless approach allows one to take advantage of the precision in radiosurgery, the intricacies regarding treatment with this frameless system are not well established. Our initial experience will help to serve as a guide to those wishing to implement this novel technology in their practice.

miR-21 Plays a Dual Role in Tumor Formation and Cytotoxic Response in Breast Tumors.

Breast cancer (BrCa) relies on specific microRNAs to drive disease progression. Oncogenic miR-21 is upregulated in many cancers, including BrCa, and is associated with poor survival and treatment resistance. We sought to determine the role of miR-21 in BrCa tumor initiation, progression and treatment response. In a triple-negative BrCa model, radiation exposure increased miR-21 in both primary tumor and metastases. In vitro, miR-21 knockdown decreased survival in all BrCa subtypes in the presence of radiation. The role of miR-21 in BrCa initiation was evaluated by implanting wild-type miR-21 BrCa cells into genetically engineered mouse models where miR-21 was intact, heterozygous or globally ablated. Tumors were unable to grow in the mammary fat pads of miR-21-/- mice, and grew in ~50% of miR-21+/- and 100% in miR-21+/+ mice. The contribution of miR-21 to progression and metastases was tested by crossing miR-21-/- mice with mice that spontaneously develop BrCa. The global ablation of miR-21 significantly decreased the tumorigenesis and metastases of BrCa, while sensitizing tumors to radio- and chemotherapeutic agents via Fas/FasL-dependent apoptosis. Therefore, targeting miR-21 alone or in combination with various radio or cytotoxic therapies may represent novel and efficacious therapeutic modalities for the future treatment of BrCa patients.

Margin-Free Fractionated Stereotactic Radiation Therapy for Pediatric Brain Tumors.

PURPOSE: Conventional radiation therapy (RT) to pediatric brain tumors exposes a large volume of normal brain to unwarranted radiation causing late toxicity. We hypothesized that in well demarcated pediatric tumors lacking microscopic extensions, fractionated stereotactic RT (SRT), without target volume expansions, can reduce high dose normal tissue irradiation without affecting local control. METHODS AND MATERIALS: Between 2008 and 2017, 52 pediatric patients with brain tumors were treated using the CyberKnife (CK) with SRT in 180 to 200 cGy per fraction. Thirty representative cases were retrospectively planned for intensity modulated RT (IMRT) with 4-mm PTV expansion. We calculated the volume of normal tissue within the high or intermediate dose region adjacent to the target. Plan quality and radiation dose-volume dosimetry parameters were compared between CK and IMRT plans. We also reported overall survival, progression-free survival (PFS), and local control. RESULTS: Tumors included low-grade gliomas (n = 28), craniopharyngiomas (n = 16), and ependymomas (n = 8). The volumes of normal tissue receiving high (≥80% of prescription dose or ≥40 Gy) or intermediate (80% > dose ≥50% of the prescription dose or 40 Gy > dose ≥25 Gy) dose were significantly smaller with CK versus IMRT plans (P < .0001 for all comparisons). With a median follow-up of 3.7 years (range, 0.1-9.0), 3-year local control was 92% for all patients. Eight failures occurred: 1 craniopharyngioma (marginal), 2 ependymomas (both in-field), and 5 low-grade gliomas (2 in-field, 1 marginal, and 2 distant). CONCLUSIONS: Fractionated SRT using CK without target volume expansion appears to reduce the volume of irradiated tissue without majorly compromising local control in pediatric demarcated brain tumors. These results are hypothesis generating and should be tested and validated in prospective studies.

Phase II trial of hippocampal-sparing whole brain irradiation with simultaneous integrated boost for metastatic cancer.

BACKGROUND: Advanced radiotherapeutic treatment techniques limit the cognitive morbidity associated with whole-brain radiotherapy (WBRT) for brain metastasis through avoidance of hippocampal structures. However, achieving durable intracranial control remains challenging. METHODS: We conducted a single-institution single-arm phase II trial of hippocampal-sparing whole brain irradiation with simultaneous integrated boost (HSIB-WBRT) to metastatic deposits in adult patients with brain metastasis. Radiation therapy consisted of intensity-modulated radiation therapy delivering 20 Gy in 10 fractions over 2-2.5 weeks to the whole brain with a simultaneous integrated boost of 40 Gy in 10 fractions to metastatic lesions. Hippocampal regions were limited to 16 Gy. Cognitive performance and cancer outcomes were evaluated. RESULTS: A total of 50 patients, median age 60 years (interquartile range, 54-65), were enrolled. Median progression-free survival was 2.9 months (95% CI: 1.5-4.0) and overall survival was 9 months. As expected, poor survival and end-of-life considerations resulted in a high exclusion rate from cognitive testing. Nevertheless, mean decline in Hopkins Verbal Learning Test-Revised delayed recall (HVLT-R DR) at 3 months after HSIB-WBRT was only 10.6% (95% CI: -36.5‒15.3%). Cumulative incidence of local and intracranial failure with death as a competing risk was 8.8% (95% CI: 2.7‒19.6%) and 21.3% (95% CI: 10.7‒34.2%) at 1 year, respectively. Three grade 3 toxicities consisting of nausea, vomiting, and necrosis or headache were observed in 3 patients. Scores on the Multidimensional Fatigue Inventory 20 remained stable for evaluable patients at 3 months. CONCLUSIONS: HVLT-R DR after HSIB-WBRT was significantly improved compared with historical outcomes in patients treated with traditional WBRT, while achieving intracranial control similar to patients treated with WBRT plus stereotactic radiosurgery (SRS). This technique can be considered in select patients with multiple brain metastases who cannot otherwise receive SRS.

A web-based brain metastases segmentation and labeling platform for stereotactic radiosurgery.

PURPOSE: Stereotactic radiosurgery (SRS) has become a standard of care for patients' with brain metastases (BMs). However, the manual multiple BMs delineation can be time-consuming and could create an efficiency bottleneck in SRS workflow. There is a clinical need for automatic delineation and quantitative evaluation tools. In this study, building on our previous developed deep learning-based segmentation algorithms, we developed a web-based automated BMs segmentation and labeling platform to assist the SRS clinical workflow. METHOD: This platform was developed based on the Django framework, including a web client and a back-end server. The web client enables interactions as database access, data import, and image viewing. The server performs the segmentation and labeling tasks including: skull stripping; deep learning-based BMs segmentation; and affine registration-based BMs labeling. Additionally, the client can display BMs contours with corresponding atlas labels, and allows further postprocessing tasks including: (a) adjusting window levels; (b) displaying/hiding specific contours; (c) removing false-positive contours; (d) exporting contours as DICOM RTStruct files; etc. RESULTS: We evaluated this platform on 10 clinical cases with BMs number varied from 12-81 per case. The overall operation took about 4-5 min per patient. The segmentation accuracy was evaluated between the manual contour and automatic segmentation with several metrics. The averaged center of mass shift was 1.55 ± 0.36 mm, the Hausdorff distance was 2.98 ± 0.63 mm, the mean of surface-to-surface distance (SSD) was 1.06 ± 0.31 mm, and the standard deviation of SSD was 0.80 ± 0.16 mm. In addition, the initial averaged false-positive over union (FPoU) and false-negative rate (FNR) were 0.43 ± 0.19 and 0.15 ± 0.10 respectively. After case-specific postprocessing, the averaged FPoU and FNR were 0.19 ± 0.10 and 0.15 ± 0.10 respectively. CONCLUSION: The evaluated web-based BMs segmentation and labeling platform can substantially improve the clinical efficiency compared to manual contouring. This platform can be a useful tool for assisting SRS treatment planning and treatment follow-up.