Modern Radiation Treatment Planning Parameters and Outcomes in Pediatric Tectal Gliomas.

Purpose: Pediatric low-grade tectal gliomas are rare, indolent tumors of the brain stem. We reviewed outcomes of pediatric patients who received a diagnosis of low-grade tectal gliomas and report dosimetric parameters for those receiving radiation therapy (RT). Methods and Materials: We retrospectively reviewed all pediatric patients (age <18 years) at our institution diagnosed with a low-grade glioma between 1993 and 2020 (n = 288). Twenty-three patients with tectal gliomas were identified. Patients who received RT (n = 8) had detailed dosimetric analyses performed. Doses to critical structures and any resulting toxicities were reviewed. Minimum follow-up was 2 years and complete follow-up was available for all patients. Results: Twenty-three patients, with a median age of 8.9 years, were included (range, 0.5-16.2 years). At a median follow-up of 7.4 years (range, 2-24 years), all were alive at the end of the study period. Three patients (13%) were treated with upfront RT; none of these patients developed local failure (LF) after a median follow-up of 10.6 years. One patient was treated with upfront chemotherapy with no evidence of progression afterward. Nineteen patients were initially observed after diagnosis and 26% of them (n = 5) experienced local progression. All 5 were treated with salvage RT, with 1 patient requiring further treatment with chemotherapy. Fractionation schedules for patients undergoing upfront or salvage RT included 50.4 Gy in 28 fractions (n = 4), 54 Gy in 30 fractions (n = 2), and 51 Gy in 30 fractions (n = 2). For patients treated after 2007, the gross tumor volume was delineated on a T2 magnetic resonance imaging with an average gross tumor volume-to-planning target volume expansion of 4.5 mm (range, 3-5 mm). Detailed dosimetric parameters were available for all patients treated with RT. Conclusions: Our review supports the indolent behavior for most tectal gliomas. For the subset of tumors with evidence of progression, modern photon RT results in excellent oncologic outcomes with minimal late effects.

Lumbar and Thoracic Vertebrae Segmentation in CT Scans Using a 3D Multi-Object Localization and Segmentation CNN.

Radiation treatment of cancers like prostate or cervix cancer requires considering nearby bone structures like vertebrae. In this work, we present and validate a novel automated method for the 3D segmentation of individual lumbar and thoracic vertebra in computed tomography (CT) scans. It is based on a single, low-complexity convolutional neural network (CNN) architecture which works well even if little application-specific training data are available. It is based on volume patch-based processing, enabling the handling of arbitrary scan sizes. For each patch, it performs segmentation and an estimation of up to three vertebrae center locations in one step, which enables utilizing an advanced post-processing scheme to achieve high segmentation accuracy, as required for clinical use. Overall, 1763 vertebrae were used for the performance assessment. On 26 CT scans acquired for standard radiation treatment planning, a Dice coefficient of 0.921 ± 0.047 (mean ± standard deviation) and a signed distance error of 0.271 ± 0.748 mm was achieved. On the large-sized publicly available VerSe2020 data set with 129 CT scans depicting lumbar and thoracic vertebrae, the overall Dice coefficient was 0.940 ± 0.065 and the signed distance error was 0.109 ± 0.301 mm. A comparison to other methods that have been validated on VerSe data showed that our approach achieved a better overall segmentation performance.

Guiding principles on the education and practice of theranostics.

PURPOSE: The recent development and approval of new diagnostic imaging and therapy approaches in the field of theranostics have revolutionised nuclear medicine practice. To ensure the provision of these new imaging and therapy approaches in a safe and high-quality manner, training of nuclear medicine physicians and qualified specialists is paramount. This is required for trainees who are learning theranostics practice, and for ensuring minimum standards for knowledge and competency in existing practising specialists. METHODS: To address the need for a training curriculum in theranostics that would be utilised at a global level, a Consultancy Meeting was held at the IAEA in May 2023, with participation by experts in radiopharmaceutical therapy and theranostics including representatives of major international organisations relevant to theranostics practice. RESULTS: Through extensive discussions and review of existing curriculum and guidelines, a harmonised training program for theranostics was developed, which aims to ensure safe and high quality theranostics practice in all countries. CONCLUSION: The guiding principles for theranostics training outlined in this paper have immediate relevance for the safe and effective practice of theranostics.

Radiation effects on retinal layers revealed by OCT, OCT-A, and perimetry as a function of dose and time from treatment.

Optical coherence tomography (OCT) has become a key method for diagnosing and staging radiation retinopathy, based mainly on the presence of fluid in the central macula. A robust retinal layer segmentation method is required for identification of the specific layers involved in radiation-induced pathology in individual eyes over time, in order to determine damage driven by radiation injury to the microvessels and to the inner retinal neurons. Here, we utilized OCT, OCT-angiography, visual field testing, and patient-specific dosimetry models to analyze abnormal retinal layer thickening and thinning relative to microvessel density, visual function, radiation dose, and time from radiotherapy in a cross-sectional cohort of uveal melanoma patients treated with 125I-plaque brachytherapy. Within the first 24 months of radiotherapy, we show differential thickening and thinning of the two inner retinal layers, suggestive of microvessel leakage and neurodegeneration, mostly favoring thickening. Four out of 13 eyes showed decreased inner retinal capillary density associated with a corresponding normal inner retinal thickness, indicating early microvascular pathology. Two eyes showed the opposite: significant inner retinal layer thinning and normal capillary density, indicating early neuronal damage preceding a decrease in capillary density. At later time points, inner retinal thinning becomes the dominant pathology and correlates significantly with decreased vascularity, vision loss, and dose to the optic nerve. Stable multiple retinal layer segmentation provided by 3D graph-based methods aids in assessing the microvascular and neuronal response to radiation, information needed to target therapeutics for radiation retinopathy and vision loss.

Survival and neurological outcomes following management of intramedullary spinal metastasis patients: a case series with comprehensive review of the literature.

Intramedullary spinal cord metastasis (ISCM), though rare, represents a potentially debilitating manifestation of systemic cancer. With emerging advances in cancer care, ISCMs are increasingly being encountered in clinical practice. Herein, we describe one of the larger retrospective single institutional case series on ISCMs, analyze survival and treatment outcomes, and review the literature. All surgically evaluated ISCMs at our institution between 2005 and 2023 were retrospectively reviewed. Demographics, tumor features, treatment, and clinical outcome characteristics were collected. Neurological function was quantified via the Frankel grade and the McCormick score (MCS). The pre- and post-operative Karnofsky performance scores (KPS) were used to assess functional status. Descriptive statistics, univariate analysis, log-rank test, and the Kaplan-Meier survival analysis were performed. A total of 9 patients were included (median age 67 years (range, 26-71); 6 were male). Thoracic and cervical spinal segments were most affected (4 patients each). Six patients (75%) underwent surgical management (1 biopsy and 5 resections), and 3 cases underwent chemoradiation only. Post-operatively, 2 patients had an improvement in their neurological exam with one patient becoming ambulatory after surgery; three patients maintained their neurological exam, and 1 had a decline. There was no statistically significant difference in the pre- and post-operative MCS and median KPS scores in surgically treated patients. Median OS after ISCM diagnosis was 7 months. Absence of brain metastasis, tumor histology (renal and melanoma), cervical/thoracic location, and post-op KPS ≥ 70 showed a trend toward improved overall survival. The incidence of ISCM is increasing, and earlier diagnosis and treatment are considered key for the preservation of neurological function. When patient characteristics are favorable, surgical resection of ISCM can be considered in patients with rapidly progressive neurological deficits. Surgical treatment was not associated with an improvement in overall survival in patients with ISCMs.

A Technique to Enable Efficient Adaptive Radiation Therapy: Automated Contouring of Prostate and Adjacent Organs.

Purpose: The purpose of this work was to investigate the use of a segmentation approach that could potentially improve the speed and reproducibility of contouring during magnetic resonance-guided adaptive radiation therapy. Methods and Materials: The segmentation algorithm was based on a hybrid deep neural network and graph optimization approach that also allows rapid user intervention (Deep layered optimal graph image segmentation of multiple objects and surfaces [LOGISMOS] + just enough interaction [JEI]). A total of 115 magnetic resonance-data sets were used for training and quantitative assessment. Expert segmentations were used as the independent standard for the prostate, seminal vesicles, bladder, rectum, and femoral heads for all 115 data sets. In addition, 3 independent radiation oncologists contoured the prostate, seminal vesicles, and rectum for a subset of patients such that the interobserver variability could be quantified. Consensus contours were then generated from these independent contours using a simultaneous truth and performance level estimation approach, and the deviation of Deep LOGISMOS + JEI contours to the consensus contours was evaluated and compared with the interobserver variability. Results: The absolute accuracy of Deep LOGISMOS + JEI generated contours was evaluated using median absolute surface-to-surface distance which ranged from a minimum of 0.20 mm for the bladder to a maximum of 0.93 mm for the prostate compared with the independent standard across all data sets. The median relative surface-to-surface distance was less than 0.17 mm for all organs, indicating that the Deep LOGISMOS + JEI algorithm did not exhibit a systematic under- or oversegmentation. Interobserver variability testing yielded a mean absolute surface-to-surface distance of 0.93, 1.04, and 0.81 mm for the prostate, seminal vesicles, and rectum, respectively. In comparison, the deviation of Deep LOGISMOS + JEI from consensus simultaneous truth and performance level estimation contours was 0.57, 0.64, and 0.55 mm for the same organs. On average, the Deep LOGISMOS algorithm took less than 26 seconds for contour segmentation. Conclusions: Deep LOGISMOS + JEI segmentation efficiently generated clinically acceptable prostate and normal tissue contours, potentially limiting the need for time intensive manual contouring with each fraction.

Surgical Management of Craniospinal Axis Solitary Fibrous Tumors: A Single-Institution Case Series and Comprehensive Review of the Literature.

BACKGROUND AND OBJECTIVES: Meningeal solitary fibrous tumors (SFTs) comprise 0.4% of primary central nervous system neoplasms and carry metastatic potential. Disease course and optimal management are largely unknown, and there is currently no literature rigorously describing neurological outcomes in surgically managed SFTs. We present one of the largest craniospinal SFT series, analyze patient outcomes, and extensively review the associated literature. METHODS: All surgically managed SFTs at our institution between January 2005 and March 2023 were retrospectively reviewed. Patient demographics, tumor and radiographic features, treatment, and clinical outcomes were collected. Neurological function was quantified using Frankel grade and Neurologic Assessment in Neuro-Oncology scores. Descriptive statistics, multivariate analysis, log-rank test, and Kaplan-Meier survival analysis were performed. RESULTS: Twenty-one patients satisfied inclusion criteria. Tumor locations included 15 supratentorial, three infratentorial, and three spinal. All patients underwent surgical resection, and 16 (76.2%) underwent radiation. Six (28.6%) patients had tumor recurrence, and three (14.3%) developed metastasis. Younger age and higher postoperative Frankel grade were significantly associated with increased overall survival (OS) ( P = .011, P = .002, respectively). All patients symptomatically improved or stabilized after surgery, and Neurologic Assessment in Neuro-Oncology score ( P = .001) and functional status significantly improved postoperatively (Karnofsky Performance Status: 65.2 ± 25.2 vs 91.4 ± 13.5, P = .001). Sex, adjuvant radiation, and extent of resection were not significantly associated with OS. CONCLUSION: SFT of the central nervous system is a rare entity with a variable clinical course. Surgical resection was associated with improved postoperative functional and neurological status. Higher postoperative neurological function was significantly associated with OS. Further studies are warranted to validate a standardized treatment algorithm and investigate the efficacy of adjuvant radiation in SFT.

Magnetic Resonance Imaging of Iron Metabolism with T2* Mapping Predicts an Enhanced Clinical Response to Pharmacologic Ascorbate in Patients with GBM.

PURPOSE: Pharmacologic ascorbate (P-AscH-) is hypothesized to be an iron (Fe)-dependent tumor-specific adjuvant to chemoradiation in treating glioblastoma (GBM). This study determined the efficacy of combining P-AscH- with radiation and temozolomide in a phase II clinical trial while simultaneously investigating a mechanism-based, noninvasive biomarker in T2* mapping to predict GBM response to P-AscH- in humans. PATIENTS AND METHODS: The single-arm phase II clinical trial (NCT02344355) enrolled 55 subjects, with analysis performed 12 months following the completion of treatment. Overall survival (OS) and progression-free survival (PFS) were estimated with the Kaplan-Meier method and compared across patient subgroups with log-rank tests. Forty-nine of 55 subjects were evaluated using T2*-based MRI to assess its utility as an Fe-dependent biomarker. RESULTS: Median OS was estimated to be 19.6 months [90% confidence interval (CI), 15.7-26.5 months], a statistically significant increase compared with historic control patients (14.6 months). Subjects with initial T2* relaxation < 50 ms were associated with a significant increase in PFS compared with T2*-high subjects (11.2 months vs. 5.7 months, P < 0.05) and a trend toward increased OS (26.5 months vs. 17.5 months). These results were validated in preclinical in vitro and in vivo model systems. CONCLUSIONS: P-AscH- combined with temozolomide and radiotherapy has the potential to significantly enhance GBM survival. T2*-based MRI assessment of tumor iron content is a prognostic biomarker for GBM clinical outcomes. See related commentary by Nabavizadeh and Bagley, p. 255.

Cancer Informatics for Cancer Centers: Sharing Ideas on How to Build an Artificial Intelligence-Ready Informatics Ecosystem for Radiation Oncology.

In August 2022, the Cancer Informatics for Cancer Centers brought together cancer informatics leaders for its biannual symposium, Precision Medicine Applications in Radiation Oncology, co-chaired by Quynh-Thu Le, MD (Stanford University), and Walter J. Curran, MD (GenesisCare). Over the course of 3 days, presenters discussed a range of topics relevant to radiation oncology and the cancer informatics community more broadly, including biomarker development, decision support algorithms, novel imaging tools, theranostics, and artificial intelligence (AI) for the radiotherapy workflow. Since the symposium, there has been an impressive shift in the promise and potential for integration of AI in clinical care, accelerated in large part by major advances in generative AI. AI is now poised more than ever to revolutionize cancer care. Radiation oncology is a field that uses and generates a large amount of digital data and is therefore likely to be one of the first fields to be transformed by AI. As experts in the collection, management, and analysis of these data, the informatics community will take a leading role in ensuring that radiation oncology is prepared to take full advantage of these technological advances. In this report, we provide highlights from the symposium, which took place in Santa Barbara, California, from August 29 to 31, 2022. We discuss lessons learned from the symposium for data acquisition, management, representation, and sharing, and put these themes into context to prepare radiation oncology for the successful and safe integration of AI and informatics technologies.

Surgical management of craniospinal axis malignant peripheral nerve sheath tumors: a single-institution experience and literature review.

BACKGROUND: Malignant peripheral nerve sheath tumor (MPNST) is an exceedingly rare and aggressive tumor, with limited literature on its management. Herein, we present our series of surgically managed craniospinal MPNSTs, analyze their outcomes, and review the literature. METHODS: We retrospectively reviewed surgically managed primary craniospinal MPNSTs treated at our institution between January 2005 and May 2023. Patient demographics, tumor features, and treatment outcomes were assessed. Neurological function was quantified using the Frankel grade and Karnofsky performance scores. Descriptive statistics, rank-sum tests, and Kaplan-Meier survival analyses were performed. RESULTS: Eight patients satisfied the inclusion criteria (4 male, 4 female). The median age at presentation was 38 years (range 15-67). Most tumors were localized to the spine (75%), and 3 patients had neurofibromatosis type 1. The most common presenting symptoms were paresthesia (50%) and visual changes (13%). The median tumor size was 3 cm, and most tumors were oval-shaped (50%) with well-defined borders (75%). Six tumors were high grade (75%), and gross total resection was achieved in 5 patients, with subtotal resection in the remaining 3 patients. Postoperative radiotherapy and chemotherapy were performed in 6 (75%) and 4 (50%) cases, respectively. Local recurrence occurred in 5 (63%) cases, and distant metastases occurred in 2 (25%). The median overall survival was 26.7 months. Five (63%) patients died due to recurrence. CONCLUSIONS: Primary craniospinal MPNSTs are rare and have an aggressive clinical course. Early diagnosis and treatment are essential for managing these tumors. In this single-center study with a small cohort, maximal resection, low-grade pathology, young age (< 30), and adjuvant radiotherapy were associated with improved survival.

Head and Neck Cancer Segmentation in FDG PET Images: Performance Comparison of Convolutional Neural Networks and Vision Transformers.

Convolutional neural networks (CNNs) have a proven track record in medical image segmentation. Recently, Vision Transformers were introduced and are gaining popularity for many computer vision applications, including object detection, classification, and segmentation. Machine learning algorithms such as CNNs or Transformers are subject to an inductive bias, which can have a significant impact on the performance of machine learning models. This is especially relevant for medical image segmentation applications where limited training data are available, and a model's inductive bias should help it to generalize well. In this work, we quantitatively assess the performance of two CNN-based networks (U-Net and U-Net-CBAM) and three popular Transformer-based segmentation network architectures (UNETR, TransBTS, and VT-UNet) in the context of HNC lesion segmentation in volumetric [F-18] fluorodeoxyglucose (FDG) PET scans. For performance assessment, 272 FDG PET-CT scans of a clinical trial (ACRIN 6685) were utilized, which includes a total of 650 lesions (primary: 272 and secondary: 378). The image data used are highly diverse and representative for clinical use. For performance analysis, several error metrics were utilized. The achieved Dice coefficient ranged from 0.833 to 0.809 with the best performance being achieved by CNN-based approaches. U-Net-CBAM, which utilizes spatial and channel attention, showed several advantages for smaller lesions compared to the standard U-Net. Furthermore, our results provide some insight regarding the image features relevant for this specific segmentation application. In addition, results highlight the need to utilize primary as well as secondary lesions to derive clinically relevant segmentation performance estimates avoiding biases.

Predictive power of deep-learning segmentation based prognostication model in non-small cell lung cancer.

Purpose: The study aims to create a model to predict survival outcomes for non-small cell lung cancer (NSCLC) after treatment with stereotactic body radiotherapy (SBRT) using deep-learning segmentation based prognostication (DESEP). Methods: The DESEP model was trained using imaging from 108 patients with NSCLC with various clinical stages and treatment histories. The model generated predictions based on unsupervised features learned by a deep-segmentation network from computed tomography imaging to categorize patients into high and low risk groups for overall survival (DESEP-predicted-OS), disease specific survival (DESEP-predicted-DSS), and local progression free survival (DESEP-predicted-LPFS). Serial assessments were also performed using auto-segmentation based volumetric RECISTv1.1 and computer-based unidimensional RECISTv1.1 patients was performed. Results: There was a concordance between the DESEP-predicted-LPFS risk category and manually calculated RECISTv1.1 (φ=0.544, p=0.001). Neither the auto-segmentation based volumetric RECISTv1.1 nor the computer-based unidimensional RECISTv1.1 correlated with manual RECISTv1.1 (p=0.081 and p=0.144, respectively). While manual RECISTv1.1 correlated with LPFS (HR=6.97,3.51-13.85, c=0.70, p<0.001), it could not provide insight regarding DSS (p=0.942) or OS (p=0.662). In contrast, the DESEP-predicted methods were predictive of LPFS (HR=3.58, 1.66-7.18, c=0.60, p<0.001), OS (HR=6.31, 3.65-10.93, c=0.71, p<0.001) and DSS (HR=9.25, 4.50-19.02, c=0.69, p<0.001). The promising results of the DESEP model were reproduced for the independent, external datasets of Stanford University, classifying survival and 'dead' group in their Kaplan-Meyer curves (p = 0.019). Conclusion: Deep-learning segmentation based prognostication can predict LPFS as well as OS, and DSS after SBRT for NSCLC. It can be used in conjunction with current standard of care, manual RECISTv1.1 to provide additional insights regarding DSS and OS in NSCLC patients receiving SBRT. Summary: While current standard of care, manual RECISTv1.1 correlated with local progression free survival (LPFS) (HR=6.97,3.51-13.85, c=0.70, p<0.001), it could not provide insight regarding disease specific survival (DSS) (p=0.942) or overall survival (OS) (p=0.662). In contrast, the deep-learning segmentation based prognostication (DESEP)-predicted methods were predictive of LPFS (HR=3.58, 1.66-7.18, c=0.60, p<0.001), OS (HR=6.31, 3.65-10.93, c=0.71, p<0.001) and DSS (HR=9.25, 4.50-19.02, c=0.69, p<0.001). DESEP can be used in conjunction with current standard of care, manual RECISTv1.1 to provide additional insights regarding DSS and OS in NSCLC patients.

Cutaneous Metastasis of Alveolar Rhabdomyosarcoma in a Child.

ABSTRACT: Rhabdomyosarcoma (RMS) is one of the most common soft tissue sarcomas in children. This lesion is classically included in the generic group of "small round blue cell tumors" along with other entities that share similar microscopic features. Although the head and neck region is a frequent site for primary tumors, cutaneous metastases of RMS involving this anatomical location are rare in the pediatric population. We report a case of a 12-year old girl previously diagnosed with a primary alveolar RMS involving the left maxillary sinus, presenting with a metastatic lesion on the skin of the left temple area. Along with a brief review of the previous case reports on the topic, we highlight the initial immunohistochemistry panel useful for diagnosing this tumor.

Initial clinical applications treating pediatric and adolescent patients using MR-guided radiotherapy.

Purpose: To demonstrate the clinical applications and feasibility of online adaptive magnetic resonance image guided radiotherapy (MRgRT) in the pediatric, adolescent and young adult (AYA) population. Methods: This is a retrospective case series of patients enrolled onto a prospective study. All pediatric (age < 18) and AYA patients (age< 30), treated on the Elekta Unity MR linear accelerator (MRL) from 2019 to 2021 were enrolled onto a prospective registry. Rationale for MRgRT included improved visualization of and alignment to the primary tumor, re-irradiation in a critical area, ability to use smaller margins, and need for daily adaptive replanning to minimize dose to adjacent critical structures. Step-and-shoot intensity-modulated radiation treatment (IMRT) plans were generated for all Unity patients with a dose grid of 3 mm and a statistical uncertainty of < 1% per plan. Results: A total of 15 pediatric and AYA patients have been treated with median age of 13 years (range: 6 mos - 27 yrs). Seven patients were <10 yo. The clinical applications of MRgRT included Wilms tumor with unresectable IVC thrombus (n=1), Ewing sarcoma (primary and metastatic, n=3), recurrent diffuse intrinsic pontine glioma (DIPG, n=2), nasopharyngeal carcinoma (n=1), clival chordoma (n=1), primitive neuroectodermal tumor of the pancreas (n=1), recurrent gluteo-sacral germ cell tumor (n=1), C-spine ependymoma (n=1), and posterior fossa ependymoma (n=1). Two children required general anesthesia. One AYA patient could not complete the MRgRT course due to tumor-related pain exacerbated by longer treatment times. Two AYA patients experienced anxiety related to treatment on the MRL, one of which required daily Ativan. No patient experienced treatment interruptions or unexpected toxicity. Conclusion: MRgRT was well-tolerated by pediatric and AYA patients. There was no increased use of anesthesia outside of our usual practice. Dosimetric advantages were seen for patients with tumors in critical locations such as adjacent to or involving optic structures, stomach, kidney, bowel, and heart.

Reduced blood flow by laser speckle flowgraphy after 125I-plaque brachytherapy for uveal melanoma.

BACKGROUND: To determine whether reductions in retinal and choroidal blood flow measured by laser speckle flowgraphy are detected after 125I-plaque brachytherapy for uveal melanoma. METHODS: In a cross-sectional study, retinal and choroidal blood flow were measured using laser speckle flowgraphy in 25 patients after treatment with 125I-plaque brachytherapy for uveal melanoma. Flow was analyzed in the peripapillary region by mean blur rate as well as in the entire image area with a novel superpixel-based method. Relationships between measures were determined by Spearman correlation. RESULTS: Significant decreases in laser speckle blood flow were observed in both the retinal and choroidal vascular beds of irradiated, but not fellow, eyes. Overall, 24 of 25 patients had decreased blood flow compared to their fellow eye, including 5 of the 6 patients imaged within the first 6 months following brachytherapy. A significant negative correlation between blood flow and time from therapy was present. CONCLUSIONS: Decreases in retinal and choroidal blood flow by laser speckle flowgraphy were detected within the first 6 months following brachytherapy. Reduced retinal and choroidal blood flow may be an early indicator of microangiographic response to radiation therapy.

Pharmacological ascorbate improves the response to platinum-based chemotherapy in advanced stage non-small cell lung cancer.

PURPOSE: Platinum-based chemotherapy with or without immunotherapy is the mainstay of treatment for advanced stage non-small cell lung cancer (NSCLC) lacking a molecular driver alteration. Pre-clinical studies have reported that pharmacological ascorbate (P-AscH-) enhances NSCLC response to platinum-based therapy. We conducted a phase II clinical trial combining P-AscH- with carboplatin-paclitaxel chemotherapy. EXPERIMENTAL DESIGN: Chemotherapy naïve advanced stage NSCLC patients received 75 g ascorbate twice per week intravenously with carboplatin and paclitaxel every three weeks for four cycles. The primary endpoint was to improve tumor response per Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 compared to the historical control of 20%. The trial was conducted as an optimal Simon's two-stage design. Blood samples were collected for exploratory analyses. RESULTS: The study enrolled 38 patients and met its primary endpoint with an objective response rate of 34.2% (p = 0.03). All were confirmed partial responses (cPR). The disease control rate was 84.2% (stable disease + cPR). Median progression-free and overall survival were 5.7 months and 12.8 months, respectively. Treatment-related adverse events (TRAE) included one grade 5 (neutropenic fever) and five grade 4 events (cytopenias). Cytokine and chemokine data suggest that the combination elicits an immune response. Immunophenotyping of peripheral blood mononuclear cells demonstrated an increase in effector CD8 T-cells in patients with a progression-free survival (PFS) ≥ 6 months. CONCLUSIONS: The addition of P-AscH- to platinum-based chemotherapy improved tumor response in advanced stage NSCLC. P-AscH- appears to alter the host immune response and needs further investigation as a potential adjuvant to immunotherapy.

Clinical Implementational and Site-Specific Workflows for a 1.5T MR-Linac.

MR-guided adaptive radiotherapy (MRgART) provides opportunities to benefit patients through enhanced use of advanced imaging during treatment for many patients with various cancer treatment sites. This novel technology presents many new challenges which vary based on anatomic treatment location, technique, and potential changes of both tumor and normal tissue during treatment. When introducing new treatment sites, considerations regarding appropriate patient selection, treatment planning, immobilization, and plan-adaption criteria must be thoroughly explored to ensure adequate treatments are performed. This paper presents an institution's experience in developing a MRgART program for a 1.5T MR-linac for the first 234 patients. The paper suggests practical treatment workflows and considerations for treating with MRgART at different anatomical sites, including imaging guidelines, patient immobilization, adaptive workflows, and utilization of bolus.

Graded Prognostic Assessment (GPA) for Patients With Lung Cancer and Brain Metastases: Initial Report of the Small Cell Lung Cancer GPA and Update of the Non-Small Cell Lung Cancer GPA Including the Effect of Programmed Death Ligand 1 and Other Prognostic Factors.

PURPOSE: Patients with lung cancer and brain metastases represent a markedly heterogeneous population. Accurate prognosis is essential to optimally individualize care. In prior publications, we described the graded prognostic assessment (GPA), but a GPA for patients with small cell lung cancer (SCLC) has never been reported, and in non-small cell lung cancer (NSCLC), the effect of programmed death ligand 1 (PD-L1) was unknown. The 3-fold purpose of this work is to provide the initial report of an SCLC GPA, to evaluate the effect of PD-L1 on survival in patients with NSCLC, and to update the Lung GPA accordingly. METHODS AND MATERIALS: A multivariable analysis of prognostic factors and treatments associated with survival was performed on 4183 patients with lung cancer (3002 adenocarcinoma, 611 nonadenocarcinoma, 570 SCLC) with newly diagnosed brain metastases between January 1, 2015, and December 31, 2020, using a multi-institutional retrospective database. Significant variables were used to update the Lung GPA. RESULTS: Overall median survival for lung adenocarcinoma, SCLC, and nonadenocarcinoma was 17, 10, and 8 months, respectively, but varied widely by GPA from 2 to 52 months. In SCLC, the significant prognostic factors were age, performance status, extracranial metastases, and number of brain metastases. In NSCLC, the distribution of molecular markers among patients with lung adenocarcinoma and known primary tumor molecular status revealed alterations/expression in PD-L1 50% to 100%, PD-L1 1% to 49%, epidermal growth factor receptor, and anaplastic lymphoma kinase in 32%, 31%, 30%, and 7%, respectively. Median survival of patients with lung adenocarcinoma and brain metastases with 0, 1% to 49%, and ≥50% PD-L1 expression was 17, 19, and 24 months, respectively (P < .01), confirming PD-L1 is a prognostic factor. Previously identified prognostic factors for NSCLC (epidermal growth factor receptor and anaplastic lymphoma kinase status, performance status, age, number of brain metastases, and extracranial metastases) were reaffirmed. These factors were incorporated into the updated Lung GPA with robust separation between subgroups for all histologies. CONCLUSIONS: Survival for patients with lung cancer and brain metastases has improved but varies widely. The initial report of a GPA for SCLC is presented. For patients with NSCLC-adenocarcinoma and brain metastases, PD-L1 is a newly identified significant prognostic factor, and the previously identified factors were reaffirmed. The updated indices establish unique criteria for SCLC, NSCLC-nonadenocarcinoma, and NSCLC-adenocarcinoma (incorporating PD-L1). The updated Lung GPA, available for free at brainmetgpa.com, provides an accurate tool to estimate survival, individualize treatment, and stratify clinical trials.