Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma

INTRODUCTION: The purpose of this retrospective study was to compare two, widely available software packages for calculation of Dynamic Susceptibility Contrast (DSC) perfusion MRI normalized relative Cerebral Blood Volume (rCBV) values to differentiate tumor progression from pseudoprogression in treated high-grade glioma patients. MATERIAL AND METHODS: rCBV maps processed by Siemens Syngo.via (Siemens Healthineers) and Olea Sphere (Olea Medical) software packages were co-registered to contrast-enhanced T1 (T1-CE). Regions of interest based on T1-CE were transferred to the rCBV maps. rCBV was calculated using mean values and normalized using contralateral normal- appearing white matter. The Wilcoxon test was performed to assess for significant differences, and software-specific optimal rCBV cutoff values were determined using the Youden index. Interrater reliability was evaluated for two raters using the intraclass correlation coefficient. RESULTS: 41 patients (18 females; median age = 59 years; range 21-77 years) with 49 new or size-increasing post-treatment contrast-enhancing lesions were included (tumor progression = 40 lesions; pseudoprogression = 9 lesions). Optimal rCBV cutoffs of 1.31 (Syngo.via) and 2.40 (Olea) were significantly different, with an AUC of 0.74 and 0.78, respectively. Interrater reliability was 0.85. DISCUSSION: We demonstrate that different clinically available MRI DSC-perfusion software packages generate significantly different rCBV cutoff values for the differentiation of tumor progression from pseudoprogression in standard-of-care treated high grade gliomas. Physicians may want to determine the unique value of their perfusion software packages on an institutional level in order to maximize diagnostic accuracy when faced with this clinical challenge. Furthermore, combined with implementation of current DSC-perfusion recommendations, multi-center comparability will be improved

The centrally restricted diffusion sign on MRI for assessment of radiation necrosis in metastases treated with stereotactic radiosurgery

PURPOSE Differentiation of radiation necrosis from tumor progression in brain metastases treated with stereotactic radiosurgery (SRS) is challenging. For this, we assessed the performance of the centrally restricted diffusion sign. METHODS Patients with brain metastases treated with SRS who underwent a subsequent intervention (biopsy/resection) for a ring-enhancing lesion on preoperative MRI between 2000 and 2020 were included. Excluded were lesions containing increased susceptibility limiting assessment of DWI. Two neuroradiologists classified the location of the diffusion restriction with respect to the post-contrast T1 images as centrally within the ring-enhancement (the centrally restricted diffusion sign), peripherally correlating to the rim of contrast enhancement, both locations, or none. Measures of diagnostic accuracy and 95% CI were calculated for the centrally restricted diffusion sign. Cohen's kappa was calculated to identify the interobserver agreement. RESULTS Fifty-nine patients (36 female; mean age 59, range 40 to 80) were included, 36 with tumor progression and 23 with radiation necrosis based on histopathology. Primary tumors included 34 lung, 12 breast, 5 melanoma, 3 colorectal, 2 esophagus, 1 head and neck, 1 endometrium, and 1 thyroid. The centrally restricted diffusion sign was seen in 19/23 radiation necrosis cases (sensitivity 83% (95% CI 63 to 93%), specificity 64% (95% CI 48 to 78%), PPV 59% (95% CI 42 to 74%), NPV 85% (95% CI 68 to 94%)) and 13/36 tumor progression cases (difference p < 0.001). Interobserver agreement was substantial, at 0.61 (95% CI 0.45 to 70.8). CONCLUSION We found a low probability of radiation necrosis in the absence of the centrally restricted diffusion sign

Transformational Role of Medical Imaging in (Radiation) Oncology

Onboard, real-time, imaging techniques, from the original megavoltage planar imaging devices, to the emerging combined MRI-Linear Accelerators, have brought a huge transformation in the ability to deliver targeted radiation therapies. Each generation of these technologies enables lethal doses of radiation to be delivered to target volumes with progressively more accuracy and thus allows shrinking of necessary geometric margins, leading to reduced toxicities. Alongside these improvements in treatment delivery, advances in medical imaging, e.g., PET, and MRI, have also allowed target volumes themselves to be better defined. The development of functional and molecular imaging is now driving a conceptually larger step transformation to both better understand the cancer target and disease to be treated, as well as how tumors respond to treatment. A biological description of the tumor microenvironment is now accepted as an essential component of how to personalize and adapt treatment. This applies not only to radiation oncology but extends widely in cancer management from surgical oncology planning and interventional radiology, to evaluation of targeted drug delivery efficacy in medical oncology/immunotherapy. Here, we will discuss the role and requirements of functional and metabolic imaging techniques in the context of brain tumors and metastases to reliably provide multi-parametric imaging biomarkers of the tumor microenvironment

ATIM-22. PROGNOSTIC VALUE OF PTEN LOSS IN NEWLY DIAGNOSED GBM PATIENTS TREATED WITH AUTOLOGOUS HEAT SHOCK PROTEIN VACCINE

Abstract INTRODUCTION: The safety and efficacy of a heat shock protein peptide complex- 96 vaccine (HSPPC-96, Prophage) has been previously studied in phase II single-arm trials for the treatment of newly diagnosed and recurrent glioblastoma (GBM). These studies demonstrated modest improvements in survival compared with historical standards. PTEN loss has been recently associated with immunoresistance in GBM patients, mediated in part by B7-H1. PTEN status has not shown clear prognostic value in GBM patients treated with standard of care therapies. The aim of this study is to evaluate the prognostic significance of PTEN status in newly diagnosed GBM patients treated with autologous HSP vaccine and standard chemoradiation. METHODS Our institutional cohort of patients enrolled in a single arm, phase II study of adult GBM patients treated with autologous HSP vaccine and standard chemoradiation (n=27) was analyzed. Differences in overall survival (OS) by PTEN status were evaluated via Kaplan-Meier curves and Log-rank test. RESULTS Median overall survival (n=27) was 26 months. 23 patients had PTEN status available. PTEN loss was found in 16 patients (69.6%) whereas retained PTEN was present in 7 patients (30.4%). Median OS was 59 months (95% CI, 0–120 months) in patients with retained PTEN and 23 months (95% CI, 15–30 months) in patients with PTEN loss. The difference in OS was statistically significant (p=0.037). CONCLUSION: Retained PTEN expression was associated with extended survival in GBM patients treated with HSP vaccine. This finding suggests that PTEN loss may be associated with resistance to vaccine treatment and emphasizes the need for subgroup analysis in further immunotherapy studies

Treatment-induced lesions in newly diagnosed glioblastoma patients undergoing chemoradiotherapy and heat-shock protein vaccine therapy

ObjectivesTreatment-induced lesions represent a great challenge in neuro-oncology. The aims of this study were (i) to characterize treatment induced lesions in glioblastoma patients treated with chemoradiotherapy and heat-shock protein (HSP) vaccine and (ii) to evaluate the diagnostic accuracy of diffusion weighted imaging for differentiation between treatment-induced lesions and tumor progression.MethodsTwenty-seven patients with newly diagnosed glioblastoma treated with HSP vaccine and chemoradiotherapy were included. Serial magnetic resonance imaging evaluation was performed to detect treatment-induced lesions and assess their growth. Quantitative analysis of the apparent diffusion coefficient (ADC) was performed to discriminate treatment-induced lesions from tumor progression. Mann-Whitney U-test and receiver operating characteristic (ROC) curves were used for analysis.ResultsThirty-three percent of patients developed treatment-induced lesions. Five treatment-related lesions appeared between end of radiotherapy and the first vaccine administration; 4 lesions within the first 4&nbsp;months from vaccine initiation and 1 at 3.5&nbsp;years. Three patients with pathology proven treatment-induced lesions showed a biphasic growth pattern progressed shortly after. ADC ratio between the peripheral enhancing rim and central necrosis showed an accuracy of 0.84 (95% CI 0.63-1) for differentiation between progression and treatment-induced lesions.ConclusionOur findings do not support the iRANO recommendation of a 6-month time window in which progressive disease should not be declared after immunotherapy initiation. A biphasic growth&nbsp;pattern of pathologically proven treatment-induced lesions&nbsp;was associated with a dismal prognosis. The presence of lower ADC values in the central necrotic portion of the lesions compared to the enhancing rim shows high specificity for detection of treatment-induced lesions

Meta-analysis of timing of endovascular aneurysm treatment in subarachnoid haemorrhage : inconsistent results of early treatment within 1 day

BACKGROUND AND PURPOSE: To systematically review and meta-analyse the data on impact of timing of endovascular treatment in aneurysmal subarachnoid haemorrhage (SAH) to determine if earlier treatment is associated with improved clinical outcomes and reduced case fatality. METHODS: We searched MEDLINE, Cochrane database, EMBASE and Web of Science to identify studies for inclusion. The measures of effect utilised were unadjusted/adjusted ORs. Effect estimates were combined using random effects models for each outcome (poor outcome, case fatality); heterogeneity was assessed using the I2index. Subgroup and sensitivity analyses were performed to account for heterogeneity and risk of bias. RESULTS: 16 studies met the inclusion criteria. Treatment 1 day (OR=0.40 (95% CI 0.28 to 0.56; I2=0%)) but not when compared with treatment at 1-3 days (OR=1.16 (95% CI 0.47 to 2.90; I2=81%)). Treatment at <2 days and at <3 days were associated with similar odds of poor outcome compared with later treatment (OR=1.20 (95% CI 0.70 to 2.05; I2=73%; OR=0.71 (95% CI 0.36 to 1.37; I2=71%)). Early treatment was associated with similar odds of case fatality compared with later treatment, regardless of how early/late treatment were defined (OR=1.80 (95% CI 0.88 to 3.67; I2=34%) for treatment <1 day vs days 1-3; OR=1.71 (95% CI 0.72 to 4.03; I2=54%) for treatment <2 days vs later; OR=0.90 (95% CI 0.31 to 2.68; I2=48%) for treatment <3 days vs later). CONCLUSIONS: In only 1 of the analyses was there a statistically significant result, which favoured treatment <1 day. The inconsistent results and heterogeneity within most analyses highlight the lack of evidence for best timing of endovascular treatment in SAH patients

Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma

Introduction: The purpose of this retrospective study was to compare two, widely available software packages for calculation of Dynamic Susceptibility Contrast (DSC) perfusion MRI normalized relative Cerebral Blood Volume (rCBV) values to differentiate tumor progression from pseudoprogression in treated high-grade glioma patients. Material and Methods: rCBV maps processed by Siemens Syngo.via (Siemens Healthineers) and Olea Sphere (Olea Medical) software packages were co-registered to contrast-enhanced T1 (T1-CE). Regions of interest based on T1-CE were transferred to the rCBV maps. rCBV was calculated using mean values and normalized using contralateral normal- appearing white matter. The Wilcoxon test was performed to assess for significant differences, and software-specific optimal rCBV cutoff values were determined using the Youden index. Interrater reliability was evaluated for two raters using the intraclass correlation coefficient. Results: 41 patients (18 females; median age = 59 years; range 21–77 years) with 49 new or size-increasing post-treatment contrast-enhancing lesions were included (tumor progression = 40 lesions; pseudoprogression = 9 lesions). Optimal rCBV cutoffs of 1.31 (Syngo.via) and 2.40 (Olea) were significantly different, with an AUC of 0.74 and 0.78, respectively. Interrater reliability was 0.85. Discussion: We demonstrate that different clinically available MRI DSC-perfusion software packages generate significantly different rCBV cutoff values for the differentiation of tumor progression from pseudoprogression in standard-of-care treated high grade gliomas. Physicians may want to determine the unique value of their perfusion software packages on an institutional level in order to maximize diagnostic accuracy when faced with this clinical challenge. Furthermore, combined with implementation of current DSC-perfusion recommendations, multi-center comparability will be improved.ISSN:0720-048XISSN:1872-772

Improving the noninvasive classification of glioma genetic subtype with deep learning and diffusion-weighted imaging

BackgroundDiagnostic classification of diffuse gliomas now requires an assessment of molecular features, often including IDH-mutation and 1p19q-codeletion status. Because genetic testing requires an invasive process, an alternative noninvasive approach is attractive, particularly if resection is not recommended. The goal of this study was to evaluate the effects of training strategy and incorporation of biologically relevant images on predicting genetic subtypes with deep learning.MethodsOur dataset consisted of 384 patients with newly diagnosed gliomas who underwent preoperative MRI with standard anatomical and diffusion-weighted imaging, and 147 patients from an external cohort with anatomical imaging. Using tissue samples acquired during surgery, each glioma was classified into IDH-wildtype (IDHwt), IDH-mutant/1p19q-noncodeleted (IDHmut-intact), and IDH-mutant/1p19q-codeleted (IDHmut-codel) subgroups. After optimizing training parameters, top performing convolutional neural network (CNN) classifiers were trained, validated, and tested using combinations of anatomical and diffusion MRI with either a 3-class or tiered structure. Generalization to an external cohort was assessed using anatomical imaging models.ResultsThe best model used a 3-class CNN containing diffusion-weighted imaging as an input, achieving 85.7% (95% CI: [77.1, 100]) overall test accuracy and correctly classifying 95.2%, 88.9%, 60.0% of the IDHwt, IDHmut-intact, and IDHmut-codel tumors. In general, 3-class models outperformed tiered approaches by 13.5%-17.5%, and models that included diffusion-weighted imaging were 5%-8.8% more accurate than those that used only anatomical imaging.ConclusionTraining a classifier to predict both IDH-mutation and 1p19q-codeletion status outperformed a tiered structure that first predicted IDH-mutation, then 1p19q-codeletion. Including apparent diffusion coefficient (ADC), a surrogate marker of cellularity, more accurately captured differences between subgroups