Script-based implementation of automatic grid placement for lattice stereotactic body radiation therapy.

Background and purpose: Spatially fractionated radiation therapy (SFRT) has demonstrated promising clinical response in treating large tumors with heterogeneous dose distributions. Lattice stereotactic body radiation therapy (SBRT) is an SFRT technique that leverages inverse optimization to precisely localize regions of high and lose dose within disease. The aim of this study was to evaluate an automated heuristic approach to sphere placement in lattice SBRT treatment planning. Materials and methods: A script-based algorithm for sphere placement in lattice SBRT based on rules described by protocol was implemented within a treatment planning system. The script was applied to 22 treated cases and sphere distributions were compared with manually placed spheres in terms of number of spheres, number of protocol violations, and time required to place spheres. All cases were re-planned using script-generated spheres and plan quality was compared with clinical plans. Results: The mean number of spheres placed excluding those that violate rules was greater using the script (13.8) than that obtained by either dosimetrist (10.8 and 12.0, p < 0.001 and p = 0.003) or physicist (12.7, p = 0.061). The mean time required to generate spheres was significantly less using the script (2.5 min) compared to manual placement by dosimetrists (25.0 and 29.9 min) and physicist (19.3 min). Plan quality indices were similar in all cases with no significant differences, and OAR constraints remained met on all plans except two. Conclusion: A script placed spheres for lattice SBRT according to institutional protocol rules. The script-produced placement was superior to that of manually-specified spheres, as characterized by sphere number and rule violations.

The impact of individual-level income predicted from the BRFSS on the association between insurance status and overall survival among adults with cancer from the SEER program.

INTRODUCTION: Among patients with cancer in the United States, Medicaid insurance is associated with worse outcomes than private insurance and with similar outcomes as being uninsured. However, prior studies have not addressed the impact of individual-level socioeconomic status, which determines Medicaid eligibility, on the associations of Medicaid status and cancer outcomes. Our objective was to determine whether differences in cancer outcomes by insurance status persist after accounting for individual-level income. METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was queried for 18-64 year-old individuals with cancer from 2014-2016. Individual-level income was imputed using a model trained on Behavioral Risk Factors Surveillance Survey participants including covariates also present in SEER. The association of 1-year overall survival and insurance status was estimated with and without adjustment for estimated individual-level income and other covariates. RESULTS: A total of 416,784 cases in SEER were analyzed. The 1-yr OS for patients with private insurance, Medicaid insurance, and no insurance was 88.7%, 76.1%, and 73.7%, respectively. After adjusting for all covariates except individual-level income, 1-year OS differences were worse with Medicaid (-6.0%, 95% CI = -6.3 to -5.6) and no insurance (-6.7%, 95% CI = -7.3 to -6.0) versus private insurance. After also adjusting for estimated individual-level income, the survival difference for Medicaid patients was similar to privately insured (-0.4%, 95% CI = -1.9 to 1.1) and better than uninsured individuals (2.1%, 95% CI = 0.7 to 3.4). CONCLUSIONS: Income, rather than Medicaid status, may drive poor cancer outcomes in the low-income and Medicaid-insured population. Medicaid insurance coverage may improve cancer outcomes for low-income individuals.

Overview and Recommendations for Prospective Multi-institutional Spatially Fractionated Radiation Therapy Clinical Trials.

PURPOSE: The highly heterogeneous dose delivery of spatially fractionated radiation therapy (SFRT) is a profound departure from standard radiation planning and reporting approaches. Early SFRT studies have shown excellent clinical outcomes. However, prospective multi-institutional clinical trials of SFRT are still lacking. This NRG Oncology/American Association of Physicists in Medicine working group consensus aimed to develop recommendations on dosimetric planning, delivery, and SFRT dose reporting to address this current obstacle toward the design of SFRT clinical trials. METHODS AND MATERIALS: Working groups consisting of radiation oncologists, radiobiologists, and medical physicists with expertise in SFRT were formed in NRG Oncology and the American Association of Physicists in Medicine to investigate the needs and barriers in SFRT clinical trials. RESULTS: Upon reviewing the SFRT technologies and methods, this group identified challenges in several areas, including the availability of SFRT, the lack of treatment planning system support for SFRT, the lack of guidance in the physics and dosimetry of SFRT, the approximated radiobiological modeling of SFRT, and the prescription and combination of SFRT with conventional radiation therapy. CONCLUSIONS: Recognizing these challenges, the group further recommended several areas of improvement for the application of SFRT in cancer treatment, including the creation of clinical practice guidance documents, the improvement of treatment planning system support, the generation of treatment planning and dosimetric index reporting templates, and the development of better radiobiological models through preclinical studies and through conducting multi-institution clinical trials.

From Bragg Peaks to Adaptive Fields-The Need for Evidence-Based Adoption of New Technologies in Radiotherapy.

This Viewpoint discusses the need for multi-institutional prospective randomized trials of new technologies in radiotherapy to improve the therapeutic ratio and safety of radiotherapy treatments.

A pilot study of same-day MRI-only simulation and treatment with MR-guided adaptive palliative radiotherapy (MAP-RT).

We conducted a prospective pilot study evaluating the feasibility of same day MRI-only simulation and treatment with MRI-guided adaptive palliative radiotherapy (MAP-RT) for urgent palliative indications (NCT#03824366). All (16/16) patients were able to complete 99% of their first on-table attempted fractions, and no grades 3-5 toxicities occurred.

First treatments for Lattice stereotactic body radiation therapy using magnetic resonance image guided radiation therapy.

Two abdominal patients were treated with Lattice stereotactic body radiation therapy (SBRT) using magnetic resonance guided radiation therapy (MRgRT). This is one of the first reported treatments of Lattice SBRT with the use of MRgRT. A description of the treatment approach and planning considerations were incorporated into this report. MRgRT Lattice SBRT delivered similar planning quality metrics to established dosimetric parameters for Lattice SBRT. Increased signal intensity were seen in the MRI treatments for one of the patients during the course of treatment.

Nearest Neighbor-Based Strategy to Optimize Multi-View Triplet Network for Classification of Small-Sample Medical Imaging Data.

Multi-view classification with limited sample size and data augmentation is a very common machine learning (ML) problem in medicine. With limited data, a triplet network approach for two-stage representation learning has been proposed. However, effective training and verifying the features from the representation network for their suitability in subsequent classifiers are still unsolved problems. Although typical distance-based metrics for the training capture the overall class separability of the features, the performance according to these metrics does not always lead to an optimal classification. Consequently, an exhaustive tuning with all feature-classifier combinations is required to search for the best end result. To overcome this challenge, we developed a novel nearest-neighbor (NN) validation strategy based on the triplet metric. This strategy is supported by a theoretical foundation to provide the best selection of the features with a lower bound of the highest end performance. The proposed strategy is a transparent approach to identify whether to improve the features or the classifier. This avoids the need for repeated tuning. Our evaluations on real-world medical imaging tasks (i.e., radiation therapy delivery error prediction and sarcoma survival prediction) show that our strategy is superior to other common deep representation learning baselines [i.e., autoencoder (AE) and softmax]. The strategy addresses the issue of feature's interpretability which enables more holistic feature creation such that the medical experts can focus on specifying relevant data as opposed to tedious feature engineering.

Simulation-Free Radiation Therapy: An Emerging Form of Treatment Planning to Expedite Plan Generation for Patients Receiving Palliative Radiation Therapy.

Purpose: Herein we report the clinical and dosimetric experience for patients with metastases treated with palliative simulation-free radiation therapy (SFRT) at a single institution. Methods and Materials: SFRT was performed at a single institution. Multiple fractionation regimens were used. Diagnostic imaging was used for treatment planning. Patient characteristics as well as planning and treatment time points were collected. A matched cohort of patients with conventional computed tomography simulation radiation therapy (CTRT) was acquired to evaluate for differences in planning and treatment time. SFRT dosimetry was evaluated to determine the fidelity of SFRT. Descriptive statistics were calculated on all variables and statistical significance was evaluated using the Wilcoxon signed rank test and t test methods. Results: Thirty sessions of SFRT were performed and matched with 30 sessions of CTRT. Seventy percent of SFRT and 63% of CTRT treatments were single fraction. The median time to plan generation was 0.88 days (0.19-1.47) for SFRT and 1.90 days (0.39-5.23) for CTRT (P = .02). The total treatment time was 41 minutes (28-64) for SFRT and 30 minutes (21-45) for CTRT (P = .02). In the SFRT courses, the maximum and mean deviations in the actual delivered dose from the approved plans for the maximum dose were 4.1% and 0.07%, respectively. All deliveries were within a 5% threshold and deemed clinically acceptable. Conclusions: Palliative SFRT is an emerging technique that allowed for a statistically significant lower time to plan generation and was dosimetrically acceptable. This benefit must be weighed against increased total treatment time for patients receiving SFRT compared with CTRT, and appropriate patient selection is critical.

Remote Symptom Monitoring of Patients With Cancer Undergoing Radiation Therapy.

The goal of the study was to develop and test an automated short message service (SMS) and web service platform using CareSignal for remote symptom monitoring in a diverse population of patients with cancer. Twenty-eight patients with cancer undergoing radiotherapy were recruited at the start of their treatment regimen. Patients received a weekly SMS symptom survey to assess the severity of the side effects they experienced from treatment. An assessment of patient perceptions of the system in terms of patient-provider communication, feasibility, and overall satisfaction was conducted, finding overall good compliance in a sick patient population and patient willingness to engage with the software in the future.

NCCN Guidelines® Insights: Gastrointestinal Stromal Tumors, Version 2.2022.

Gastrointestinal stromal tumors (GIST) are the most common type of soft tissue sarcoma that occur throughout the gastrointestinal tract. Most of these tumors are caused by oncogenic activating mutations in the KIT or PDGFRA genes. The NCCN Guidelines for GIST provide recommendations for the diagnosis, evaluation, treatment, and follow-up of patients with these tumors. These NCCN Guidelines Insights summarize the panel discussion behind recent important updates to the guidelines, including revised systemic therapy options for unresectable, progressive, or metastatic GIST based on mutational status, and updated recommendations for the management of GIST that develop resistance to specific tyrosine kinase inhibitors.

Treatment of Stage I Lung Cancer Detected by Computed Tomography Screening.

Introduction: Reducing lung cancer deaths through early detection by computed tomography (CT) screening requires delivery of effective treatment. We performed this retrospective study to determine the types of treatment used for screen-detected stage I lung cancer at our academic center and to compare the demographic and clinical characteristics of patients by type of treatment. Methods: All persons screened in the lung cancer screening program at our institution through June 16, 2021, were included. Those with screening CT findings needing follow-up were managed through a thoracic surgery clinic. Demographic and clinical characteristics of patients diagnosed with having stage I lung cancer through June 16, 2021, were compared by type of treatment, with follow-up through December 31, 2021. Results: Stage I NSCLC was diagnosed in 54 of 2203 persons screened (2.5%), on the basis of biopsy in 37 and on imaging findings in 17 patients in whom a tissue diagnosis could not be obtained. Treatment was by lobectomy in 18, sublobar resection in 14, and stereotactic body radiation therapy (SBRT) in 22. Patients treated with SBRT had lower forced expiratory volume in 1 second (p < 0.001) and diffusing capacity of the lung for carbon monoxide (p < 0.001) and more comorbidities (p = 0.003) than those treated with surgery. New or recurrent cancer developed in nine patients (three lobectomy, three sublobar resection, three SBRT). Conclusions: Many patients with screen-detected stage I lung cancer are medically unfit for lobectomy, and a variety of treatments are being used. Assessment of treatment-based outcomes will be critical for ensuring an optimal balance of the risks and benefits of CT screening in a medically diverse population.

Soft Tissue Sarcoma, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology.

Soft tissue sarcomas (STS) are rare malignancies of mesenchymal cell origin that display a heterogenous mix of clinical and pathologic characteristics. STS can develop from fat, muscle, nerves, blood vessels, and other connective tissues. The evaluation and treatment of patients with STS requires a multidisciplinary team with demonstrated expertise in the management of these tumors. The complete NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Soft Tissue Sarcoma provide recommendations for the diagnosis, evaluation, and treatment of extremity/superficial trunk/head and neck STS, as well as retroperitoneal/intra-abdominal STS, desmoid tumors, and rhabdomyosarcoma. This portion of the NCCN Guidelines discusses general principles for the diagnosis and treatment of retroperitoneal/intra-abdominal STS, outlines treatment recommendations, and reviews the evidence to support the guidelines recommendations.

Considerations for Optimal Implementation of Radiation Therapy Into Multidisciplinary Care for Patients With Sarcoma.

Radiation therapy (RT) plays an important role in reducing the risk of local recurrence associated with localized soft-tissue sarcoma (STS) treated with resection alone. The use of image guidance and intensity modulated RT has allowed for excellent local control after wide resection, even with positive margins, with an improved toxicity profile compared with historical strategies used in the literature. However, optimal implementation of RT into multidisciplinary care remains a challenge. Tumors can arise anywhere in the body and exhibit a wide range of behavior, so individualized use of RT is difficult. Data regarding RT for STS are also limited, so making evidence-based decisions is difficult. The American Society for Radiation Oncology recently commissioned a multidisciplinary task force, led by radiation oncologist chair and cochair Drs Kilian Salerno and Ashleigh Guadagnolo. Through 5 key questions (KQs), the recommendations address the most important topics for consideration when discussing RT use with a multidisciplinary treatment team. For patients with localized extremity sarcoma, the authors generally recommend delivering RT for patients at a high risk of recurrence (ie, patients with large, high-grade tumors, especially those expected to have positive margins after surgery). KQ2 and KQ3 recommend that most patients undergo preoperative intensity modulated RT using small clinical target volumes that have been associated with excellent local control in prospective studies. The final KQ discusses the role of preoperative RT in the management of patients with retroperitoneal sarcoma, which is controversial. Overall, the guidelines offer evidence-based expert consensus recommendations that can be used today as a starting point for a multidisciplinary recommendations about RT for patients at your clinic. I look forward to future versions of this guideline, which will consider the results of ongoing work aimed at further improving the value of RT for patients with STS.

Neoadjuvant Therapy Induces a Potent Immune Response to Sarcoma, Dominated by Myeloid and B Cells.

PURPOSE: To characterize changes in the soft-tissue sarcoma (STS) tumor immune microenvironment induced by standard neoadjuvant therapy with the goal of informing neoadjuvant immunotherapy trial design. EXPERIMENTAL DESIGN: Paired pre- and postneoadjuvant therapy specimens were retrospectively identified for 32 patients with STSs and analyzed by three modalities: multiplexed IHC, NanoString, and RNA sequencing with ImmunoPrism analysis. RESULTS: All 32 patients, representing a variety of STS histologic subtypes, received neoadjuvant radiotherapy and 21 (66%) received chemotherapy prior to radiotherapy. The most prevalent immune cells in the tumor before neoadjuvant therapy were myeloid cells (45% of all immune cells) and B cells (37%), with T (13%) and natural killer (NK) cells (5%) also present. Neoadjuvant therapy significantly increased the total immune cells infiltrating the tumors across all histologic subtypes for patients receiving neoadjuvant radiotherapy with or without chemotherapy. An increase in the percentage of monocytes and macrophages, particularly M2 macrophages, B cells, and CD4+ T cells was observed postneoadjuvant therapy. Upregulation of genes and cytokines associated with antigen presentation was also observed, and a favorable pathologic response (≥90% necrosis postneoadjuvant therapy) was associated with an increase in monocytic infiltrate. Upregulation of the T-cell checkpoint TIM3 and downregulation of OX40 were observed posttreatment. CONCLUSIONS: Standard neoadjuvant therapy induces both immunostimulatory and immunosuppressive effects within a complex sarcoma microenvironment dominated by myeloid and B cells. This work informs ongoing efforts to incorporate immune checkpoint inhibitors and novel immunotherapies into the neoadjuvant setting for STSs.

LITE SABR M1: A phase I trial of Lattice stereotactic body radiotherapy for large tumors.

PURPOSE: Stereotactic body radiotherapy (SBRT) is an attractive treatment option for patients with metastatic and/or unresectable tumors, however its use is limited to smaller tumors. Lattice is a form of spatially fractionated radiotherapy that may allow safe delivery of ablative doses to bulky tumors. We previously described Lattice SBRT, which delivers 20 Gy in 5 fractions with a simultaneous integrated boost to 66.7 Gy in a defined geometric arrangement (Lattice boost). The goal of this study was to prospectively evaluate the acute toxicity and quality of life (QoL) of patients with large tumors (>5 cm) treated with Lattice SBRT. METHODS: This was a single-arm phase I trial conducted between October 2019 and August 2020. Patients with tumors > 4.5 cm were eligible. Lattice SBRT was delivered every other day. The primary outcome was the rate of 90-day treatment-associated (probably or definitely attributable) grade 3 + acute toxicity by Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 criteria. Other outcomes included changes in patient reported toxicity and QoL inventories, GTV, and peripheral blood cytokines. RESULTS: Twenty patients (22 tumors) were enrolled. Median GTV was 579.2 cc (range: 54.2-3713.5 cc) in volume and 11.1 cm (range: 5.6-21.4 cm) in greatest axial diameter. Fifty percent of tumors were in the thorax, 45% abdomen/pelvis, and 5% extremity. There was no likely treatment-associated grade 3 + toxicity in the 90-day period (acute and sub-acute). There was one case of grade 4 toxicity possibly associated with Lattice SBRT. CONCLUSIONS: This phase I study met its primary endpoint of physician reported short-term safety. An ongoing phase II clinical trial of Lattice SBRT will evaluate late safety and efficacy of this novel technique.

LITE SABR M1: Planning design and dosimetric endpoints for a phase I trial of lattice SBRT.

PURPOSE: Lattice stereotactic body radiation therapy (SBRT) is a form of spatially fractionated radiation therapy (SFRT) using SBRT methods. This study reports clinical dosimetric endpoints achieved for Lattice SBRT plans delivering 20 Gy in 5 fractions to the periphery of a tumor with a simultaneous integrated boost (SIB) of 66.7 Gy, as part of a prospective Phase I clinical trial (NCT04133415). Additionally, it updates previously reported planning and delivery techniques based on extended experience with a broader patient population. METHODS: Patients were enrolled on a single-arm phase I trial conducted between November 2019 and August 2020. Eligibility was restricted to tumors >4.5 cm in the largest dimension. Characteristic SFRT dose gradients were achieved using a lattice of 1.5 cm diameter spheres spaced within the GTV in a regular pattern, with peak-to-valley dose varying from 66.7 Gy to 20 Gy within 1.5 cm. Organ-at-risk (OAR) sparing followed AAPM TG101 recommendations for 5-fraction SBRT. RESULTS: Twenty patients (22 plans) were enrolled on study, with one additional plan treated off study. All OAR and target coverage planning objectives were achieved, with the exception of a single small bronchus. Conformity of the 20 Gy isodose line significantly improved over the course of the study. The majority (85.2%) of treatment fractions were delivered in a 30 minutes timeslot, with 4 (3.5%) exceeding a total treatment time of 40 minutes. CONCLUSION: Lattice SBRT planning techniques produce consistent and efficient treatment plans. Refined techniques described here further improve the quality of the planning technique.

MRI-based delta-radiomics predicts pathologic complete response in high-grade soft-tissue sarcoma patients treated with neoadjuvant therapy.

PURPOSE: In high-grade soft-tissue sarcomas (STS) the standard of care encompasses multimodal therapy regimens. While there is a growing body of evidence for prognostic pretreatment radiomic models, we hypothesized that temporal changes in radiomic features following neoadjuvant treatment ("delta-radiomics") may be able to predict the pathological complete response (pCR). METHODS: MRI scans (T1-weighted with fat-saturation and contrast-enhancement (T1FSGd) and T2-weighted with fat-saturation (T2FS)) of patients with STS of the extremities and trunk treated with neoadjuvant therapy were gathered from two independent institutions (training: 103, external testing: 53 patients). pCR was defined as <5% viable cells. After segmentation and preprocessing, 105 radiomic features were extracted. Delta-radiomic features were calculated by subtraction of features derived from MRI scans obtained before and after neoadjuvant therapy. After feature reduction, machine learning modeling was performed in 100 iterations of 3-fold nested cross-validation. Delta-radiomic models were compared with single timepoint models in the testing cohort. RESULTS: The combined delta-radiomic models achieved the best area under the receiver operating characteristic curve (AUC) of 0.75. Pre-therapeutic tumor volume was the best conventional predictor (AUC 0.70). The T2FS-based delta-radiomic model had the most balanced classification performance with a balanced accuracy of 0.69. Delta-radiomic models achieved better reproducibility than single timepoint radiomic models, RECIST or the peri-therapeutic volume change. Delta-radiomic models were significantly associated with survival in multivariate Cox regression. CONCLUSION: This exploratory analysis demonstrated that MRI-based delta-radiomics improves prediction of pCR over tumor volume and RECIST. Delta-radiomics may one day function as a biomarker for personalized treatment adaptations.