Predictors of Tumor Dynamics Over a 6-Week Course of Concurrent Chemoradiotherapy for Glioblastoma and the Effect on Survival.

PURPOSE: We present the final analyses of tumor dynamics and their prognostic significance during a 6-week course of concurrent chemoradiotherapy for glioblastoma in the Glioblastoma Longitudinal Imaging Observational study. METHODS AND MATERIALS: This is a prospective serial magnetic resonance imaging study in 129 patients with glioblastoma who had magnetic resonance imaging obtained at radiation therapy (RT) planning (F0), fraction 10 (F10), fraction 20 (F20), and 1-month post-RT. Tumor dynamics assessed included gross tumor volume relative to F0 (Vrel) and tumor migration distance (dmigration). Covariables evaluated included: corpus callosum involvement, extent of surgery, O6-methylguanine-DNA-methyltransferase methylation, and isocitrate dehydrogenase mutation status. RESULTS: The median Vrel were 0.85 (range, 0.25-2.29) at F10, 0.79 (range, 0.09-2.22) at F20, and 0.78 (range, 0.13-4.27) at 1 month after completion of RT. The median dmigration were 4.7 mm (range, 1.1-20.4 mm) at F10, 4.7 mm (range, 0.8-20.7 mm) at F20, and 6.1 mm (range, 0.0-45.5 mm) at 1 month after completion of RT. Compared with patients who had corpus callosum involvement (n = 26), those without corpus callosum involvement (n = 103) had significant Vrel reduction at F20 (P = .03) and smaller dmigration at F20 (P = .007). Compared with patients who had biopsy alone (n = 19) and subtotal resection (n = 71), those who had gross total resection (n = 38) had significant Vrel reduction at F10 (P = .001) and F20 (P = .001) and a smaller dmigration at F10 (P = .03) and F20 (P = .002). O6-Methylguanine-DNA-methyltransferase methylation and isocitrate dehydrogenase mutation status were not significantly associated with tumor dynamics. The median progression-free survival and overall survival (OS) were 8.5 months (95% CI, 6.9-9.9) and 20.4 months (95% CI, 17.6-25.2). In multivariable analyses, patients with Vrel ≥ 1.33 at F10 had worse OS (hazard ratio [HR], 4.6; 95% CI, 1.8-11.4; P = .001), and patients with dmigration ≥ 5 mm at 1-month post-RT had worse progression-free survival (HR, 1.76; 95% CI, 1.08-2.87) and OS (HR, 2.2; 95% CI, 1.2-4.0; P = .007). CONCLUSIONS: Corpus callosum involvement and extent of surgery are independent predictors of tumor dynamics during RT and can enable patient selection for adaptive RT strategies. Significant tumor enlargement at F10 and tumor migration 1-month post-RT were associated with poorer OS.

Evolving concepts in margin strategies and adaptive radiotherapy for glioblastoma: A new future is on the horizon.

Chemoradiotherapy is the standard treatment after maximal safe resection for glioblastoma (GBM). Despite advances in molecular profiling, surgical techniques, and neuro-imaging, there have been no major breakthroughs in radiotherapy (RT) volumes in decades. Although the majority of recurrences occur within the original gross tumor volume (GTV), treatment of a clinical target volume (CTV) ranging from 1.5 to 3.0 cm beyond the GTV remains the standard of care. Over the past 15 years, the incorporation of standard and functional MRI sequences into the treatment workflow has become a routine practice with increasing adoption of MR simulators, and new integrated MR-Linac technologies allowing for daily pre-, intra- and post-treatment MR imaging. There is now unprecedented ability to understand the tumor dynamics and biology of GBM during RT, and safe CTV margin reduction is being investigated with the goal of improving the therapeutic ratio. The purpose of this review is to discuss margin strategies and the potential for adaptive RT for GBM, with a focus on the challenges and opportunities associated with both online and offline adaptive workflows. Lastly, opportunities to biologically guide adaptive RT using non-invasive imaging biomarkers and the potential to define appropriate volumes for dose modification will be discussed.

Endocrine and dog factors associated with semen quality.

Knowledge of factors associated with semen quality may help in investigations of the aetiology and pathophysiology. We investigated the correlation between biomarkers for testicular cell function (anti-müllerian hormone, AMH, Inhibin B, testosterone, free androgen-index (testosterone/sex-hormone binding globulin), insulin like peptide 3, INSL-3), alkaline phosphate (ALP), canine prostate-specific esterase (CPSE), and heterophilic antibodies with dog variables, semen quality, and fertility. Blood and semen were collected from 65 Bernese Mountain Dogs. We evaluated total sperm count, motility and morphological parameters. The semen quality ranged from poor to excellent, with an average total sperm count of 1.1 × 109 and 50% morphologically normal spermatozoa (MNS). Age and abnormal testicular consistency correlated with decreased motility and MNS. Higher ALP correlated with higher total sperm count. AMH could not be detected in seminal plasma. AMH in blood correlated with head defects and high AMH concentration correlated with a severe decline in several semen parameters. Testosterone was negatively and CPSE positively correlated with age. No correlations were found for INSL-3, inhibin B, or heterophilic antibodies. Our findings contribute to the understanding of factors associated with semen quality in dogs, particularly related to Sertoli cell function.

Technical note: The migration distance - a unidirectional distance metric for region-of-interest comparisons.

BACKGROUND: The radiotherapy process relies on several metrics in determining a notion of "distance" from one three-dimensional region-of-interest (ROI) to another. The majority are symmetric (or commutative) and do not contain information pertaining to directionality. Growth versus regression, for example, is not inherently distinguished by these metrics. PURPOSE: The purpose of this work was to formalize a unidirectional distance metric, motivated by radiotherapy margin concepts, which we term the migration distance. Informally, the migration distance from ROI X to Y is the minimum isotropic expansion of X such that Y is completely encompassed by the expansion. If Y is contained within X, the migration distance is negative with magnitude equal to the maximum isotropic contraction of X such that Y remains contained within contraction. The metric is demonstrated by quantifying glioblastoma interfraction target changes. METHODS: An explicit mathematical formulation of the migration distance is presented and contrasted with the related Hausdorff distance. The results are demonstrated for the gross tumor volume (GTV) dynamics of a glioblastoma cohort consisting of 111 patients that underwent standard chemoradiotherapy with offline MR imaging at planning, fraction 10, fraction 20, and 1-month post radiotherapy. RESULTS: The mean ± SD of the GTV migration distance relative to planning was 5.9 ± 3.9 mm at fraction 10, 6.2 ± 4.4 mm at fraction 20, and 7.9 ± 7.1 mm at 1-month post radiotherapy. The maximum GTV migration distance across all patients at the same timepoints was 20.4, 20.7, and 45.5 mm, respectively. CONCLUSIONS: We have proposed and demonstrated a unidirectional distance metric. The migration distance may have applications in the quantification of anatomical changes, planning target volume designs, and dosimetric radiotherapy plan assessment.

Chemical Exchange Saturation Transfer MRI: What Neuro-Oncology Clinicians Need To Know.

Chemical exchange saturation transfer (CEST) is a relatively novel magnetic resonance imaging (MRI) technique with an image contrast designed for in vivo measurement of certain endogenous molecules with protons that are exchangeable with water protons, such as amide proton transfer commonly used for neuro-oncology applications. Recent technological advances have made it feasible to implement CEST on clinical grade scanners within practical acquisition times, creating new opportunities to integrate CEST in clinical workflow. In addition, the majority of CEST applications used in neuro-oncology are performed without the use gadolinium-based contrast agents which are another appealing feature of this technique. This review is written for clinicians involved in neuro-oncologic care (nonphysicists) as the target audience explaining what they need to know as CEST makes its way into practice. The purpose of this article is to (1) review the basic physics and technical principles of CEST MRI, and (2) review the practical applications of CEST in neuro-oncology.

Relationship between apparent diffusion coefficient and survival as a function of distance from gross tumor volume on radiation planning MRI in newly diagnosed glioblastoma.

PURPOSE: To investigate the changes in apparent diffusion coefficient (ADC) within incrementally-increased margins beyond the gross tumor volume (GTV) on post-operative radiation planning MRI and their prognostic utility in glioblastoma. METHODS: Radiation planning MRIs of adult patients with newly diagnosed glioblastoma from 2017 to 2020 were assessed. The ADC values were normalized to contralateral normal white matter (nADC). Using 1 mm isotropic incremental margin increases from the GTV, the nADC values were calculated at each increment. Age, ECOG performance status, extent of resection and MGMT promoter methylation status were obtained from medical records. Using univariate and multivariable Cox regression analysis, association of nADC to progression-free and overall survival (PFS, OS) was assessed at each increment. RESULTS: Seventy consecutive patients with mean age of 53.6 ± 10.3 years, were evaluated. The MGMT promoter was methylated in 31 (44.3%), unmethylated in 36 (51.6%) and unknown in 3 (4.3%) patients. 11 (16%) underwent biopsy, 41 (44%) subtotal resection and 18 (26%) gross total resection. For each 1 mm increase in distance from GTV, the nADC decreased by 0.16% (p < 0.0001). At 1-5 mm increment, the nADC was associated with OS (p < 0.01). From 6 to 11 mm increment the nADC was associated with OS with the p-value gradually increasing from 0.018 to 0.046. nADC was not associated with PFS. CONCLUSION: The nADC values at 1-11 mm increments from the GTV margin were associated with OS. Future prospective multicenter studies are needed to validate the findings and to pave the way for the utilization of ADC for margin reduction in radiation planning.

Diffusion-weighted imaging on an MRI-linear accelerator to identify adversely prognostic tumour regions in glioblastoma during chemoradiation.

BACKGROUND AND PURPOSE: Survival in glioblastoma might be extended by escalating the radiotherapy dose to treatment-resistant tumour and adapting to tumour changes. Diffusion-weighted imaging (DWI) on MRI-linear accelerators (MR-Linacs) could be used to identify a dose escalation target, but its prognostic value must be demonstrated. The purpose of this study was to determine whether MR-Linac DWI can assess treatment response in glioblastoma and whether changes in DWI show greater prognostic value than changes in the contrast-enhancing gross tumour volume (GTV). MATERIALS AND METHODS: Seventy-five patients with glioblastoma were treated with chemoradiotherapy, of which 32 were treated on a 1.5 T MRI-linear accelerator (MR-Linac). Patients were imaged with simulation MRI scanners (MR-sim) at treatment planning and weeks 2, 4, and 10 after treatment start. Twenty-eight patients had additional MR-Linac DWI sequences. Cox modelling was used to evaluate the correlation of overall and progression-free survival (OS and PFS) with clinical variables and volumetric changes in the GTV and low-ADC regions (ADC < 1.25 µm2/ms within GTV). RESULTS: In total, 479 MR-Linac DWI and 289 MR-sim DWI datasets were analyzed. MR-Linac low-ADC changes between weeks 2 and 5 inclusive were prognostic for OS (hazard ratio lower limits ≥ 1.2, p-values ≤ 0.02). MR-sim low-ADC changes showed greater correlation with OS and PFS than GTV changes (e.g., OS hazard ratio at week 2 was 3.4 (p <0.001) for low-ADC versus 2.0 (p = 0.022) for GTV). CONCLUSION: MR-Linac DWI can measure low-ADC tumour volumes that correlate with OS and PFS better than contrast-enhancing GTV. Low-ADC regions could serve as dose escalation targets.

Cine MRI-based analysis of intrafractional motion in radiation treatment planning of head and neck cancer patients.

PURPOSE/OBJECTIVE(S): To investigate intrafraction motion of (HN) target volumes and to determine patient-specific planning target volume (PTV) margins. MATERIALS/METHODS: MR-cine imaging was performed for radiation treatment planning in HN cancer patients treated with definitive EBRT (n = 62) or SBRT (n = 4) on a 1.5 T MRI between 2017-2019. Dynamic MRI scans (sagittal orientation, 2 × 82 × 7 mm3 resolution), ranging from 3-5 min and 900-1500 images, were acquired. The position of the maximum tumor displacement along each direction in the anterior/posterior (A/P) and superior/inferior (S/I) position was recorded and analyzed to determine average PTV margins. RESULTS: Primary tumor sites (n = 66) were oropharynx (n = 39), larynx (n = 24) and hypopharynx (n = 3). PTV margins for A/P/S/I positions were 4.1/4.4/5.0/6.2 mm and 4.9/4.3/6.7/7.7 mm for oropharyngeal and laryngeal/hypopharyngeal cancers when accounting for all motion. V100 for PTV was calculated and compared to the original plans. The mean drop in PTV coverage was in most cases under 5%. For a subset of patients with 3 mm plans available, V100 for PTV had more substantial decreases in coverage averaging 8.2% - and 14.3% for oropharyngeal and laryngeal/hypopharynx plans, respectively. CONCLUSION: The use of MR-cine in treatment planning allows for quantification of tumor motion during swallow and resting periods and should be accounted for during treatment planning. With motion considered, the derived margins may exceed the commonly used 3-5 mm PTV margins. Quantification and analysis of tumor and patient-specific PTV margins is a step towards real-time MRI guidance adaptive radiotherapy.

Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group.

BACKGROUND AND PURPOSE: The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it. MATERIALS AND METHODS: Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CVD) and calculation methods (CVC). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group. RESULTS: The median (range) CVD and CVC were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types. CONCLUSION: Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.

CysPresso: a classification model utilizing deep learning protein representations to predict recombinant expression of cysteine-dense peptides.

BACKGROUND: Cysteine-dense peptides (CDPs) are an attractive pharmaceutical scaffold that display extreme biochemical properties, low immunogenicity, and the ability to bind targets with high affinity and selectivity. While many CDPs have potential and confirmed therapeutic uses, synthesis of CDPs is a challenge. Recent advances have made the recombinant expression of CDPs a viable alternative to chemical synthesis. Moreover, identifying CDPs that can be expressed in mammalian cells is crucial in predicting their compatibility with gene therapy and mRNA therapy. Currently, we lack the ability to identify CDPs that will express recombinantly in mammalian cells without labour intensive experimentation. To address this, we developed CysPresso, a novel machine learning model that predicts recombinant expression of CDPs based on primary sequence. RESULTS: We tested various protein representations generated by deep learning algorithms (SeqVec, proteInfer, AlphaFold2) for their suitability in predicting CDP expression and found that AlphaFold2 representations possessed the best predictive features. We then optimized the model by concatenation of AlphaFold2 representations, time series transformation with random convolutional kernels, and dataset partitioning. CONCLUSION: Our novel model, CysPresso, is the first to successfully predict recombinant CDP expression in mammalian cells and is particularly well suited for predicting recombinant expression of knottin peptides. When preprocessing the deep learning protein representation for supervised machine learning, we found that random convolutional kernel transformation preserves more pertinent information relevant for predicting expressibility than embedding averaging. Our study showcases the applicability of deep learning-based protein representations, such as those provided by AlphaFold2, in tasks beyond structure prediction.

Empirical planning target volume modeling for high precision MRI guided intracranial radiotherapy.

Purpose: Magnetic resonance image-guided radiotherapy for intracranial indications is a promising advance; however, uncertainties remain for both target localization after translation-only MR setup and intrafraction motion. This investigation quantified these uncertainties and developed a population-based planning target volume (PTV) model to explore target and organ-at-risk (OAR) volumetric coverage tradeoffs. Methods: Sixty-six patients, 49 with a primary brain tumor and 17 with a post-surgical resection cavity, treated on a 1.5T-based MR-linac across 1329 fractions were included. At each fraction, patients were setup by translation-only fusion of the online T1 MRI to the planning image. Each fusion was independently repeated offline accounting for rotations. The six degree-of-freedom difference between fusions was applied to transform the planning CTV at each fraction (CTVfx). A PTV model parameterized by volumetric CTVfx coverage, proportion of fractions, and proportion of patients was developed. Intrafraction motion was quantified in a 412 fraction subset as the fusion difference between post- and pre-irradiation T1 MRIs. Results: For the left-right/anterior-posterior/superior-inferior axes, mean ± SD of the rotational fusion differences were 0.1 ± 0.8/0.1 ± 0.8/-0.2 ± 0.9°. Covering 98 % of the CTVfx in 95 % of fractions in 95 % of patients required a 3 mm PTV margin. Margin reduction decreased PTV-OAR overlap; for example, the proportion of optic chiasm overlapped by the PTV was reduced up to 23.5 % by margin reduction from 4 mm to 3 mm. Conclusions: An evidence-based PTV model was developed for brain cancer patients treated on the MR-linac. Informed by this model, we have clinically adopted a 3 mm PTV margin for conventionally fractionated intracranial patients.

High grade glioma radiation therapy on a high field 1.5 Tesla MR-Linac - workflow and initial experience with daily adapt-to-position (ATP) MR guidance: A first report.

Purpose: This study reports the workflow and initial clinical experience of high grade glioma (HGG) radiotherapy on the 1.5 T MR-Linac (MRL), with a focus on the temporal variations of the tumor and feasibility of multi-parametric image (mpMRI) acquisition during routine treatment workflow. Materials and methods: Ten HGG patients treated with radiation within the first year of the MRL's clinical operation, between October 2019 and August 2020, were identified from a prospective database. Workflow timings were recorded and online adaptive plans were generated using the Adapt-To-Position (ATP) workflow. Temporal variation within the FLAIR hyperintense region (FHR) was assessed by the relative FHR volumes (n = 281 contours) and migration distances (maximum linear displacement of the volume). Research mpMRIs were acquired on the MRL during radiation and changes in selected functional parameters were investigated within the FHR. Results: All patients completed radiotherapy to a median dose of 60 Gy (range, 54-60 Gy) in 30 fractions (range, 30-33), receiving a total of 287 fractions on the MRL. The mean in-room time per fraction with or without post-beam research imaging was 42.9 minutes (range, 25.0-69.0 minutes) and 37.3 minutes (range, 24.0-51.0 minutes), respectively. Three patients (30%) required re-planning between fractions 9 to 12 due to progression of tumor and/or edema identified on daily MRL imaging. At the 10, 20, and 30-day post-first fraction time points 3, 3, and 4 patients, respectively, had a FHR volume that changed by at least 20% relative to the first fraction. Research mpMRIs were successfully acquired on the MRL. The median apparent diffusion coefficient (ADC) within the FHR and the volumes of FLAIR were significantly correlated when data from all patients and time points were pooled (R=0.68, p<.001). Conclusion: We report the first clinical series of HGG patients treated with radiotherapy on the MRL. The ATP workflow and treatment times were clinically acceptable, and daily online MRL imaging triggered adaptive re-planning for selected patients. Acquisition of mpMRIs was feasible on the MRL during routine treatment workflow. Prospective clinical outcomes data is anticipated from the ongoing UNITED phase 2 trial to further refine the role of MR-guided adaptive radiotherapy.

Putaminal Recombinant Glucocerebrosidase Delivery with Magnetic Resonance-Guided Focused Ultrasound in Parkinson's Disease: A Phase I Study.

BACKGROUND: GBA1 mutation is the most common genetic risk factor for Parkinson's disease (PD). Replacement of the lysosomal enzyme glucocerebrosidase (GCase) slows neurodegeneration in PD models and may be a promising disease-modifying therapy in patients with PD. However, recombinant GCase has limited penetration through the blood-brain barrier (BBB). Microbubble-mediated magnetic resonance-guided focused ultrasound (MRgFUS) can reversibly disrupt the BBB for drug delivery. METHODS: This open-label phase I study investigated the safety and feasibility of MRgFUS putaminal delivery of intravenous GCase at escalating doses (15 to 30 to 60 IU/kg) every 2 weeks in four patients with PD with GBA1 mutations. RESULTS: BBB permeability was achieved and restored in all patients as quantified by dynamic contrast-enhanced magnetic resonance imaging after treatment. There were no serious adverse events. Two patients developed transient dyskinesia after treatment. Blinded Movement Disorder Society-Unified Parkinson's Disease Rating Scale motor scores off medication decreased by 12% at 6 months from baseline (from 26 ± 9 to 22 ± 6). Standardized uptake value ratio on fluorodeoxyglucose positron emission tomography imaging in the treated putamen reduced from 1.66 ± 0.14 to 1.27 ± 0.08. CONCLUSIONS: Results from this study demonstrate the safety and feasibility of MRgFUS GCase delivery in PD and support further investigation of this approach. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Skull phantom-based methodology to validate MRI co-registration accuracy for Gamma Knife radiosurgery.

PURPOSE: Target localization, for stereotactic radiosurgery (SRS) treatment with Gamma Knife, has become increasingly reliant on the co-registration between the planning MRI and the stereotactic cone-beam computed tomography (CBCT). Validating image registration between modalities would be particularly beneficial when considering the emergence of novel functional and metabolic MRI pulse sequences for target delineation. This study aimed to develop a phantom-based methodology to quantitatively compare the co-registration accuracy of the standard clinical imaging protocol to a representative MRI sequence that was likely to fail co-registration. The comparative methodology presented in this study may serve as a useful tool to evaluate the clinical translatability of novel MRI sequences. METHODS: A realistic human skull phantom with fiducial marker columns was designed and manufactured to fit into a typical MRI head coil and the Gamma Knife patient positioning system. A series of "optimized" 3D MRI sequences-T1 -weighted Dixon, T1 -weighted fast field echo (FFE), and T2 -weighted fluid-attenuated inversion recovery (FLAIR)-were acquired and co-registered to the CBCT. The same sequences were "compromised" by reconstructing without geometric distortion correction and re-collecting with lower signal-to-noise-ratio (SNR) to simulate a novel MRI sequence with poor co-registration accuracy. Image similarity metrics-structural similarity (SSIM) index, mean squared error (MSE), and peak SNR (PSNR)-were used to quantitatively compare the co-registration of the optimized and compromised MR images. RESULTS: The ground truth fiducial positions were compared to positions measured from each optimized image volume revealing a maximum median geometric uncertainty of 0.39 mm (LR), 0.92 mm (AP), and 0.13 mm (SI) between the CT and CBCT, 0.60 mm (LR), 0.36 mm (AP), and 0.07 mm (SI) between the CT and T1 -weighted Dixon, 0.42 mm (LR), 0.23 mm (AP), and 0.08 mm (SI) between the CT and T1 -weighted FFE, and 0.45 mm (LR), 0.19 mm (AP), and 1.04 mm (SI) between the CT and T2 -weighted FLAIR. Qualitatively, pairs of optimized and compromised image slices were compared using a fusion image where separable colors were used to differentiate between images. Quantitatively, MSE was the most predictive and SSIM the second most predictive metric for evaluating co-registration similarity. A clinically relevant threshold of MSE, SSIM, and/or PSNR may be defined beyond which point an MRI sequence should be rejected for target delineation based on its dissimilarity to an optimized sequence co-registration. All dissimilarity thresholds calculated using correlation coefficients with in-plane geometric uncertainty would need to be defined on a sequence-by-sequence basis and validated with patient data. CONCLUSION: This study utilized a realistic skull phantom and image similarity metrics to develop a methodology capable of quantitatively assessing whether a modern research-based MRI sequence can be co-registered to the Gamma Knife CBCT with equal or less than equal accuracy when compared to a clinically accepted protocol.

Predicting survival in patients with glioblastoma using MRI radiomic features extracted from radiation planning volumes.

BACKGROUND: Quantitative image analysis using pre-operative magnetic resonance imaging (MRI) has been able to predict survival in patients with glioblastoma (GBM). The study explored the role of postoperative radiation (RT) planning MRI-based radiomics to predict the outcomes, with features extracted from the gross tumor volume (GTV) and clinical target volume (CTV). METHODS: Patients with IDH-wildtype GBM treated with adjuvant RT having MRI as a part of RT planning process were included in the study. 546 features were extracted from each GTV and CTV. A LASSO Cox model was applied, and internal validation was performed using leave-one-out cross-validation with overall survival as endpoint. Cross-validated time-dependent area under curve (AUC) was constructed to test the efficacy of the radiomics model, and clinical features were used to generate a combined model. Analysis was done for the entire group and in individual surgical groups-gross total excision (GTR), subtotal resection (STR), and biopsy. RESULTS: 235 patients were included in the study with 57, 118, and 60 in the GTR, STR, and biopsy subgroup, respectively. Using the radiomics model, binary risk groups were feasible in the entire cohort (p < 0.01) and biopsy group (p = 0.04), but not in the other two surgical groups individually. The integrated AUC (iAUC) was 0.613 for radiomics-based classification in the biopsy subgroup, which improved to 0.632 with the inclusion of clinical features. CONCLUSION: Imaging features extracted from the GTV and CTV regions can lead to risk-stratification of GBM undergoing biopsy, while the utility in other individual subgroups needs to be further explored.

International Multi-institutional Patterns of Contouring Practice and Clinical Target Volume Recommendations for Stereotactic Body Radiation Therapy for Non-Spine Bone Metastases.

PURPOSE: Despite the increasing use of stereotactic body radiation therapy for non-spine bone metastases (NSBM), there is no established standard for target delineation. The objective of this study was to provide consensus recommendations on clinical target volume (CTV) delineation based on international expert contours. METHODS AND MATERIALS: Eleven cases of NSBM were contoured by 9 international radiation oncologists. For each case, the gross tumor volume was provided on the simulation computed tomography scans with accompanying magnetic resonance imaging. Participants contoured the CTV and completed a clinical survey. Agreement between CTV contours were analyzed with simultaneous truth and performance level estimation using the kappa coefficient and the Dice similarity coefficient (DSC) and summarized to establish contouring recommendations. A direction-dependent analysis was applied to the consensus contours to quantify margins. RESULTS: All CTV contours were completed. Six participants used a single-dose level, whereas 3 used a 2-dose level simultaneous integrated boost (SIB) technique. For the SIB cases, the largest volume receiving a stereotactic body radiation therapy (SBRT) dose was used for contour analysis. There was substantial agreement between contours across cases with a mean kappa of 0.72 (mean sensitivity 0.85, mean specificity 0.97). The mean DSC value was 0.77 (range, 0.67-0.87). Consensus CTV contouring recommendations were (1) an intraosseous CTV margin of 5 to 10 mm should be strongly considered within contiguous bone; (2) an extraosseous margin of 5 to 10 mm should be strongly considered where there is soft tissue disease or cortical bone disruption; (3) CTVs should be manually cropped to respect anatomic barriers to spread (eg, peritoneal cavity, pleura, uninvolved joint space and cortical bone). CONCLUSIONS: CTV contouring recommendations for NSBM-SBRT were established based on analysis of international expert consensus contours with a high level of agreement. These principles may provide guidance to treating physicians and inform future study until prospective clinical data can provide further refinement.

Alzheimer's Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases.

Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis in the early stages of dementia remains challenging. Fueled by AD Neuroimaging Initiatives (ADNI) (Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.), a number of neuroimaging biomarkers for AD have been proposed, yet it remains to be seen whether these markers are also sensitive to other types of dementia. We assessed AD-related metabolic patterns in 27 patients with diverse forms of dementia (five had probable/possible AD while others had atypical cases) and 20 non-demented individuals. All participants had positron emission tomography (PET) scans on file. We used a pre-trained machine learning-based AD designation (MAD) framework to investigate the AD-related metabolic pattern among the participants under study. The MAD algorithm showed a sensitivity of 0.67 and specificity of 0.90 for distinguishing dementia patients from non-dementia participants. A total of 18/27 dementia patients and 2/20 non-dementia patients were identified as having AD-like patterns of metabolism. These results highlight that many underlying causes of dementia have similar hypometabolic pattern as AD and this similarity is an interesting avenue for future research.

MRI radiomics to differentiate between low grade glioma and glioblastoma peritumoral region.

BACKGROUND: The peritumoral region (PTR) of glioblastoma (GBM) appears as a T2W-hyperintensity and is composed of microscopic tumor and edema. Infiltrative low grade glioma (LGG) comprises tumor cells that seem similar to GBM PTR on MRI. The work here explored if a radiomics-based approach can distinguish between the two groups (tumor and edema versus tumor alone). METHODS: Patients with GBM and LGG imaged using a 1.5 T MRI were included in the study. Image data from cases of GBM PTR, and LGG were manually segmented guided by T2W hyperintensity. A set of 91 first-order and texture features were determined from each of T1W-contrast, and T2W-FLAIR, diffusion-weighted imaging sequences. Applying filtration techniques, a total of 3822 features were obtained. Different feature reduction techniques were employed, and a subsequent model was constructed using four machine learning classifiers. Leave-one-out cross-validation was used to assess classifier performance. RESULTS: The analysis included 42 GBM and 36 LGG. The best performance was obtained using AdaBoost classifier using all the features with a sensitivity, specificity, accuracy, and area of curve (AUC) of 91%, 86%, 89%, and 0.96, respectively. Amongst the feature selection techniques, the recursive feature elimination technique had the best results, with an AUC ranging from 0.87 to 0.92. Evaluation with the F-test resulted in the most consistent feature selection with 3 T1W-contrast texture features chosen in over 90% of instances. CONCLUSIONS: Quantitative analysis of conventional MRI sequences can effectively demarcate GBM PTR from LGG, which is otherwise indistinguishable on visual estimation.

Accuracy and precision of apparent diffusion coefficient measurements on a 1.5 T MR-Linac in central nervous system tumour patients.

BACKGROUND AND PURPOSE: MRI linear accelerators (MR-Linacs) may allow treatment adaptation to be guided by quantitative MRI including diffusion-weighted imaging (DWI). The aim of this study was to evaluate the accuracy and precision of apparent diffusion coefficient (ADC) measurements from DWI on a 1.5 T MR-Linac in patients with central nervous system (CNS) tumours through comparison with a diagnostic scanner. MATERIALS AND METHODS: CNS patients were treated using a 1.5 T Elekta Unity MR-Linac. DWI was acquired during MR-Linac treatment and on a Philips Ingenia 1.5 T. The agreement between the two scanners on median ADC over the gross tumour/clinical target volumes (GTV/CTV) and in brain regions (white/grey matter, cerebrospinal fluid (CSF)) was computed. Repeated scans were used to estimate ADC repeatability. Daily changes in ADC over the GTV of high-grade gliomas were characterized from MR-Linac scans. RESULTS: DWI from 59 patients was analyzed. MR-Linac ADC measurements showed a small bias relative to Ingenia measurements in white matter, grey matter, GTV, and CTV (bias: -0.05 ± 0.03, -0.08 ± 0.05, -0.1 ± 0.1, -0.08 ± 0.07 µm2/ms). ADC differed substantially in CSF (bias: -0.5 ± 0.3 µm2/ms). The repeatability of MR-Linac ADC over white/grey matter was similar to previous reports (coefficients of variation for median ADC: 1.4%/1.8%). MR-Linac ADC changes in the GTV were detectable. CONCLUSIONS: It is possible to obtain ADC measurements in the brain on a 1.5 T MR-Linac that are comparable to those of diagnostic-quality scanners. This technical validation study adds to the foundation for future studies that will correlate brain tumour ADC with clinical outcomes.

Deuterium MRS of early treatment-induced changes in tumour lactate in vitro.

Elevated production of lactate is a key characteristic of aberrant tumour cell metabolism and can be non-invasively measured as an early marker of tumour response using deuterium (2 H) MRS. Following treatment, changes in the 2 H-labelled lactate signal could identify tumour cell death or impaired metabolic function, which precede morphological changes conventionally used to assess tumour response. In this work, the association between apoptotic cell death, extracellular lactate concentration, and early treatment-induced changes in the 2 H-labelled lactate signal was established in an in vitro tumour model. Experiments were conducted at 7 T on acute myeloid leukaemia (AML) cells, which had been treated with 10 µg/mL of the chemotherapeutic agent cisplatin. At 24 and 48 h after cisplatin treatment the cells were supplied with 20 mM of [6,6'-2 H2 ]glucose and scanned over 2 h using a two-dimensional 2 H MR spectroscopic imaging sequence. The resulting signals from 2 H-labelled glucose, lactate, and water were quantified using a spectral fitting algorithm implemented on the Oxford Spectroscopy Analysis MATLAB toolbox. After scanning, the cells were processed for histological stains (terminal deoxynucleotidyl transferase UTP nick end labelling and haematoxylin and eosin) to assess apoptotic area fraction and cell morphology respectively, while a colorimetric assay was used to measure extracellular lactate concentrations in the supernatant. Significantly lower levels of 2 H-labelled lactate were observed in the 48 h treated cells compared with the untreated and 24 h treated cells, and these changes were significantly correlated with an increase in apoptotic fraction and a decrease in extracellular lactate. By establishing the biological processes associated with treatment-induced changes in the 2 H-labelled lactate signal, these findings suggest that 2 H MRS of lactate may be valuable in evaluating early tumour response.