Sequential MRI Research Articles

RADT-30. MANAGEMENT OF PRESUMED PSEUDOPROGRESSION WITH EARLY BEVACIZUMAB IN THE THREE MONTHS AFTER HIGH DOSE RADIATION THERAPY FOR GLIOBLASTOMA

Abstract BACKGROUND Optimal management for symptomatic steroid-refractory pseudoprogression (rPsP) following IMRT for Glioblastoma remains poorly defined. This study examined radiological volumetric response and clinical outcomes following use of early Bevacizumab (earlyBEV), defined as commencing during or within 3 months of IMRT. METHODS Consecutive patients managed with Stupp60Gy IMRT between 2016-2023 for Glioblastoma were analysed for those patients receiving earlyBEV for rPsP. Volumetric analysis was performed with sequential MRI T1gd/T2 sequences using preBEV and postBEV scans. Primary endpoint was volumetric reduction of T1gd/T2 volumes at month+2/3 postBEV. Clinical response, overall survival and pattern of relapse, specifically distant failure was assessed. RESULTS Forty-one (14%) of 289 patients received earlyBEV for rPsP, with median follow-up of 9.9months (q1-3:8-25) for survivors. Compared to remaining 248 patient cohort, earlyBEV had worse initial ECOG0,1 (50%vs76%); less near-total resection (5%vs42%); and less MGMT methylation (35%vs46%). Additionally at diagnosis the initial tumours had larger T1gd and T2 volumes. Median time to commencement of earlyBEV was 1.4months postIMRT; including seven patients during IMRT. All patients responded to BEV, with reduction in symptoms, steroid use and radiological volume, though one died pre-assessment. Median T1gd and T2 volumes before earlyBEV were 37cm3 (q1-3:23-63cm3) and 116cm3 (q1-3:90-148cm3) respectively, which were 95% and 78% larger than at diagnosis. Median survival postBEV was 8.1months (95%CI:7.5-8.6). Median volumes postBEV reduced to 16cm3 (q1-3:8-23cm3) and 41cm3 (29-55cm3); which was a percentage reduction for T1gd and T2 of 57% and 65%. Midline shift reduced from 5mm(q1-3:3-8mm) to zero in two-thirds of patients. Patients requiring earlyBEV had worse survival compared to remaining cohort (p<0.001); with median OS 11.9months (95%CI:10.4-13.5) vs 19.9months (95%CI:18.4-21.5). A component of distant relapse was evident in 48% of earlyBEV vs 34% in remaining cohort. One serious adverse event occurred with fatal intracranial haemorrhage day10 after initial BEV dose. CONCLUSION This study data confirms efficacy of earlyBEV for managing steroid-refractory pseudoprogression, but also the worse prognosis of this high-risk cohort.

Simplified shielded MEG-MRI multimodal system with scalar-mode optically pumped magnetometers as MEG sensors

Magnetoencephalography (MEG) conventionally operates within high-performance magnetic shields due to the extremely weak magnetic field signals from the measured objects and the narrow dynamic range of the magnetic sensors employed for detection. This limitation results in elevated equipment costs and restricted usage. Additionally, the information obtained from MEG is functional images, and to analyze from which part of the brain the signals are coming, it is necessary to capture morphological images separately. When MEG and morphological imaging devices are separate, despite their individual high measurement accuracies, discrepancies in positional information may arise. In response, we have developed a low-field magnetic resonance imaging system that incorporates scalar-mode optically pumped magnetometers with a wide dynamic range and exceptionally high measurement sensitivity as sensors for MEG. Operating at low magnetic fields eliminates the need for superconducting coils in magnetic resonance imaging and the high-performance magnetic shields essential for MEG, promising a substantial cost reduction compared to traditional approaches. We achieved a noise level of about 16.7pT/Hz1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${16.7}\\,\\hbox {pT/Hz}^{1/2}$$\\end{document} with a single channel magnetometer, and reached a noise level of 367fT/cm/Hz1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${367}\\,\\hbox {fT/cm/Hz}^{1/2}$$\\end{document} with a baseline of 1 cm through differential measurements. We employed this system to conduct sequential OPM-based magnetic field measurements and MRI imaging, successfully demonstrating the compatibility of high OPM sensitivity with clear MRI acquisition.

Evaluation of VQC-LSTM for disability forecasting in multiple sclerosis using sequential multisequence MRI

Evaluation of VQC-LSTM for disability forecasting in multiple sclerosis using sequential multisequence MRI

Sequential MRI Evaluation of Lymphatic Abnormalities over the Course of Fontan Completion.

Purpose To evaluate lymphatic abnormalities before and after Fontan completion using noncontrast lymphatic imaging and relate findings with postoperative outcomes. Materials and Methods This study is a retrospective review of noncontrast T2-weighted lymphatic imaging performed at The Children's Hospital of Philadelphia from June 2012 to February 2023 in patients with single ventricle physiology. All individuals with imaging at both pre-Fontan and Fontan stages were eligible. Lymphatic abnormalities were classified into four types based on severity and location of lymphatic vessels. Classifications were compared between images and related to clinical outcomes such as postoperative drainage and hospitalization, lymphatic complications, heart transplant, and death. Results Forty-three patients (median age, 10 years [IQR, 8-11]; 20 [47%] boys, 23 [53%] girls) were included in the study. Lymphatic abnormalities progressed in 19 individuals after Fontan completion (distribution of lymphatic classifications: type 1, 23; type 2, 11; type 3, 6; type 4, 3 vs type 1, 10; type 2, 18; type 3, 10; type 4, 5; P = .04). Compared with individuals showing no progression of lymphatic abnormalities, those progressing to a high-grade lymphatic classification had longer postoperative drainage (median time, 9 days [IQR, 6-14] vs 17 days [IQR, 10-23]; P = .04) and hospitalization (median time, 13 days [IQR, 9-25] vs 26 days [IQR, 18-30]; P = .03) after Fontan completion and were more likely to develop chylothorax (12% [three of 24] vs 75% [six of eight]; P < .01) and/or protein-losing enteropathy (0% [0 of 24] vs 38% [three of eight]; P < .01) during a median follow-up of 8 years (IQR, 5-9). Progression to any type was not associated with an increased risk of adverse events. Conclusion The study demonstrated that lymphatic structural abnormalities may progress in select individuals with single ventricle physiology after Fontan completion, and progression of abnormalities to a high-grade classification was associated with worse postoperative outcomes. Keywords: Congenital Heart Disease, Glenn, Fontan, Lymphatic Imaging, Cardiovascular MRI Supplemental material is available for this article. Published under a CC BY 4.0 license.

Computer-aided detection of prostate cancer in early stages using multi-parameter MRI: A promising approach for early diagnosis.

Transrectal ultrasound-guided prostate biopsy is the gold standard diagnostic test for prostate cancer, but it is an invasive examination of non-targeted puncture and has a high false-negative rate. In this study, we aimed to develop a computer-assisted prostate cancer diagnosis method based on multiparametric MRI (mpMRI) images. We retrospectively collected 106 patients who underwent radical prostatectomy after diagnosis with prostate biopsy. mpMRI images, including T2 weighted imaging (T2WI), diffusion weighted imaging (DWI), and dynamic-contrast enhanced (DCE), and were accordingly analyzed. We extracted the region of interest (ROI) about the tumor and benign area on the three sequential MRI axial images at the same level. The ROI data of 433 mpMRI images were obtained, of which 202 were benign and 231 were malignant. Of those, 50 benign and 50 malignant images were used for training, and the 333 images were used for verification. Five main feature groups, including histogram, GLCM, GLGCM, wavelet-based multi-fractional Brownian motion features and Minkowski function features, were extracted from the mpMRI images. The selected characteristic parameters were analyzed by MATLAB software, and three analysis methods with higher accuracy were selected. Through prostate cancer identification based on mpMRI images, we found that the system uses 58 texture features and 3 classification algorithms, including Support Vector Machine (SVM), K-nearest Neighbor (KNN), and Ensemble Learning (EL), performed well. In the T2WI-based classification results, the SVM achieved the optimal accuracy and AUC values of 64.3% and 0.67. In the DCE-based classification results, the SVM achieved the optimal accuracy and AUC values of 72.2% and 0.77. In the DWI-based classification results, the ensemble learning achieved optimal accuracy as well as AUC values of 75.1% and 0.82. In the classification results based on all data combinations, the SVM achieved the optimal accuracy and AUC values of 66.4% and 0.73. The proposed computer-aided diagnosis system provides a good assessment of the diagnosis of the prostate cancer, which may reduce the burden of radiologists and improve the early diagnosis of prostate cancer.

Ketamine-induced prevention of SD-associated late infarct progression in experimental ischemia

Spreading depolarizations (SDs) occur frequently in patients with malignant hemispheric stroke. In animal-based experiments, SDs have been shown to cause secondary neuronal damage and infarct expansion during the initial period of infarct progression. In contrast, the influence of SDs during the delayed period is not well characterized yet. Here, we analyzed the impact of SDs in the delayed phase after cerebral ischemia and the potential protective effect of ketamine. Focal ischemia was induced by distal occlusion of the left middle cerebral artery in C57BL6/J mice. 24 h after occlusion, SDs were measured using electrocorticography and laser-speckle imaging in three different study groups: control group without SD induction, SD induction with potassium chloride, and SD induction with potassium chloride and ketamine administration. Infarct progression was evaluated by sequential MRI scans. 24 h after occlusion, we observed spontaneous SDs with a rate of 0.33 SDs/hour which increased during potassium chloride application (3.37 SDs/hour). The analysis of the neurovascular coupling revealed prolonged hypoemic and hyperemic responses in this group. Stroke volume increased even 24 h after stroke onset in the SD-group. Ketamine treatment caused a lesser pronounced hypoemic response and prevented infarct growth in the delayed phase after experimental ischemia. Induction of SDs with potassium chloride was significantly associated with stroke progression even 24 h after stroke onset. Therefore, SD might be a significant contributor to delayed stroke progression. Ketamine might be a possible drug to prevent SD-induced delayed stroke progression.

The dilemma of neuroprotection trials in times of successful endovascular recanalization.

The "translational roadblock" between successful animal stroke studies and neutral clinical trials is usually attributed to conceptual weaknesses. However, we hypothesized that rodent studies cannot inform the human disease due to intrinsic pathophysiological differences between rodents and humans., i.e., differences in infarct evolution. To verify our hypothesis, we employed a mixed study design and compared findings from meta-analyses of animal studies and a retrospective clinical cohort study. For animal data, we systematically searched pubmed to identify all rodent studies, in which stroke was induced by MCAO and at least two sequential MRI scans were performed for infarct volume assessment within the first two days. For clinical data, we included 107 consecutive stroke patients with large artery occlusion, who received MRI scans upon admission and one or two days later. Our preclinical meta-analyses included 50 studies with 676 animals. Untreated animals had a median post-reperfusion infarct volume growth of 74%. Neuroprotective treatments reduced this infarct volume growth to 23%. A retrospective clinical cohort study showed that stroke patients had a median infarct volume growth of only 2% after successful recanalization. Stroke patients with unsuccessful recanalization, by contrast, experienced a meaningful median infarct growth of 148%. Our study shows that rodents have a significant post-reperfusion infarct growth, and that this post-reperfusion infarct growth is the target of neuroprotective treatments. Stroke patients with successful recanalization do not have such infarct growth and thus have no target for neuroprotection.

Brain Tumor Detection Using Classification Model

This study aims to develop automated methods for detecting and segmenting brain tumors in MRI scans using neural networks and conventional image processing. Accurately identifying tumor location and boundaries is crucial for diagnosis and determining the most effective treatment approach. Manual review by radiologists is time-consuming and subjective. However, recent advances in deep learning now enable more efficient analysis of large MRI datasets.&#x0D; A variety of neural network models have been explored for tumor segmentation, including recurrent networks, autoencoders and convolutional networks. RNNs are well-suited to capture contextual information across sequential MRI slices. Autoencoders perform unsupervised feature learning from the images. CNNs have shown promise due to their ability to directly learn visual patterns from pixel values. Unsupervised clustering techniques such as fuzzy c-means and k-means are also investigated to group tumor pixels based on intensity similarity without labeled data.&#x0D; Previous research combining these techniques has achieved high segmentation accuracy between 84-97% using additional image processing steps. Automated segmentation provides benefits over manual inspection such as reduced workload and more consistent delineation of tumor margins. It can precisely outline growths to aid radiologists in diagnosis and pathologists in assessing malignancy.&#x0D; The detection and segmentation of brain tumors has applications in both radiology and oncology. Radiologists could benefit from faster scan review and automated report generation. Neurosurgeons would gain insights into a tumor's size, location and infiltration to determine the most suitable surgical approach. Oncologists could utilize quantitative tumor features to select the most targeted radiation therapy or chemotherapy protocols. Overall, continued advances in deep and machine learning hold promise to improve diagnosis and management of brain cancer patients.

Preoperative growth dynamics of untreated glioblastoma: Description of an exponential growth type, correlating factors, and association with postoperative survival.

Little is known about the growth dynamics of untreated glioblastoma and its possible influence on postoperative survival. Our aim was to analyze a possible association of preoperative growth dynamics with postoperative survival. We performed a retrospective analysis of all adult patients surgically treated for newly diagnosed glioblastoma at our center between 2010 and 2020. By volumetric analysis of data of patients with availability of ≥3 preoperative sequential MRI, a growth pattern was aimed to be identified. Main inclusion criterion for further analysis was the availability of two preoperative MRI scans with a slice thickness of 1mm, at least 7 days apart. Individual growth rates were calculated. Association with overall survival (OS) was examined by multivariable. Out of 749 patients screened, 13 had ≥3 preoperative MRI, 70 had 2 MRI and met the inclusion criteria. A curve estimation regression model showed the best fit for exponential tumor growth. Median tumor volume doubling time (VDT) was 31 days, median specific growth rate (SGR) was 2.2% growth per day. SGR showed negative correlation with tumor size (rho = -0.59, P < .001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log-rank: P = .010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox regression model for patients after tumor resection. Especially small lesions suggestive of glioblastoma showed exponential tumor growth with variable growth rates and a median VDT of 31 days. SGR was significantly associated with OS in patients with tumor resection in our sample.

An Artificial Intelligence Generated Automated Algorithm to Measure Total Kidney Volume in ADPKD

IntroductionAccurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, we report an artificial intelligence (AI) generated method for routinely measuring total kidney volume (TKV). MethodsAn ensemble U-net algorithm was created using the nnUNet approach. The training and internal cross-validation cohort consisted of all 1.5T MRI data acquired using 5 different MRI scanners (454 kidneys, 227 scans) in the CYSTic consortium which was first manually segmented by a single human operator. As an independent validation cohort, we utilised 48 sequential clinical MRI scans with reference results of manual segmentation acquired by 6 individual analysts at a single centre. The tool was then implemented for clinical use and its performance analysed. ResultsThe training / internal validation cohort was younger (mean age 44.0 vs 51.5 years) and the female-male ratio higher (1.2 v 0.94) compared to the clinical validation cohort. The majority of CYSTic patients had PKD1 mutations (79%) and typical disease (Mayo Imaging Class 1, 86%). The median DICE score on the clinical validation dataset between the algorithm and human analysts was 0.96 for left and right kidneys with a median TKV error of -1.8%. The time taken to manually segment kidneys in the CYSTic dataset was 56 (±28) min whereas manual corrections of the algorithm output took 8.5 (±9.2) min per scan. ConclusionsOur AI-based algorithm demonstrates performance comparable to manual segmentation. Its rapidity and precision in real-world clinical cases demonstrate its suitability for clinical application.

Endoscope-assisted microsurgical resection of a third ventricular immature teratoma.

Reaching a tumor within the third ventricle is challenging, and planning an accessible trajectory is crucial without injuring the surrounding structures. We report a 5-year-old boy presented with headache and a seizure where sequential MRI brain studies in a short time period revealed a rapid growing immature teratoma within the third ventricle with hydrocephalic changes. Several management procedures were performed for CSF diversion and medical treatment of the tumor with chemotherapy and stem cell therapy. The tumor was rapidly growing, and surgical excision was decided. Total resection was achieved via endoscope-assisted microsurgical transcallosal approach. Seven years after surgery, the patient experienced no recurrence of the tumor with a favorable clinical condition. We report a rare case of posterior third ventricular immature teratoma where the endoscope-assisted microsurgical technique was implemented with favorable long-term postoperative outcome.

Poster 285: MRI Measurement of TT-TG Can Change Without Intervention: An Analysis of Sequential Pre-Operative MRIs in PFI patients

Objectives: Following a patella dislocation event, the patella can remain unstable, leading to patellofemoral instability (PI). There are various anatomic risk factors for PI that help guide surgical treatment including the tibial tubercle to trochlear groove (TT-TG) distance. However, to the authors knowledge, no study has analyzed the temporal changes in TT-TG prior to any surgical intervention. This study, therefore, sought to understand the variations in TT-TG for pediatric patients suffering from patellar instability prior to any surgical intervention. The authors hypothesized that the TT-TG would not substantially change between timepoints. Methods: Patients undergoing medial patellofemoral ligament (MPFL) reconstruction using CPT code 27427 between January 1, 2014 and December 31, 2019 by one of two orthopedic surgeons were identified. Patients were included if they 1) had two pre-operative MRIs performed of the same knee within 8 months of each other prior to any surgical intervention and 2) had an initial TT-TG between 10 mm and 20 mm. Exclusion criteria were previous ipsilateral knee surgery or planned MPFL reconstruction with tibial tubercle osteotomy. Initial and subsequent TT-TG measurements were compared using paired-samples t-tests with two-tailed statistical significance set at p ≤0.05. IBM SPSS Statistics version 22 (Armonk, NY) was used for all statistical analysis. Results: After considering 251 patients for inclusion, 26 patients met inclusion criteria and were analyzed. Mean age of the cohort was 14.5±2.4 years and 42.3% were male. TT-TG was initially noted to be 15.3±1.8 mm. At mean time between sequential MRI’s of 4.8±1.9 months, TT-TG was noted to be 17.1±3.5 mm. The differences between initial and subsequent TT-TG ranged from a 21% decrease to a 61% increase, with a mean difference of a 12.1% increase. Comparison between initial and subsequent TT-TG values demonstrated a significant difference (p=0.006). Conclusions: At a mean time between MRIs of 4.8 months, variations in TT-TG ranged from a decrease of 21% to an increase of 61%. These findings suggest that TT-TG measurements may vary in patients on sequential MRIs and could be due to variations in tibiofemoral rotation during imaging. Surgeons should be aware of these variations when planning surgical correction for patellar instability. [Table: see text]

Maternal SARS-CoV-2, Placental Changes and Brain Injury in 2 Neonates.

Long-term neurodevelopmental sequelae are a potential concern in neonates following in utero exposure to severe acute respiratory syndrome coronavirus disease 2 (SARS-CoV-2). We report 2 neonates born to SARS-CoV-2 positive mothers, who displayed early-onset (day 1) seizures, acquired microcephaly, and significant developmental delay over time. Sequential MRI showed severe parenchymal atrophy and cystic encephalomalacia. At birth, neither infant was SARS-CoV-2 positive (nasopharyngeal swab, reverse transcription polymerase chain reaction), but both had detectable SARS-CoV-2 antibodies and increased blood inflammatory markers. Placentas from both mothers showed SARS-CoV-2-nucleocapsid protein and spike glycoprotein 1 in the syncytiotrophoblast, fetal vascular malperfusion, and significantly increased inflammatory and oxidative stress markers pyrin domain containing 1 protein, macrophage inflammatory protein 1 βη, stromal cell-derived factor 1, interleukin 13, and interleukin 10, whereas human chorionic gonadotropin was markedly decreased. One infant (case 1) experienced sudden unexpected infant death at 13 months of age. The deceased infant's brain showed evidence of SARS-CoV-2 by immunofluorescence, with colocalization of the nucleocapsid protein and spike glycoprotein around the nucleus as well as within the cytoplasm. The constellation of clinical findings, placental pathology, and immunohistochemical changes strongly suggests that second-trimester maternal SARS-CoV-2 infection with placentitis triggered an inflammatory response and oxidative stress injury to the fetoplacental unit that affected the fetal brain. The demonstration of SARS-CoV-2 in the deceased infant's brain also raises the possibility that SARS-CoV-2 infection of the fetal brain directly contributed to ongoing brain injury. In both infants, the neurologic findings at birth mimicked the presentation of hypoxic-ischemic encephalopathy of newborn and neurologic sequelae progressed well beyond the neonatal period.

Sequential multi-parametric MRI in assessment of the histological subtype and features in the malignant pleural mesothelioma xenografts

ObjectiveIt is still a challenge to find a noninvasive technique to distinguish the histological subtypes of malignant pleural mesothelioma (MPM) and characterize the development of related histological features. We investigated the potential value of multiparametric MRI in the assessment of the histological subtype and development of histologic features in the MPM xenograft model. MethodsMPM xenograft models were developed by injecting tumour cells into the right axillary space of nude mice. The T1, T2, R2*, T2*, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) at 14 d, 28 d, and 42 d were measured and compared between the epithelial and biphasic MPM. Correlations between multiparametric MRI parameters and histologic features, including necrotic fraction (NF) and microvessel density (MVD), were analysed. ResultsThis study found that T2, T2* and IVIM-DWI parameters can reflect the spatial and temporal heterogeneity of MPM. Compared to the epithelial MPM, T2 and T2* were higher and ADC, D, D*, and f were lower in the biphasic MPM (P < 0.05). MRI parameters were different in different stages of epithelial and biphasic MPM. Moderate correlations were found between ADC and tumor volume and NF in the epithelial MPM, and there was a correlation between f and tumor volume and NF and MVD in the two groups. ConclusionMRI parameters changed with tumor progression in a xenograft model of MPM. MRI parameters may provide useful biomarkers for evaluating the histological subtype and histological features development of MPM.

MRI Investigation of the Differential Impact of Left Ventricular Ejection Fraction After Myocardial Infarction in Elderly vs. Nonelderly Patients to Predict Readmission for Heart Failure.

Patients with ST-segment elevation myocardial infarction (STEMI), especially elderly individuals, have an increased risk of readmission for acute heart failure (AHF). To study the impact of left ventricular ejection fraction (LVEF) by MRI to predict AHF in elderly (>70 years) and nonelderly patients after STEMI. Prospective. Multicenter registry of 759 reperfused STEMI patients (23.3% elderly). 1.5-T. Balanced steady-state free precession (cine imaging) and segmented inversion recovery steady-state free precession (late gadolinium enhancement) sequences. One-week MRI-derived LVEF (%) was quantified. Sequential MRI data were recorded in 579 patients. Patients were categorized according to their MRI-derived LVEF as preserved (p-LVEF, ≥50%), mildly reduced (mr-LVEF, 41%-49%), or reduced (r-LVEF, ≤40%). Median follow-up was 5 [2.33-7.54] years. Univariable (Student's t, Mann-Whitney U, chi-square, and Fisher's exact tests) and multivariable (Cox proportional hazard regression) comparisons and continuous-time multistate Markov model to analyze transitions between LVEF categories and to AHF. Hazard ratios (HR) with 95% confidence intervals (CIs) were computed. P < 0.05 was considered statistically significant. Over the follow-up period, 79 (10.4%) patients presented AHF. MRI-LVEF was the most robust predictor in nonelderly (HR 0.94 [0.91-0.98]) and elderly patients (HR 0.94 [0.91-0.97]). Elderly patients had an increased AHF risk across the LVEF spectrum. An excess of risk (compared to p-LVEF) was noted in patients with r-LVEF both in nonelderly (HR 11.25 [5.67-22.32]) and elderly patients (HR 7.55 [3.29-17.34]). However, the mr-LVEF category was associated with increased AHF risk only in elderly patients (HR 3.66 [1.54-8.68]). Less transitions to higher LVEF states (n=19, 30.2% vs. n=98, 53%) and more transitions to AHF state (n=34, 53.9% vs. n=45, 24.3%) were observed in elderly than nonelderly patients. MRI-derived p-LVEF confers a favorable prognosis and r-LVEF identifies individuals at the highest risk of AHF in both elderly and nonelderly patients. Nevertheless, an excess of risk was also found in the mr-LVEF category in the elderly group. 2. Stage 2.

Abstract 129: Cerebral Oxygen Extraction Fraction Predicts White Matter Lesion Progression In Patients With A Monogenic Cerebral Small Vessel Disease

Background: A rare, monogenic cerebral small vessel disease (cSVD), retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations (RVCL-S), is associated with progressive cerebral ischemia and accelerated vascular cognitive impairment, resulting in premature death. We hypothesized that low cerebral blood flow (CBF) and elevated oxygen extraction fraction (OEF), as metrics of microvascular ischemia, would predict growth of white matter lesions (WML) and other neuroimaging manifestations of cSVD. Methods: We prospectively performed sequential brain MRI in a cohort of RVCL-S participants. Pseudocontinuous arterial spin labeling and asymmetric spin echo quantified CBF and OEF in normal appearing white matter (NAWM), respectively. WMLs were manually delineated on FLAIR. WM volumes were segmented and quantified. Diffusion tensor imaging (DTI) was used to measure NAWM mean diffusivity (MD). Results: Each of 14 RVCL-S participants underwent a median of 4.5 scans (IQR 3 - 6.75) with a median of 6.5 months (IQR 5.8 - 8.6) between scans performed over 2.9 years (IQR 2.0 - 4.2). Elevated NAWM OEF from the previous MRI, but not CBF, was associated with WML growth (ρ = 0.672, p &lt; 0.0001), WM atrophy (ρ = 0.654, p &lt; 0.0001), and increased MD (ρ = 0.714, p &lt; 0.0001, Figure). After adjusting for age, sex, previous WML volume, and participant, previous OEF remained an independent predictor of WML growth (β = 7.04 (1.08, 13.01), p = 0.021). NAWM OEF was not retained in the mixed models predicting WM atrophy and MD. Conclusion: We found evidence that hypoxic-ischemic physiology, as measured by elevated OEF in NAWM, independently predicted WML growth. Previous OEF was associated with WM atrophy and decrease in microstructural integrity on follow-up. This work suggests that ischemia in normal brain regions may be a harbinger of disease progression in patients with RVCL-S, an inherited cSVD. Additionally, OEF may serve as a potential predictive biomarker in sporadic cSVD.

Evaluating the safety of perioperative dexamethasone treatment: A retrospective analysis of a single center pediatric low-grade glioma cohort.

In addition to surgical management, corticosteroids have proven to be beneficial in the management of acute symptoms related to CNS tumors, and have been widely used for many decades, with dexamethasone (DM) representing the most commonly used agent. However, lately published in vitro data possibly indicates a DM-induced suppression of oncogene-induced senescence (OIS) in a preclinical pediatric low-grade glioma (pLGG) model, which, alongside data associating perioperative DM treatment with reduced event-free survival in adult glioma, raises questions concerning the safety of DM treatment in pLGG. A total of 172 patients with pLGG were retrospectively analyzed concerning the impact of perioperative DM application on postoperative short- and long-term tumor growth velocity and progression-free survival (PFS). Three-dimensional volumetric analyses of sequential MRI follow-up examinations were used for assessment of tumor growth behavior. Mean follow-up period accounted for 60.1months. Sixty-five patients (45%) were perioperatively treated with DM in commonly used doses. Five-year PFS accounted for 93% following gross-total resection (GTR) and 57% post incomplete resection (IR). Comparison of short- and long-term postoperative tumor growth rates in patients with vs without perioperative DM application showed no significant difference (short-term: 0.022 vs 0.023 cm3 /month, respectively; long-term: 0.019 vs 0.023 cm3 /month, respectively). Comparison of PFS post IR (5-year-PFS: 65% vs 55%, respectively; 10-year-PFS: 52% vs 53%, respectively) and GTR (5- and 10-years-PFS: 91% vs 92%, respectively) likewise showed similarity. This data emphasizes the safety of perioperative DM application in pLGG, adding further evidence for decision making and requested future guidelines.

Intermuscular adipose tissue in patients with systemic lupus erythematosus

ObjectivePatients with SLE frequently have debilitating fatigue and reduced physical activity. Intermuscular adipose tissue (IMAT) accumulation is associated with reduced physical exercise capacity. We hypothesised that IMAT is increased in...

P17.05.A Re-irradiation with bevacizumab for large volume chemo-refractory glioblastoma after prior high-dose chemoradiotherapy

Abstract Background There are limited options for salvage treatment of glioblastoma. The role of re-irradiation (reRT) for large-volume chemo-refractory relapse is not established due to concerns regarding potential toxicity, which may be overcome with use of bevacizumab. Material and Methods Patients who received initial post-operative chemoradiotherapy with 60Gy (EORTC-NCIC protocol) for glioblastoma across two centres from 2007-2021 were entered into a prospective database. Patients with progressive chemo-refractory disease, including some progressing on bevacizumab, were considered for reRT. Pseudoprogression and late RT necrosis was actively excluded using sequential MRI and PET. Clinico-pathologic characteristics of the reRT cohort and patients who had progressed but did not undergo reRT were compared. Kaplan-Meier survival analysis was used to assess overall (OS) and progression-free survival (PFS) from diagnosis in the overall and reRT cohorts as well as OS post-reRT. Factors associated with improved survival post-reRT were assessed. Results Of 447 patients treated for glioblastoma, 372 had progressed of which 71 received reRT. Median follow up for surviving patients was 26 and 37 months from diagnosis for the reRT and overall cohorts respectively. Median PFS and OS from initial diagnosis were 11.6 (95% CI: 9.4-14.2) and 23.6 (95% CI: 21.0-33.1) months respectively for re-RT patients, compared to 11.8 (95% CI: 11.0-12.5) and 18.0 (95% CI 17.0-19.1) months for the overall cohort. The reRT subgroup were more likely to be younger (median 53 vs. 59 years, p&amp;lt;0.001), have ECOG performance status at diagnosis 0-1 (86% vs. 69%, p=0.002) and have MGMT promoter methylation (54% vs. 40% p=0.083). There was no difference in extent of initial resection (p=0.59). The most common reRT schedule was 15 fractions to a total dose of either 40 Gy (32 patients) or 35 Gy (28 patients). Sixty (85%) had progression on bevacizumab prior to reRT; bevacizumab was continued during reRT in these cases. A further 10 (14%) received salvage bevacizumab after reRT. Median reRT PTV volume was 135cc (IQR 69-207cc). Median OS following reRT was 7.1 months (95% CI: 6.3-7.9). Six (8%) patients were admitted to hospital within 30 days of reRT, only one due to reRT toxicity. Median OS post-reRT was 7.7, 6.4 and 6.0 months for patients aged &amp;lt;50, 50-70 and &amp;gt;70 years respectively (p=0.021) and 8.1 vs. 6.3 months for patients with ECOG performance status of 0-1 and 2-3 respectively (p=0.039). Distant versus local progression (p=0.87), anatomical location of disease (p=0.65), MGMT methylation status (p=0.77) and PTV volume (p=0.91) did not predict post-reRT survival. Conclusion Large volume reRT for patients with recurrent glioblastoma is feasible, well-tolerated, associated with favourable overall survival and produces meaningful post-radiotherapy survival times.

AI-assisted biparametric MRI surveillance of prostate cancer: feasibility study

ObjectivesTo evaluate the feasibility of automatic longitudinal analysis of consecutive biparametric MRI (bpMRI) scans to detect clinically significant (cs) prostate cancer (PCa).MethodsThis retrospective study included a multi-center dataset of 1513 patients who underwent bpMRI (T2 + DWI) between 2014 and 2020, of whom 73 patients underwent at least two consecutive bpMRI scans and repeat biopsies. A deep learning PCa detection model was developed to produce a heatmap of all PIRADS ≥ 2 lesions across prior and current studies. The heatmaps for each patient’s prior and current examination were used to extract differential volumetric and likelihood features reflecting explainable changes between examinations. A machine learning classifier was trained to predict from these features csPCa (ISUP > 1) at the current examination according to biopsy. A classifier trained on the current study only was developed for comparison. An extended classifier was developed to incorporate clinical parameters (PSA, PSA density, and age). The cross-validated diagnostic accuracies were compared using ROC analysis. The diagnostic performance of the best model was compared to the radiologist scores.ResultsThe model including prior and current study (AUC 0.81, CI: 0.69, 0.91) resulted in a higher (p = 0.04) diagnostic accuracy than the current only model (AUC 0.73, CI: 0.61, 0.84). Adding clinical variables further improved diagnostic performance (AUC 0.86, CI: 0.77, 0.93). The diagnostic performance of the surveillance AI model was significantly better (p = 0.02) than of radiologists (AUC 0.69, CI: 0.54, 0.81).ConclusionsOur proposed AI-assisted surveillance of prostate MRI can pick up explainable, diagnostically relevant changes with promising diagnostic accuracy.Key Points• Sequential prostate MRI scans can be automatically evaluated using a hybrid deep learning and machine learning approach.• The diagnostic accuracy of our csPCa detection AI model improved by including clinical parameters.