Assessment of image quality and dose calculation accuracy on kV CBCT, MV CBCT, and MV CT images for urgent palliative radiotherapy treatments.

A clinical workflow was developed for urgent palliative radiotherapy treatments that integrates patient simulation, planning, quality assurance, and treatment in one 30-minute session. This has been successfully tested and implemented clinically on a linac with MV CBCT capabilities. To make this approach available to all clinics equipped with common imaging systems, dose calculation accuracy based on treatment sites was assessed for other imaging units. We evaluated the feasibility of palliative treatment planning using on-board imaging with respect to image quality and technical challenges. The purpose was to test multiple systems using their commercial setup, disregarding any additional in-house development. kV CT, kV CBCT, MV CBCT, and MV CT images of water and anthropomorphic phantoms were acquired on five different imaging units (Philips MX8000 CT Scanner, and Varian TrueBeam, Elekta VersaHD, Siemens Artiste, and Accuray Tomotherapy linacs). Image quality (noise, contrast, uniformity, spatial resolution) was evaluated and compared across all machines. Using individual image value to density calibrations, dose calculation accuracies for simple treatment plans were assessed for the same phantom images. Finally, image artifacts on clinical patient images were evaluated and compared among the machines. Image contrast to visualize bony anatomy was sufficient on all machines. Despite a high noise level and low contrast, MV CT images provided the most accurate treatment plans relative to kV CT-based planning. Spatial resolution was poorest for MV CBCT, but did not limit the visualization of small anatomical structures. A comparison of treatment plans showed that monitor units calculated based on a prescription point were within 5% difference relative to kV CT-based plans for all machines and all studied treatment sites (brain, neck, and pelvis). Local dose differences >5% were found near the phantom edges. The gamma index for 3%/3 mm criteria was ≥95% in most cases. Best dose calculation results were obtained when the treatment isocenter was near the image isocenter for all machines. A large field of view and immediate image export to the treatment planning system were essential for a smooth workflow and were not provided on all devices. Based on this phantom study, image quality of the studied kV CBCT, MV CBCT, and MV CT on-board imaging devices was sufficient for treatment planning in all tested cases. Treatment plans provided dose calculation accuracies within an acceptable range for simple, urgently planned palliative treatments. However, dose calculation accuracy was compromised towards the edges of an image. Feasibility for clinical implementation should be assessed separately and may be complicated by machine specific features. Image artifacts in patient images and the effect on dose calculation accuracy should be assessed in a separate, machine-specific study. PACS number(s): 87.55.D-, 87.57.C-, 87.57.Q

Phase I study of dose escalation to dominant intraprostatic lesions using high-dose-rate brachytherapy.

PurposeRadiation dose escalation for prostate cancer improves biochemical control but is limited by toxicity. Magnetic resonance spectroscopic imaging (MRSI) can define dominant intraprostatic lesions (DIL). This phase I study evaluated dose escalation to MRSI-defined DIL using high-dose-rate (HDR) brachytherapy.Material and methodsEnrollment was closed early due to low accrual. Ten patients with prostate cancer (T2a-3b, Gleason 6-9, PSA < 20) underwent pre-treatment MRSI, and eight patients had one to three DIL identified. The eight enrolled patients received external beam radiation therapy to 45 Gy and HDR brachytherapy boost to the prostate of 19 Gy in 2 fractions. MRSI images were registered to planning CT images and DIL dose-escalated up to 150% of prescription dose while maintaining normal tissue constraints. The primary endpoint was genitourinary (GU) toxicity.ResultsThe median total DIL volume was 1.31 ml (range, 0.67-6.33 ml). Median DIL boost was 130% of prescription dose (range, 110-150%). Median urethra V120 was 0.15 ml (range, 0-0.4 ml) and median rectum V75 was 0.74 ml (range, 0.1-1.0 ml). Three patients had acute grade 2 GU toxicity, and two patients had late grade 2 GU toxicity. No patients had grade 2 or higher gastrointestinal toxicity, and no grade 3 or higher toxicities were noted. There were no biochemical failures with median follow-up of 4.9 years (range, 2-8.5 years).ConclusionsDose escalation to MRSI-defined DIL is feasible. Toxicity was low but incompletely assessed due to limited patients' enrollment

Predicting Adverse Radiation Effects in Brain Tumors After Stereotactic Radiotherapy With Deep Learning and Handcrafted Radiomics

Introduction There is a cumulative risk of 20-40% of developing brain metastases (BM) in solid cancers. Stereotactic radiotherapy (SRT) enables the application of high focal doses of radiation to a volume and is often used for BM treatment. However, SRT can cause adverse radiation effects (ARE), such as radiation necrosis, which sometimes cause irreversible damage to the brain. It is therefore of clinical interest to identify patients at a high risk of developing ARE. We hypothesized that models trained with radiomics features, deep learning (DL) features, and patient characteristics or their combination can predict ARE risk in patients with BM before SRT. Methods Gadolinium-enhanced T1-weighted MRIs and characteristics from patients treated with SRT for BM were collected for a training and testing cohort (N = 1,404) and a validation cohort (N = 237) from a separate institute. From each lesion in the training set, radiomics features were extracted and used to train an extreme gradient boosting (XGBoost) model. A DL model was trained on the same cohort to make a separate prediction and to extract the last layer of features. Different models using XGBoost were built using only radiomics features, DL features, and patient characteristics or a combination of them. Evaluation was performed using the area under the curve (AUC) of the receiver operating characteristic curve on the external dataset. Predictions for individual lesions and per patient developing ARE were investigated. Results The best-performing XGBoost model on a lesion level was trained on a combination of radiomics features and DL features (AUC of 0.71 and recall of 0.80). On a patient level, a combination of radiomics features, DL features, and patient characteristics obtained the best performance (AUC of 0.72 and recall of 0.84). The DL model achieved an AUC of 0.64 and recall of 0.85 per lesion and an AUC of 0.70 and recall of 0.60 per patient. Conclusion Machine learning models built on radiomics features and DL features extracted from BM combined with patient characteristics show potential to predict ARE at the patient and lesion levels. These models could be used in clinical decision making, informing patients on their risk of ARE and allowing physicians to opt for different therapies

Histopathologic findings in malignant peripheral nerve sheath tumor predict response to radiotherapy and overall survival

BACKGROUND: Malignant peripheral nerve sheath tumor (MPNST) is an aggressive and poorly understood malignant neoplasm. Even in the setting of multimodal therapy, the clinical course of MPNST is frequently marked by metastatic conversion and poor overall prognosis, with optimal treatment paradigms for this rare tumor unknown. METHODS: We reviewed the medical records and histopathology of 54 consecutive patients who were treated at University of California San Francisco between 1990 and 2018. RESULTS: Our cohort consisted of 24 male and 30 female patients (median age 38 years). Fédération Nationale des Centres de Lutte Contre Le Cancer (FNCLCC) sarcoma grading criteria segregated patients into groups with differences in overall survival (OS) ( CONCLUSIONS: Our results lend support to the FNCLCC sarcoma grading criteria as a prognostic scheme for MPNST, although few cases of grade 1 were included. Further, we identify increased Ki-67 labeling as a strong predictor of poor OS from MPNST. Finally, we identify a subset of MPNSTs with a predictive immunohistochemical profile that has improved local control with adjuvant radiotherapy. These data provide insights into the grading and therapy for patients with MPNST, although further studies are needed for independent validation

T2 FLAIR hyperintensity volume Is associated with cognitive function and quality of life in clinically stable patients with lower grade gliomas

Survival outcomes for patients with lower grade gliomas (LrGG) continue to improve. However, damage caused both by tumor growth and by the consequences of treatment often leads to significantly impaired cognitive function and quality of life (QoL). While neuropsychological testing is not routine, serial clinical MRIs are standard of care for patients with LrGG. Thus, having a greater understanding of MRI indicators of cognitive and QoL impairment risk could be beneficial to patients and clinicians. In this work we sought to test the hypothesis that in clinically stable LrGG patients, T2 FLAIR hyperintensity volumes at the time of cognitive assessment are associated with impairments of cognitive function and QoL and could be used to help identify patients for cognitive and QoL assessments and interventions. We performed anatomical MR imaging, cognitive testing and QoL assessments cross-sectionally in 30 clinically stable grade 2 and 3 glioma patients with subjective cognitive concerns who were 6 or more months post-treatment. Larger post-surgical T2 FLAIR volume at testing was significantly associated with lower cognitive performance, while pre-surgical tumor volume was not. Older patients had lower cognitive performance than younger patients, even after accounting for normal age-related declines in performance. Patients with Astrocytoma, IDH mutant LrGGs were more likely to show lower cognitive performance than patients with Oligodendroglioma, IDH mutant 1p19q co-deleted LrGGs. Previous treatment with combined radiation and chemotherapy was associated with poorer self-reported QoL, including self-reported cognitive function. This study demonstrates the importance of appreciating that LrGG patients may experience impairments in cognitive function and QoL over their disease course, including during periods of otherwise sustained clinical stability. Imaging factors can be helpful in identifying vulnerable patients who would benefit from cognitive assessment and rehabilitation

The University of California San Francisco, Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) dataset is a public, clinical, multimodal brain MRI dataset consisting of 560 brain MRIs from 412 patients with expert annotations of 5136 brain metastases. Data consists of registered and skull stripped T1 post-contrast, T1 pre-contrast, FLAIR and subtraction (T1 pre-contrast - T1 post-contrast) images and voxelwise segmentations of enhancing brain metastases in NifTI format. The dataset also includes patient demographics, surgical status and primary cancer types. The UCSF-BSMR has been made publicly available in the hopes that researchers will use these data to push the boundaries of AI applications for brain metastases.Comment: 15 pages, 2 tables, 2 figure

Expert consensus on re-irradiation for current glioma

Source at http://doi.org/10.1186/s13014-017-0928-3Purpose:To investigate radiation oncologists’ opinions on important considerations to offering re-irradiation (re-RT) as a treatment option for recurrent glioma.Materials and methods:A survey was conducted with 13 radiation oncologists involved in the care of central nervous system tumor patients. The survey was comprised of 49 questions divided into 2 domains: a demographic section (10 questions) and a case section (5 re-RT cases with 5 to 6 questions representing one or several re-RT treatment dilemmas as may be encountered in the clinic). Respondents were asked to rate the relevance of various factors to offering re-RT, respond to the cases with a decision to offer re-RT vs. not, volume to be treated, margins to be employed, dose/fractionation suggested and any additional comments with respect to rationale in each scenario.Results:Sixty nine percent of responders have been practicing for greater than 10 years and 61% have re-RT 20 to 100 patients to date, with 54% seeing 2–5 re-RT cases per month and retreating 1–2 patients per month. Recurrent tumor volume, time since previous radiation therapy, previously administered dose to organs at risk and patient performance status were rated by the majority of responders (85%, 92%, 77%, and 69% respectively) as extremely relevant or very relevant to offering re-RT as an option.Conclusion:The experts’ practice of re-RT is still heterogeneous, reflecting the paucity of high-quality prospective data available for decision-making. Nevertheless, practicing radiation oncologists can support own decisions by referring to the cases found suitable for re-RT in this survey

Estimating survival in patients with gastrointestinal cancers and brain metastases: An update of the graded prognostic assessment for gastrointestinal cancers (GI-GPA).

BackgroundPatients with gastrointestinal cancers and brain metastases (BM) represent a unique and heterogeneous population. Our group previously published the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) for patients with GI cancers (GI-GPA) (1985-2007, n = 209). The purpose of this study is to update the GI-GPA based on a larger contemporary database.MethodsAn IRB-approved consortium database analysis was performed using a multi-institutional (18), multi-national (3) cohort of 792 patients with gastrointestinal (GI) cancers, with newly-diagnosed BM diagnosed between 1/1/2006 and 12/31/2017. Survival was measured from date of first treatment for BM. Multiple Cox regression was used to select and weight prognostic factors in proportion to their hazard ratios. These factors were incorporated into the updated GI-GPA.ResultsMedian survival (MS) varied widely by primary site and other prognostic factors. Four significant factors (KPS, age, extracranial metastases and number of BM) were used to formulate the updated GI-GPA. Overall MS for this cohort remains poor; 8 months. MS by GPA was 3, 7, 11 and 17 months for GPA 0-1, 1.5-2, 2.5-3.0 and 3.5-4.0, respectively. >30% present in the worst prognostic group (GI-GPA of ≤1.0).ConclusionsBrain metastases are not uncommon in GI cancer patients and MS varies widely among them. This updated GI-GPA index improves our ability to estimate survival for these patients and will be useful for therapy selection, end-of-life decision-making and stratification for future clinical trials. A user-friendly, free, on-line app to calculate the GPA score and estimate survival for an individual patient is available at brainmetgpa.com

Clinical outcome and prognostic factors for central neurocytoma: twenty year institutional experience

Central neurocytomas are uncommon intraventricular neoplasms whose optimal management remains controversial due to their rarity. We assessed outcomes for a historical cohort of neurocytoma patients and evaluated effects of tumor atypia, size, resection extent, and adjuvant radiotherapy. Progression-free survival (PFS) was measured by Kaplan-Meier and Cox proportional hazards methods. A total of 28 patients (15 males, 13 females) were treated between 1995 and 2014, with a median age at diagnosis of 26 years (range 5-61). Median follow-up was 62.2 months and 3 patients were lost to follow-up postoperatively. Thirteen patients experienced recurrent/progressive disease and 2-year PFS was 75% (95% CI 53-88%). Two-year PFS was 48% for MIB-1 labeling >4% versus 90% for ≤4% (HR 5.4, CI 2.2-27.8, p = 0.0026). Nine patients (32%) had gross total resections (GTR) and 19 (68%) had subtotal resections (STR). PFS for >80% resection was 83 versus 67% for ≤80% resection (HR 0.67, CI 0.23-2.0, p = 0.47). Three STR patients (16%) received adjuvant radiation which significantly improved overall PFS (p = 0.049). Estimated 5-year PFS was 67% for STR with radiotherapy versus 53% for STR without radiotherapy. Salvage therapy regimens were diverse and resulted in stable disease for 54% of patients and additional progression for 38 %. Two patients with neuropathology-confirmed atypical neurocytomas died at 4.3 and 113.4 months after initial surgery. For central neurocytomas, MIB-1 labeling index >4% is predictive of poorer outcome and our data suggest that adjuvant radiotherapy after STR may improve PFS. Most patients requiring salvage therapy will be stabilized and multiple modalities can be effectively utilized