Integrating Overall Survival and Tumor Control Probability Models to Predict Local Progression After Brain Metastasis Radiosurgery.

Purpose: Stereotactic radiosurgery (SRS) for brain metastases is frequently prescribed to the maximum tolerated dose to minimize the probability of local progression. However, many patients die from extracranial disease prior to local progression and may not require maximally aggressive treatment. Recently, improvements in models of SRS tumor control probability (TCP) and overall survival (OS) have been made. We predicted that by combining models of OS and TCP, we could better predict the true risk of local progression after SRS than by using TCP modeling alone. Methods and Materials: Records of patients undergoing SRS at a single institution were reviewed retrospectively. Using established TCP and OS models, for each patient, the probability of 1-year survival [p(OS)] was calculated, as was the probability of 1-year local progression [p(LP)]) for each treated lesion. Joint-probability was used to combine the models [p(LP,OS)=p(LP)*p(OS)]. Analyses were conducted at the individual metastasis and whole-patient levels. Fine-Gray regression was used to model p(LP) or p(LP,OS) on the risk of local progression after SRS, with death as a competing risk. Results: At the patient level, 1-year local progression was 0.08 (95% CI, 0.03-0.15), median p(LP,OS) was 0.13 (95% CI, 0.07-0.2), and median p(LP) was 0.29 (95% CI, 0.22-0.38). At the metastasis level, 1-year local progression was 0.02 (95% CI, 0.01-0.04), median p(LP,OS) was 0.05 (95% CI, 0.02-0.07), and median p(LP) was 0.10 (95% CI, 0.07-0.13). p(LP,OS) was found to be significantly associated with the risk of local progression at the patient level (P = .048) and metastasis level (P = .007); however, p(LP) was not (P = .16 and P = .28, respectively). Conclusions: Simultaneous modeling of OS and TCP more accurately predicted local progression than TCP modeling alone. Better understanding which patients with brain metastases are at risk of local progression after SRS may help personalize treatment to minimize risk without sacrificing efficacy.

Experiences of Older Aboriginal People in Navigating Transport Systems in an Urban Setting: An Indigenous Perspective on Transport Access, a Social Determinant of Health.

BACKGROUND: In Australia, Aboriginal people are underserved by the transport system and are less able to easily get to places they need to go than others. This is a part of a larger pattern of exclusion and inequity for Aboriginal people which affects their health, wellbeing, and social participation. Guided by a decolonising framework, this research explored how older Aboriginal people, whose pivotal roles in their families and communities require their mobility, experience the transportation system, providing an Indigenous-centred view of the accessibility of transportation options in society. METHODS: Interviews drawing from the yarning technique were conducted with ten older Aboriginal people living in Greater Western Sydney and analysed qualitatively. RESULTS: In addition to the cognitive labour required to decipher the rules of the transport system and organise commitments to match the scheduling of transport services, older Aboriginal people in this study experienced stigmatising attitudes and condescending treatment from service professionals and the public when traveling. CONCLUSIONS: This study suggests three potential ways that the current trajectory that underserves older Aboriginal people could be disrupted, relating to service design, the diversity and inclusion agenda, and the social determinants of Indigenous health.

Lymphatic-preserving treatment sequencing with immune checkpoint inhibition unleashes cDC1-dependent antitumor immunity in HNSCC.

Despite the promise of immune checkpoint inhibition (ICI), therapeutic responses remain limited. This raises the possibility that standard of care treatments delivered in concert may compromise the tumor response. To address this, we employ tobacco-signature head and neck squamous cell carcinoma murine models in which we map tumor-draining lymphatics and develop models for regional lymphablation with surgery or radiation. We find that lymphablation eliminates the tumor ICI response, worsening overall survival and repolarizing the tumor- and peripheral-immune compartments. Mechanistically, within tumor-draining lymphatics, we observe an upregulation of conventional type I dendritic cells and type I interferon signaling and show that both are necessary for the ICI response and lost with lymphablation. Ultimately, we provide a mechanistic understanding of how standard oncologic therapies targeting regional lymphatics impact the tumor response to immune-oncology therapy in order to define rational, lymphatic-preserving treatment sequences that mobilize systemic antitumor immunity, achieve optimal tumor responses, control regional metastatic disease, and confer durable antitumor immunity.

Knowledge-based three-dimensional dose prediction for tandem-and-ovoid brachytherapy.

PURPOSE: The purpose of this work was to develop a knowledge-based dose prediction system using a convolution neural network (CNN) for cervical brachytherapy treatments with a tandem-and-ovoid applicator. METHODS: A 3D U-NET CNN was utilized to make voxel-wise dose predictions based on organ-at-risk (OAR), high-risk clinical target volume (HRCTV), and possible source location geometry. The model comprised 395 previously treated cases: training (273), validation (61), test (61). To assess voxel prediction accuracy, we evaluated dose differences in all cohorts across the dose range of 20-130% of prescription, mean (SD) and standard deviation (σ), as well as isodose dice similarity coefficients for clinical and/or predicted dose distributions. We examined discrete Dose-Volume Histogram (DVH) metrics utilized for brachytherapy plan quality assessment (HRCTV D90%; bladder, rectum, and sigmoid D2cc) with ΔDx=Dx,actual-Dx,predicted mean, standard deviation, and Pearson correlation coefficient further quantifying model performance. RESULTS: Ranges of voxel-wise dose difference accuracy (δD¯±σ) for 20-130% dose interval in training (test) sets ranged from [-0.5% ± 2.0% to +2.0% ± 14.0%] ([-0.1% ± 4.0% to +4.0% ± 26.0%]) in all voxels, [-1.7% ± 5.1% to -3.5% ± 12.8%] ([-2.9% ± 4.8% to -2.6% ± 18.9%]) in HRCTV, [-0.02% ± 2.40% to +3.2% ± 12.0%] ([-2.5% ± 3.6% to +0.8% ± 12.7%]) in bladder, [-0.7% ± 2.4% to +15.5% ± 11.0%] ([-0.9% ± 3.2% to +27.8% ± 11.6%]) in rectum, and [-0.7% ± 2.3% to +10.7% ± 15.0%] ([-0.4% ± 3.0% to +18.4% ± 11.4%]) in sigmoid. Isodose dice similarity coefficients ranged from [0.96,0.91] for training and [0.94,0.87] for test cohorts. Relative DVH metric prediction in the training (test) set were HRCTV ΔD¯90±σΔD = -0.19 ± 0.55Gy (-0.09 ± 0.67 Gy), bladder ΔD¯2cc±σΔD = -0.06 ± 0.54Gy (-0.17 ± 0.67 Gy), rectum ΔD¯2cc±σΔD= -0.03 ± 0.36Gy (-0.04 ± 0.46 Gy), and sigmoid ΔD¯2cc±σΔD = -0.01 ± 0.34Gy (0.00 ± 0.44 Gy). CONCLUSIONS: A 3D knowledge-based dose predictions provide voxel-level and DVH metric estimates that could be used for treatment plan quality control and data-driven plan guidance.

Controversies in Lung Cancer: Heterogeneity in Treatment Recommendations for Stage III NSCLC According to Disease Burden and Oncogenic Driver Alterations.

INTRODUCTION: Therapeutic options for stage III non-small-cell lung cancer (NSCLC) consist of definitive chemoradiation, surgery combined with neoadjuvant/adjuvant chemotherapy, and trimodality therapy. More recently, biologically driven systemic therapy options, including immunotherapy and targeted therapy, have become increasingly available. METHODS: A customized, case-based survey was designed and distributed to members of the International Association for the Study of Lung Cancer (IASLC) to determine practice habits and preferences for NSCLC patients with stage III disease and N2 to N3 nodal involvement. RESULTS: Data were compiled from 87 respondents from 31 countries, including medical oncologists (49%), surgical oncologists (24%), and radiation oncologists (21%). Definitive chemoradiation was more likely to be recommended for stage IIIC (98.2%) or stage IIIB (75.8%) scenarios compared with stage IIIA (59.6%) without actionable driver alterations (P < .0001 and .0003, respectively); and chemoradiation was more likely for stage IIIB (57.7%) compared to stage IIIA (39.9%) with actionable EGFR/ALK alterations (P = .008). Surgery was more likely to be recommended in the presence of an actionable alteration (38.7% vs. 19%, P < .0001). Surgeons were more likely than medical oncologists to recommend surgical approaches in scenarios without actionable alterations (25.6% vs. 11.2%, P < .0001) or with actionable alterations (57.5% vs. 31.1%, P = .0001). DISCUSSION: The dominant recommended strategy for stage III NSCLC was chemoradiation, although respondents were more likely to recommend surgical approaches in the presence of actionable alterations. Despite the lack of reported clinical trial data, many IASLC lung cancer experts favored targeted therapy when actionable driver alterations were present.

Ironbark: Developing a healthy community program for older Aboriginal people.

ISSUE ADDRESSED: Programs by, with and for Aboriginal older people must be culturally safe and relevant. Successful elements include being Aboriginal specific and group based. Co-design with Aboriginal people and stakeholders is essential. We describe the co-design process of developing the Ironbark: Healthy Community program. METHODS: Aboriginal ways of knowing, being and doing and yarning conversational methods guided the development process, during 2018. A desktop review provided details of current group characteristics and key community stakeholders. Stakeholder engagement regarding views about group operations, participants and benefits also occurred. Aboriginal Elders views of their groups were gathered through yarning circles in New South Wales (NSW). Grounded theory approach was used to ascertain key themes. RESULTS: Initial engagement occurred with 13 different community stakeholders and organisations in three Australian states (NSW, South Australia (SA), Western Australia (WA)). Three yarning circles occurred with Elders from urban (N = 10), regional coastal (N = 10) and regional country (N = 4) groups. Six key themes were organised in three groups according to an Aboriginal ontology. 1. Knowing: groups provide opportunities to share knowledge and connect socially. Adequate program resourcing and sustainability are valued. 2. Being: groups strengthen culture, providing important social, emotional and other forms of support to age well. 3. Doing: previous program experiences inform perceptions for new program operations. Group venues and operational aspects should be culturally safe, acknowledging diversity among Elders, their preferences and community control. Themes were used to develop the program and its resource manual that were finalised with stakeholders, including steering committee approval. CONCLUSIONS: Stakeholder feedback at multiple stages and Aboriginal Elders' perspectives resulted in a new co-designed community program involving weekly yarning circles and social activities. So what?: Co-design, guided by Aboriginal ways of knowing, being and doing, can develop programs relevant for Aboriginal people.

Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach.

Stereotactic radiosurgery planning for cerebral arteriovenous malformations (AVM) is complicated by the variability in appearance of an AVM nidus across different imaging modalities. We developed a deep learning approach to automatically segment cerebrovascular-anatomical maps from multiple high-resolution magnetic resonance imaging/angiography (MRI/MRA) sequences in AVM patients, with the goal of facilitating target delineation. Twenty-three AVM patients who were evaluated for radiosurgery and underwent multi-parametric MRI/MRA were included. A hybrid semi-automated and manual approach was used to label MRI/MRAs with arteries, veins, brain parenchyma, cerebral spinal fluid (CSF), and embolized vessels. Next, these labels were used to train a convolutional neural network to perform this task. Imaging from 17 patients (6362 image slices) was used for training, and 6 patients (1224 slices) for validation. Performance was evaluated by Dice Similarity Coefficient (DSC). Classification performance was good for arteries, veins, brain parenchyma, and CSF, with DSCs of 0.86, 0.91, 0.98, and 0.91, respectively in the validation image set. Performance was lower for embolized vessels, with a DSC of 0.75. This demonstrates the proof of principle that accurate, high-resolution cerebrovascular-anatomical maps can be generated from multiparametric MRI/MRA. Clinical validation of their utility in radiosurgery planning is warranted.

Correcting B0 inhomogeneity-induced distortions in whole-body diffusion MRI of bone.

Diffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy. Whole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T2-weighted images were annotated. Changes in distance between DWI- and T2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T2-weighted images of bone metastases after distortion correction were calculated. Distortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p < 10-20). On average (± SD), participants' largest error reduction was 11.8 mm (± 3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI 5.0-7.2); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p < 10-12). These findings support the use of distortion correction techniques to improve localization of bone on DWI.

Improved Prognosis of Treatment Failure in Cervical Cancer with Nontumor PET/CT Radiomics.

Radiomics has been applied to predict recurrence in several disease sites, but current approaches are typically restricted to analyzing tumor features, neglecting nontumor information in the rest of the body. The purpose of this work was to develop and validate a model incorporating nontumor radiomics, including whole-body features, to predict treatment outcomes in patients with previously untreated locoregionally advanced cervical cancer. Methods: We analyzed 127 cervical cancer patients treated definitively with chemoradiotherapy and intracavitary brachytherapy. All patients underwent pretreatment whole-body 18F-FDG PET/CT. To quantify effects due to the tumor itself, the gross tumor volume (GTV) was directly contoured on the PET/CT image. Meanwhile, to quantify effects arising from the rest of the body, the planning target volume (PTV) was deformably registered from each planning CT to the PET/CT scan, and a semiautomated approach combining seed-growing and manual contour review generated whole-body muscle, bone, and fat segmentations on each PET/CT image. A total of 965 radiomic features were extracted for GTV, PTV, muscle, bone, and fat. Ninety-five patients were used to train a Cox model of disease recurrence including both radiomic and clinical features (age, stage, tumor grade, histology, and baseline complete blood cell counts), using bagging and split-sample-validation for feature reduction and model selection. To further avoid overfitting, the resulting models were tested for generalization on the remaining 32 patients, by calculating a risk score based on Cox regression and evaluating the c-index (c-index > 0.5 indicates predictive power). Results: Optimal performance was seen in a Cox model including 1 clinical biomarker (whether or not a tumor was stage III-IVA), 2 GTV radiomic biomarkers (PET gray-level size-zone matrix small area low gray level emphasis and zone entropy), 1 PTV radiomic biomarker (major axis length), and 1 whole-body radiomic biomarker (CT bone root mean square). In particular, stratification into high- and low-risk groups, based on the linear risk score from this Cox model, resulted in a hazard ratio of 0.019 (95% CI, 0.004, 0.082), an improvement over stratification based on clinical stage alone, which had a hazard ratio of 0.36 (95% CI, 0.16, 0.83). Conclusion: Incorporating nontumor radiomic biomarkers can improve the performance of prognostic models compared with using only clinical and tumor radiomic biomarkers. Future work should look to further test these models in larger, multiinstitutional cohorts.

Evaluation of dose differences between intracavitary applicators for cervical brachytherapy using knowledge-based models.

PURPOSE: Currently, there is a lack of patient-specific tools to guide brachytherapy planning and applicator choice for cervical cancer. The purpose of this study is to evaluate the accuracy of organ-at-risk (OAR) dose predictions using knowledge-based intracavitary models, and the use of these models and clinical data to determine the dosimetric differences of tandem-and-ring (T&R) and tandem-and-ovoids (T&O) applicators. MATERIALS AND METHODS: Knowledge-based models, which predict organ D2cc, were trained on 77/75 cases and validated on 32/38 for T&R/T&O applicators. Model performance was quantified using ΔD2cc=D2cc,actual-D2cc,predicted, with standard deviation (σ(ΔD2cc)) representing precision. Model-predicted applicator dose differences were determined by applying T&O models to T&R cases, and vice versa, and compared to clinically-achieved D2cc differences. Applicator differences were assessed using a Student's t-test (p < 0.05 significant). RESULTS: Validation T&O/T&R model precision was 0.65/0.55 Gy, 0.55/0.38 Gy, and 0.43/0.60 Gy for bladder, rectum and sigmoid, respectively, and similar to training. When applying T&O/T&R models to T&R/T&O cases, bladder, rectum and sigmoid D2cc values in EQD2 were on average 5.69/2.62 Gy, 7.31/6.15 Gy and 3.65/0.69 Gy lower for T&R, with similar HRCTV volume and coverage. Clinical data also showed lower T&R OAR doses, with mean EQD2 D2cc deviations of 0.61 Gy, 7.96 Gy (p < 0.01) and 5.86 Gy (p < 0.01) for bladder, rectum and sigmoid. CONCLUSIONS: Accurate knowledge-based dose prediction models were developed for two common intracavitary applicators. These models could be beneficial for standardizing and improving the quality of brachytherapy plans. Both models and clinical data suggest that significant OAR sparing can be achieved with T&R over T&O applicators, particularly for the rectum.

Defining the Role of Immunotherapy in the Curative Treatment of Locoregionally Advanced Head and Neck Cancer: Promises, Challenges, and Opportunities.

Recent advancements in the development of immunotherapies have raised the hope for patients with locally-advanced HNSCC (LA-HNSCC) to achieve improved oncologic outcomes without the heavy burden of treatment-related morbidity. While there are several ongoing late phase clinical trials that seek to determine whether immunotherapy can be effectively employed in the definitive setting, initial results from concurrent immuno-radiotherapy therapy trials have not shown strong evidence of benefit. Encouragingly, evidence from preclinical studies and early-phase neoadjuvant studies have begun to show potential pathways forward, with therapeutic combinations and sequences that intentionally spare tumor draining lymphatics in order to maximize the synergy between definitive local therapy and immunotherapy. The intent of this review is to summarize the scientific rationale and current clinical evidence for employing immunotherapy for LA-HNSCC as well as the ongoing efforts and challenges to determine how to optimally deliver and sequence immunotherapy alongside traditional therapeutics. In both the preclinical and clinical settings, we will discuss the application of immunotherapies to both surgical and radiotherapeutic management of HNSCC.

Knowledge-based dose prediction models to inform gynecologic brachytherapy needle supplementation for locally advanced cervical cancer.

PURPOSE: The use of interstitial needles, combined with intracavitary applicators, enables customized dose distributions and is beneficial for complex cases, but increases procedure time. Overall, applicator selection is not standardized and depends on physician expertise and preference. The purpose of this study is to determine whether dose prediction models can guide needle supplementation decision-making for cervical cancer. MATERIALS AND METHODS: Intracavitary knowledge-based models for organ-at-risk (OAR) dose estimation were trained and validated for tandem-and-ring/ovoids (T&R/T&O) implants. Models were applied to hybrid cases with 1-3 implanted needles to predict OAR dose without needles. As a reference, 70/67 hybrid T&R/T&O cases were replanned without needles, following a standardized procedure guided by dose predictions. If a replanned dose exceeded the dose objective, the case was categorized as requiring needles. Receiver operating characteristic (ROC) curves of needle classification accuracy were generated. Optimal classification thresholds were determined from the Youden Index. RESULTS: Needle supplementation reduced dose to OARs. However, 67%/39% of replans for T&R/T&O met all dose constraints without needles. The ROC for T&R/T&O models had an area-under-curve of 0.89/0.86, proving high classification accuracy. The optimal threshold of 99%/101% of the dose limit for T&R/T&O resulted in classification sensitivity and specificity of 78%/86% and 85%/78%. CONCLUSIONS: Needle supplementation reduced OAR dose for most cases but was not always required to meet standard dose objectives, particularly for T&R cases. Our knowledge-based dose prediction model accurately identified cases that could have met constraints without needle supplementation, suggesting that such models may be beneficial for applicator selection.

Voxel-level Classification of Prostate Cancer on Magnetic Resonance Imaging: Improving Accuracy Using Four-Compartment Restriction Spectrum Imaging.

BACKGROUND: Diffusion magnetic resonance imaging (MRI) is integral to detection of prostate cancer (PCa), but conventional apparent diffusion coefficient (ADC) cannot capture the complexity of prostate tissues and tends to yield noisy images that do not distinctly highlight cancer. A four-compartment restriction spectrum imaging (RSI4 ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI4 -C1 , yielded greatest tumor conspicuity. PURPOSE: To evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI4 -C1 ) as a quantitative voxel-level classifier of PCa. STUDY TYPE: Retrospective. SUBJECTS: Forty-six men who underwent an extended MRI acquisition protocol for suspected PCa. Twenty-three men had benign prostates, and the other 23 men had PCa. FIELD STRENGTH/SEQUENCE: A 3 T, multishell diffusion-weighted and axial T2-weighted sequences. ASSESSMENT: High-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI4 -C1 and conventional ADC. Classifier images were also generated. STATISTICAL TESTS: Voxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. RSI4 -C1 was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR90 ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05. RESULTS: RSI4 -C1 outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR90 (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P < 0.05). DATA CONCLUSION: RSI4 -C1 yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection and facilitate clinical applications like targeted biopsy and treatment planning. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Understanding implementation factors and participant experiences of a cluster randomised controlled trial to prevent falls among older Aboriginal people: a process evaluation protocol.

INTRODUCTION: Process evaluations examining programme implementation are often conducted in conjunction with effectiveness studies. Their inclusion in studies with Aboriginal participants can give an understanding of programme delivery in Aboriginal community contexts. The Ironbark: Standing Strong and Tall programme was codesigned with Aboriginal communities and includes exercise and facilitated 'yarning' discussion about fall risk and prevention strategies. The programme pilot showed favourable outcomes and acceptability for Aboriginal people aged 45 years and over. The Ironbark: Standing Strong and Tall programme is now being compared with a 'Healthy Community' programme in a cluster randomised controlled trial within Aboriginal health and community services. An embedded process evaluation aims to explore relationships between participation and programme outcomes and the quality of programme implementation. METHODS AND ANALYSIS: The process evaluation will use a mixed methods design, guided by Indigenous research methodology. It will evaluate quantitative data (number of completed sessions, site coaching checklist tool, participant and facilitator questionnaire data and a participant habit formation scale), as well as qualitative data (open-ended responses from project and site staff and semistructured interviews using yarning with study participants and site managers). A programme logic model was developed to explain the intended inputs, activities, outputs and outcomes, which guided this process evaluation design. CONCLUSION: This process evaluation of a fall prevention programme for older Aboriginal people using a mixed methods design and data triangulation will allow for a comprehensive understanding of study findings. Multiple study sites allow for generalisability of findings and exploration of variation across sites. TRIAL REGISTRATION NUMBER: ACTRN12619000349145.

Microstructural Injury to Corpus Callosum and Intrahemispheric White Matter Tracts Correlate With Attention and Processing Speed Decline After Brain Radiation.

PURPOSE: The corpus callosum (CC) and intrahemispheric white matter tracts (IHWM) subserve critical aspects of attention and processing speed. We analyzed imaging biomarkers of microstructural injury within these regions and association with attention and processing speed performance before and after radiation therapy in primary brain tumor patients. METHODS AND MATERIALS: In a prospective clinical trial, 44 primary brain tumor patients underwent cognitive testing and magnetic resonance imaging/diffusion-weighted imaging at baseline (pre-radiation therapy) and 3-, 6-, and 12-months post-radiation therapy. CC (subregions, total) and IHWM tracts (left/right without CC, total) were autosegmented; tumor, tumor bed, and edema were censored. Biomarkers included volume changes (cm3), mean diffusivity ([MD]; higher values indicate white matter injury), fractional anisotropy ([FA]; lower values indicate white matter injury). Reliable-change indices measured changes in attention (Weschler Adult Intelligence Scale [WAIS-IV] digits-forward; Delis-Kaplan Executive Function System Trail Making [D-KEFS-TM] visual-scanning), and processing speed (WAIS-IV coding; D-KEFS-TM number-sequencing, letter-sequencing), accounting for practice effects. Linear mixed-effects models evaluated associations between mean radiation dose and biomarkers (volume, MD, FA) and imaging biomarkers and neurocognitive performance. Statistics were corrected for multiple comparisons. RESULTS: Processing speed declined at 6 months following radiation therapy (number sequencing, letter sequencing; P < .04). Seizures and antiepileptic drug therapy were associated with lower visual-scanning attention reliable-change indices at 6 months (P = .039). Higher radiation dose correlated with smaller midanterior CC volume (P = .023); lower FA in posterior CC, anterior CC, and total CC (all P < .03); and higher MD in anterior CC (P = .012). Smaller midanterior CC and left IHWM volume correlated with worse processing speed (coding, letter-sequencing, number-sequencing; all P < .03). Higher FA in right, left, and total IHWM correlated with better coding scores (all P < .01). Lower FA in total IHWM (P = .009) was associated with worse visual-scanning attention scores. Higher FA in midposterior CC (P = .029) correlated with better digits-forward attention scores. CONCLUSIONS: The CC demonstrated radiation dose-dependent atrophy and WM injury. Microstructural injury within the CC and IHWM was associated with attention and processing speed decline after radiation therapy. These areas represent possible avoidance regions for preservation of attention and processing speed.

Quantification of hemodynamics of cerebral arteriovenous malformations after stereotactic radiosurgery using 4D flow magnetic resonance imaging.

Stereotactic radiosurgery (SRS) is used to treat cerebral arteriovenous malformations (AVMs). However, early evaluation of efficacy is difficult as structural magnetic resonance imaging (MRI)/magnetic resonance angiography (MRA) often does not demonstrate appreciable changes within the first 6 months. The aim of this study was to evaluate the use of four-dimensional (4D) flow MRI to quantify hemodynamic changes after SRS as early as 2 months. This was a retrospective observational study, which included 14 patients with both pre-SRS and post-SRS imaging obtained at multiple time points from 1 to 27 months after SRS. A 3T MRI Scanner was used to obtain T2 single-shot fast spin echo, time-of-flight MRA, and postcontrast 4D flow with three-dimensional velocity encoding between 150 and 200 cm/s. Post-hoc two-dimensional cross-sectional flow was measured for the dominant feeding artery, the draining vein, and the corresponding contralateral artery as a control. Measurements were performed by two independent observers, and reproducibility was assessed. Wilcoxon signed-rank tests were used to compare differences in flow, circumference, and pulsatility between the feeding artery and the contralateral artery both before and after SRS; and differences in nidus size and flow and circumference of the feeding artery and draining vein before and after SRS. Arterial flow (L/min) decreased in the primary feeding artery (mean: 0.1 ± 0.07 vs. 0.3 ± 0.2; p < 0.05) and normalized in comparison to the contralateral artery (mean: 0.1 ± 0.07 vs. 0.1 ± 0.07; p = 0.068). Flow decreased in the draining vein (mean: 0.1 ± 0.2 vs. 0.2 ± 0.2; p < 0.05), and the circumference of the draining vein also decreased (mean: 16.1 ± 8.3 vs. 15.7 ± 6.7; p < 0.05). AVM volume decreased after SRS (mean: 45.3 ± 84.8 vs. 38.1 ± 78.7; p < 0.05). However, circumference (mm) of the primary feeding artery remained similar after SRS (mean: 15.7 ± 2.7 vs. 16.1 ± 3.1; p = 0.600). 4D flow may be able to demonstrate early hemodynamic changes in AVMs treated with radiosurgery, and these changes appear to be more pronounced and occur earlier than the structural changes on standard MRI/MRA. Level of Evidence: 4 Technical Efficacy Stage: 1.

Microstructural Injury to Left-Sided Perisylvian White Matter Predicts Language Decline After Brain Radiation Therapy.

PURPOSE: Our purpose was to investigate the association between imaging biomarkers of radiation-induced white matter (WM) injury within perisylvian regions and longitudinal language decline in patients with brain tumors. METHODS AND MATERIALS: Patients with primary brain tumors (n = 44) on a prospective trial underwent brain magnetic resonance imaging, diffusion-weighted imaging, and language assessments of naming (Boston Naming Test [BNT]) and fluency (Delis-Kaplan Executive Function System Category Fluency [DKEFS-CF]) at baseline and 3, 6, and 12 months after fractionated radiation therapy (RT). Reliable change indices of language function (0-6 months), accounting for practice effects (RCI-PE), evaluated decline. Bilateral perisylvian WM regions (superficial WM subadjacent to Broca's area and the superior temporal gyrus [STG], inferior longitudinal fasciculus [ILF], inferior fronto-occipital fasciculus [IFOF], and arcuate fasciculus) were autosegmented. We quantified volume and diffusion measures of WM microstructure: fractional anisotropy (FA; lower values indicate disruption) and mean diffusivity (MD; higher values indicate injury). Linear mixed-effects models assessed mean dose as predictor of imaging biomarker change and imaging biomarkers as longitudinal predictors of language scores. RESULTS: DKEFS-CF scores declined at 6 months post-RT (RCI-PE, -0.483; P = .01), whereas BNT scores improved (RCI-PE, 0.262; P = .04). Higher mean dose to left and right regions was predictive of decreased volume (left-STG, P = .02; right-ILF and IFOF, P = .03), decreased FA (left-WM tracts, all P < .01; right-STG and IFOF, P < .02), and increased MD of left-WM tracts (all P < .03). Volume loss within left-Broca's area (P = .01), left-ILF (P = .01), left-IFOF (P = .01), and left-arcuate fasciculus (P = .04) was associated with lower BNT scores. Lower FA correlated with poorer DKEFS-CF and BNT scores within left-ILF (P = .02, not significant), left-IFOF (P = .02, .04), and left-arcuate fasciculus (P = .01, .01), respectively. Poorer DKEFS-CF scores correlated with increased MD values within the left-arcuate fasciculus (P = .03). Right-sided biomarkers did not correlate with language scores. CONCLUSIONS: Patients with primary brain tumors experience language fluency decline post-RT. Poorer fluency and naming function may be explained by microstructural injury to left-sided perisylvian WM, representing potential dose-avoidance targets for language preservation.

A knowledge-based organ dose prediction tool for brachytherapy treatment planning of patients with cervical cancer.

PURPOSE: The purpose of this study is to explore knowledge-based organ-at-risk dose estimation for intracavitary brachytherapy planning for cervical cancer. Using established external-beam knowledge-based dose-volume histogram (DVH) estimation methods, we sought to predict bladder, rectum, and sigmoid D2cc for tandem and ovoid treatments. METHODS AND MATERIALS: A total of 136 patients with loco-regionally advanced cervical cancer treated with 456 (356:100 training:validation ratio) CT-based tandem and ovoid brachytherapy fractions were analyzed. Single fraction prescription doses were 5.5-8 Gy with dose criteria for the high-risk clinical target volume, bladder, rectum, and sigmoid. DVH estimations were obtained by subdividing training set organs-at-risk into high-risk clinical target volume boundary distance subvolumes and computing cohort-averaged differential DVHs. Full DVH estimation was then performed on the training and validation sets. Model performance was quantified by ΔD2cc = D2cc(actual)-D2cc(predicted) (mean and standard deviation). ΔD2cc between training and validation sets were compared with a Student's t test (p < 0.01 significant). Categorical variables (physician, fraction-number, total fractions, and case complexity) that might explain model variance were examined using an analysis of variance test (Bonferroni-corrected p < 0.01 threshold). RESULTS: Training set deviations were bladder ΔD2cc = -0.04 ± 0.61 Gy, rectum ΔD2cc = 0.02 ± 0.57 Gy, and sigmoid ΔD2cc = -0.05 ± 0.52 Gy. Model predictions on validation set did not statistically differ: bladder ΔD2cc = -0.02 ± 0.46 Gy (p = 0.80), rectum ΔD2cc = -0.007 ± 0.47 Gy (p = 0.53), and sigmoid ΔD2cc = -0.07 ± 0.47 Gy (p = 0.70). The only significant categorical variable was the attending physician for bladder and rectum ΔD2cc. CONCLUSION: A simple boundary distance-driven knowledge-based DVH estimation exhibited promising results in predicting critical brachytherapy dose metrics. Future work will examine the utility of these predictions for quality control and automated brachytherapy planning.