Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.

PURPOSE: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas. METHODS: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS). RESULTS: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS. CONCLUSION: Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas.

Cancer Imaging in Immunotherapy.

Immune therapeutics are revolutionizing cancer treatments. In tandem, new and confounding imaging characteristics have appeared that are distinct from those typically seen with conventional cytotoxic therapies. In fact, only 10% of patients on immunotherapy may show tumor shrinkage, typical of positive responses on conventional therapy. Conversely, those on immune therapies may initially demonstrate a delayed response, transient enlargement followed by tumor shrinkage, stable size, or the appearance of new lesions. Response Evaluation Criteria in Solid Tumors (RECIST) or WHO criteria, developed to identify early effects of cytotoxic agents, may not provide a complete evaluation of new emerging treatment response pattern of immunotherapeutic agents. Therefore, new imaging response criteria, such as the immune-related Response Evaluation Criteria in Solid Tumors (irRECIST), immune Response Evaluation Criteria in Solid Tumors (iRECIST), and immune-related Response Criteria (irRC), are proposed. However, FDA approval of emerging therapies including immunotherapies still relies on the current RECIST criteria. In this chapter, we review the traditional and new imaging response criteria for evaluation of solid tumors and briefly touch on some of the more commonly associated immunotherapy-induced adverse events.

Cancer Imaging in Immunotherapy.

Immune therapeutics are revolutionizing cancer treatments. In tandem, new and confounding imaging characteristics have appeared that are distinct from those typically seen with conventional cytotoxic therapies. In fact, only 10% of patients on immunotherapy may show tumor shrinkage, typical of positive responses on conventional therapy. Conversely, those on immune therapies may initially demonstrate a delayed response, transient enlargement followed by tumor shrinkage, stable size, or the appearance of new lesions. New imaging response criteria, such as the immune-related Response Evaluation Criteria in Solid Tumors (irRECIST) and immune-related Response Criteria (irRC), are being implemented in many trials. However, FDA approval of emerging therapies, including immunotherapies, still relies on the current RECIST criteria. In this chapter, we review the traditional and new imaging response criteria for evaluation of solid tumors and briefly touch on some of the more commonly associated immunotherapy-induced adverse events.

Primary central nervous system lymphoma in patients with and without HIV infection: a multicenter study and comparison with U.S national data.

PURPOSE: Primary central nervous system lymphoma (PCNSL) in patients living with HIV (PLWH) is a distinct entity; however, the management is adopted from patients without HIV. The study aims to examine the differences in presentation, treatment, and outcomes of PCNSL patients with or without HIV. METHODS: We retrospectively compared the characteristics of 144 patients with PCNSL with and without HIV, and analyzed factors associated with overall and progression-free survival. Results were compared to the Central Brain Tumor Registry of the United States (CBTRUS) and the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) system. RESULTS: Among all patients with PCNSL, 19% had HIV. PLWH were younger (38 vs. 63 years; p < 0.01) and more likely to be African American (59% vs. 7%; p < 0.01) and male (74% vs. 49%; p = 0.02) than patients without HIV. PLWH were more likely to have multiple lesions (67% vs. 43%; p = 0.02), hemorrhage (59 vs. 37%; p = 0.03), and peripheral rim enhancement (57% vs. 7%; p < 0.01) on imaging; to receive palliative care (15% vs. 2%) or whole brain radiation (63% vs. 3%); and less likely to receive chemotherapy (22% vs. 95%) (p < 0.01). Twenty-four patients, none PLWH, underwent stem cell transplant. Not receiving transplant was an independent factor in mortality and disease progression. Our cohort of patients, compared to the national database, were younger (60 vs. 65 years), 58% were white vs. 75%, and had longer median overall survival 43 vs. 25 months. CONCLUSION: Epidemiology, imaging, and treatment options for patients with PCNSL with and without HIV differ, but HIV was not an independent factor of mortality or disease progression. More efforts are needed to improve access to research and treatment options for PLWH with PCNSL.

Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas.

BACKGROUND: Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas. METHODS: We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes. RESULTS: Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma. CONCLUSIONS: The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).

Radiomics to predict immunotherapy-induced pneumonitis: proof of concept.

We present the first reported work that explores the potential of radiomics to predict patients who are at risk for developing immunotherapy-induced pneumonitis. Despite promising results with immunotherapies, immune-related adverse events (irAEs) are challenging. Although less common, pneumonitis is a potentially fatal irAE. Thus, early detection is critical for improving treatment outcomes; an urgent need to identify biomarkers that predict patients at risk for pneumonitis exists. Radiomics, an emerging field, is the automated extraction of high fidelity, high-dimensional imaging features from standard medical images and allows for comprehensive visualization and characterization of the tissue of interest and corresponding microenvironment. In this pilot study, we sought to determine whether radiomics has the potential to predict development of pneumonitis. We performed radiomic analyses using baseline chest computed tomography images of patients who did (N = 2) and did not (N = 30) develop immunotherapy-induced pneumonitis. We extracted 1860 radiomic features in each patient. Maximum relevance and minimum redundancy feature selection method, anomaly detection algorithm, and leave-one-out cross-validation identified radiomic features that were significantly different and predicted subsequent immunotherapy-induced pneumonitis (accuracy, 100% [p = 0.0033]). This study suggests that radiomic features can classify and predict those patients at baseline who will subsequently develop immunotherapy-induced pneumonitis, further enabling risk-stratification that will ultimately lead to better treatment outcomes.

Incidence of immune-related adverse events and its association with treatment outcomes: the MD Anderson Cancer Center experience.

Background Immunotherapy is emerging as the cornerstone for treatment of patients with advanced cancer, but significant toxicity (immune-related adverse events [irAEs]) associated with unbridled T cell activity remains a concern. Patients and methods A retrospective review of the electronic medical records of 290 patients with advanced cancer treated on an immunotherapy-based clinical trial in the Department of Investigational Cancer Therapeutics at The University of Texas MD Anderson Cancer Center between February 2010 and September 2015 was performed. Clinical and laboratory parameters were collected to determine the incidence of irAEs, risk factors, and their association with treatment outcomes. Results Ninety eight of 290 patients (34%) experienced any grade irAEs. Among the 15 (5.2%) patients with grade ≥ 3 irAEs, the most common irAEs were dermatitis and enterocolitis. Although 80% of the patients with grade ≥ 3 irAEs required systemic corticosteroids, all the 15 patients recovered from the irAEs. On re-challenge, 4 of the 5 patients who had received systemic corticosteroids for irAE continued to respond. There were no irAE-related deaths. Importantly, patients with grade ≥ 3 irAEs had improved overall response rate (25 vs. 6%; p = 0.039) and longer median time to progression (30 weeks vs. 10 weeks; p = 0.0040) when compared to those without grade ≥ 3 irAEs. Conclusion Incidence of irAEs with immunotherapeutic agents indicates an active immune status, suggestive of potential clinical benefit to the patient. Further validation of this association in a large prospective study is warranted.

Multi-center study finds postoperative residual non-enhancing component of glioblastoma as a new determinant of patient outcome.

INTRODUCTION: The aim of the present study is to assess whether postoperative residual non-enhancing volume (PRNV) is correlated and predictive of overall survival (OS) in glioblastoma (GBM) patients. METHODS: We retrospectively analyzed a total 134 GBM patients obtained from The University of Texas MD Anderson Cancer Center (training cohort, n = 97) and The Cancer Genome Atlas (validation cohort, n = 37). All patients had undergone postoperative magnetic resonance imaging immediately after surgery. We evaluated the survival outcomes with regard to PRNV. The role of possible prognostic factors that may affect survival after resection, including age, sex, preoperative Karnofsky performance status, postoperative nodular enhancement, surgically induced enhancement, and postoperative necrosis, was investigated using univariate and multivariate Cox proportional hazards regression analyses. Additionally, a recursive partitioning analysis (RPA) was used to identify prognostic groups. RESULTS: Our analyses revealed that a high PRNV (HR 1.051; p-corrected = 0.046) and old age (HR 1.031; p-corrected = 0.006) were independent predictors of overall survival. This trend was also observed in the validation cohort (higher PRNV: HR 1.127, p-corrected = 0.002; older age: HR 1.034, p-corrected = 0.022). RPA analysis identified two prognostic risk groups: low-risk group (PRNV < 70.2 cm3; n = 55) and high-risk group (PRNV ≥ 70.2 cm3; n = 42). GBM patients with low PRNV had a significant survival benefit (5.6 months; p = 0.0037). CONCLUSION: Our results demonstrate that high PRNV is associated with poor OS. Such results could be of great importance in a clinical setting, particularly in the postoperative management and monitoring of therapy.

FGWAS: Functional genome wide association analysis.

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs.

Cancer Imaging in Immunotherapy.

Immune therapeutics are revolutionizing cancer treatments. In tandem, new and confounding imaging characteristics have appeared that are distinct from those typically seen with conventional cytotoxic therapies. In fact, only 10% of patients on immunotherapy may show tumor shrinkage, typical of positive responses on conventional therapy. Conversely, those on immune therapies may initially demonstrate a delayed response, transient enlargement followed by tumor shrinkage, stable size, or the appearance of new lesions. New imaging response criteria such as the immune-related Response Evaluation Criteria in Solid Tumors (irRECIST) and immune-related Response Criteria (irRC) are being implemented in many trials. However, FDA approval of emerging therapies including immunotherapies still relies on the current RECIST criteria. In this review, we review the traditional and new imaging response criteria for evaluation of solid tumors and briefly touch on some of the more commonly associated immunotherapy-induced adverse events.

Mir-21-Sox2 Axis Delineates Glioblastoma Subtypes with Prognostic Impact.

Glioblastoma (GBM) is the most aggressive human brain tumor. Although several molecular subtypes of GBM are recognized, a robust molecular prognostic marker has yet to be identified. Here, we report that the stemness regulator Sox2 is a new, clinically important target of microRNA-21 (miR-21) in GBM, with implications for prognosis. Using the MiR-21-Sox2 regulatory axis, approximately half of all GBM tumors present in the Cancer Genome Atlas (TCGA) and in-house patient databases can be mathematically classified into high miR-21/low Sox2 (Class A) or low miR-21/high Sox2 (Class B) subtypes. This classification reflects phenotypically and molecularly distinct characteristics and is not captured by existing classifications. Supporting the distinct nature of the subtypes, gene set enrichment analysis of the TCGA dataset predicted that Class A and Class B tumors were significantly involved in immune/inflammatory response and in chromosome organization and nervous system development, respectively. Patients with Class B tumors had longer overall survival than those with Class A tumors. Analysis of both databases indicated that the Class A/Class B classification is a better predictor of patient survival than currently used parameters. Further, manipulation of MiR-21-Sox2 levels in orthotopic mouse models supported the longer survival of the Class B subtype. The MiR-21-Sox2 association was also found in mouse neural stem cells and in the mouse brain at different developmental stages, suggesting a role in normal development. Therefore, this mechanism-based classification suggests the presence of two distinct populations of GBM patients with distinguishable phenotypic characteristics and clinical outcomes. SIGNIFICANCE STATEMENT: Molecular profiling-based classification of glioblastoma (GBM) into four subtypes has substantially increased our understanding of the biology of the disease and has pointed to the heterogeneous nature of GBM. However, this classification is not mechanism based and its prognostic value is limited. Here, we identify a new mechanism in GBM (the miR-21-Sox2 axis) that can classify ∼50% of patients into two subtypes with distinct molecular, radiological, and pathological characteristics. Importantly, this classification can predict patient survival better than the currently used parameters. Further, analysis of the miR-21-Sox2 relationship in mouse neural stem cells and in the mouse brain at different developmental stages indicates that miR-21 and Sox2 are predominantly expressed in mutually exclusive patterns, suggesting a role in normal neural development.

A randomized phase II trial of standard dose bevacizumab versus low dose bevacizumab plus lomustine (CCNU) in adults with recurrent glioblastoma.

Antiangiogenic therapy can rapidly reduce vascular permeability and cerebral edema but high doses of bevacizumab may induce selective pressure to promote resistance. This trial evaluated the efficacy of low dose bevacizumab in combination with lomustine (CCNU) compared to standard dose bevacizumab in patients with recurrent glioblastoma. Patients (N = 71) with recurrent glioblastoma who previously received radiation and temozolomide were randomly assigned 1:1 to receive bevacizumab monotherapy (10 mg/kg) or low dose bevacizumab (5 mg/kg) in combination with lomustine (90 mg/m(2)). The primary end point was progression-free survival (PFS) based on a blinded, independent radiographic assessment of post-contrast T1-weighted and non-contrast T2/FLAIR weighted magnetic resonance imaging (MRI) using RANO criteria. For 69 evaluable patients, median PFS was not significantly longer in the low dose bevacizumab + lomustine arm (4.34 months, CI 2.96-8.34) compared to the bevacizumab alone arm (4.11 months, CI 2.69-5.55, p = 0.19). In patients with first recurrence, there was a trend towards longer median PFS time in the low dose bevacizumab + lomustine arm (4.96 months, CI 4.17-13.44) compared to the bevacizumab alone arm (3.22 months CI 2.5-6.01, p = 0.08). The combination of low dose bevacizumab plus lomustine was not superior to standard dose bevacizumab in patients with recurrent glioblastoma. Although the study was not designed to exclusively evaluate patients at first recurrence, a strong trend towards improved PFS was seen in that subgroup for the combination of low dose bevacizumab plus lomustine. Further studies are needed to better identify such subgroups that may most benefit from the combination treatment.

Glioblastoma: imaging genomic mapping reveals sex-specific oncogenic associations of cell death.

PURPOSE: To identify the molecular profiles of cell death as defined by necrosis volumes at magnetic resonance (MR) imaging and uncover sex-specific molecular signatures potentially driving oncogenesis and cell death in glioblastoma (GBM). MATERIALS AND METHODS: This retrospective study was HIPAA compliant and had institutional review board approval, with waiver of the need to obtain informed consent. The molecular profiles for 99 patients (30 female patients, 69 male patients) were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Volumes of necrosis at MR imaging were extracted. Differential gene expression profiles were obtained in those patients (including male and female patients separately) with high versus low MR imaging volumes of tumor necrosis. Ingenuity Pathway Analysis was used for messenger RNA-microRNA interaction analysis. A histopathologic data set (n = 368; 144 female patients, 224 male patients) was used to validate the MR imaging findings by assessing the amount of cell death. A connectivity map was used to identify therapeutic agents potentially targeting sex-specific cell death in GBM. RESULTS: Female patients showed significantly lower volumes of necrosis at MR imaging than male patients (6821 vs 11 050 mm(3), P = .03). Female patients, unlike male patients, with high volumes of necrosis at imaging had significantly shorter survival (6.5 vs 14.5 months, P = .01). Transcription factor analysis suggested that cell death in female patients with GBM is associated with MYC, while that in male patients is associated with TP53 activity. Additionally, a group of therapeutic agents that can potentially be tested to target cell death in a sex-specific manner was identified. CONCLUSION: The results of this study suggest that cell death in GBM may be driven by sex-specific molecular pathways.

Quality assurance assessment of diagnostic and radiation therapy-simulation CT image registration for head and neck radiation therapy: anatomic region of interest-based comparison of rigid and deformable algorithms.

PURPOSE: To develop a quality assurance (QA) workflow by using a robust, curated, manually segmented anatomic region-of-interest (ROI) library as a benchmark for quantitative assessment of different image registration techniques used for head and neck radiation therapy-simulation computed tomography (CT) with diagnostic CT coregistration. MATERIALS AND METHODS: Radiation therapy-simulation CT images and diagnostic CT images in 20 patients with head and neck squamous cell carcinoma treated with curative-intent intensity-modulated radiation therapy between August 2011 and May 2012 were retrospectively retrieved with institutional review board approval. Sixty-eight reference anatomic ROIs with gross tumor and nodal targets were then manually contoured on images from each examination. Diagnostic CT images were registered with simulation CT images rigidly and by using four deformable image registration (DIR) algorithms: atlas based, B-spline, demons, and optical flow. The resultant deformed ROIs were compared with manually contoured reference ROIs by using similarity coefficient metrics (ie, Dice similarity coefficient) and surface distance metrics (ie, 95% maximum Hausdorff distance). The nonparametric Steel test with control was used to compare different DIR algorithms with rigid image registration (RIR) by using the post hoc Wilcoxon signed-rank test for stratified metric comparison. RESULTS: A total of 2720 anatomic and 50 tumor and nodal ROIs were delineated. All DIR algorithms showed improved performance over RIR for anatomic and target ROI conformance, as shown for most comparison metrics (Steel test, P < .008 after Bonferroni correction). The performance of different algorithms varied substantially with stratification by specific anatomic structures or category and simulation CT section thickness. CONCLUSION: Development of a formal ROI-based QA workflow for registration assessment demonstrated improved performance with DIR techniques over RIR. After QA, DIR implementation should be the standard for head and neck diagnostic CT and simulation CT allineation, especially for target delineation.

Intravoxel incoherent motion imaging kinetics during chemoradiotherapy for human papillomavirus-associated squamous cell carcinoma of the oropharynx: preliminary results from a prospective pilot study.

This study aims to identify the temporal kinetics of intravoxel incoherent motion (IVIM) MRI in patients with human papillomavirus-associated (HPV+) oropharyngeal squamous cell carcinoma. Patients were enrolled under an Institutional Review Board (IRB)-approved protocol as part of an ongoing prospective clinical trial. All patients underwent two MRI studies: a baseline scan before chemoradiotherapy and a mid-treatment scan 3-4 weeks after treatment initiation. Parametric maps representing pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and apparent diffusion coefficient (ADC) were generated. The Mann-Whitney U-test was used to assess the temporal variation of IVIM metrics. Bayesian quadratic discriminant analysis (QDA) was used to evaluate the extent to which mid-treatment changes in IVIM metrics could be combined to predict sites that would achieve complete response (CR) in multivariate analysis. Thirty-one patients were included in the final analysis with 59 lesions. Pretreatment ADC and D values of the CR lesions (n = 19) were significantly lower than those of non-CR lesions (n = 33). Mid-treatment ADC, D and f values were significantly higher (p < 0.0001) than pretreatment values for all lesions. Each increase in normalized ΔADC of size 0.1 yielded a 1.45-fold increase in the odds of CR (p < 0.0003), each increase in normalized ΔD of size 0.1 yielded a 1.53-fold increase in the odds of CR (p < 0.0002), and each unit increase in Δf yielded a 2.29-fold increase in the odds of CR (p < 0.02). Combined ΔD and ΔADC were integrated into a multivariate prediction model and attained an AUC of 0.87 (95% confidence interval: 0.79, 0.96), as well as a sensitivity of 0.63, specificity of 0.85 and accuracy of 0.78, under leave-one-out cross-validation. In conclusion, IVIM is feasible and potentially useful in the prediction and assessment of the early response of HPV+ oropharyngeal squamous cell carcinoma to chemoradiotherapy.

Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor.

PURPOSE: To correlate patient survival with morphologic imaging features and hemodynamic parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along with clinical and genomic markers. MATERIALS AND METHODS: An institutional review board waiver was obtained for this HIPAA-compliant retrospective study. Forty-five patients with GBM underwent baseline imaging with contrast material-enhanced magnetic resonance (MR) imaging and dynamic susceptibility contrast-enhanced T2*-weighted perfusion MR imaging. Molecular and clinical predictors of survival were obtained. Single and multivariable models of overall survival (OS) and progression-free survival (PFS) were explored with Kaplan-Meier estimates, Cox regression, and random survival forests. RESULTS: Worsening OS (log-rank test, P = .0103) and PFS (log-rank test, P = .0223) were associated with increasing relative cerebral blood volume of NER (rCBVNER), which was higher with deep white matter involvement (t test, P = .0482) and poor NER margin definition (t test, P = .0147). NER crossing the midline was the only morphologic feature of NER associated with poor survival (log-rank test, P = .0125). Preoperative Karnofsky performance score (KPS) and resection extent (n = 30) were clinically significant OS predictors (log-rank test, P = .0176 and P = .0038, respectively). No genomic alterations were associated with survival, except patients with high rCBVNER and wild-type epidermal growth factor receptor (EGFR) mutation had significantly poor survival (log-rank test, P = .0306; area under the receiver operating characteristic curve = 0.62). Combining resection extent with rCBVNER marginally improved prognostic ability (permutation, P = .084). Random forest models of presurgical predictors indicated rCBVNER as the top predictor; also important were KPS, age at diagnosis, and NER crossing the midline. A multivariable model containing rCBVNER, age at diagnosis, and KPS can be used to group patients with more than 1 year of difference in observed median survival (0.49-1.79 years). CONCLUSION: Patients with high rCBVNER and NER crossing the midline and those with high rCBVNER and wild-type EGFR mutation showed poor survival. In multivariable survival models, however, rCBVNER provided unique prognostic information that went above and beyond the assessment of all NER imaging features, as well as clinical and genomic features.

Post-treatment imaging changes in primary brain tumors.

Discerning between primary brain tumor progression and treatment-related effect is a significant issue and a major challenge in neuro-oncology. The difficulty in differentiating tumor progression from treatment-related effects has important implications for treatment decisions and prognosis, as well as for clinical trial design and results. Conventional MRI is widely used to assess disease status, but cannot reliably distinguish between tumor progression and treatment-related effects. Several advanced imaging techniques are promising, but have yet to be prospectively validated for this use. This review explores two treatment-related effects, pseudoprogression and radiation necrosis, as well as the concept of pseudoresponse, and highlights several advanced imaging modalities and the evidence supporting their use in differentiating tumor progression from treatment-related effect.

Imaging mimics of primary malignant tumors of the central nervous system (CNS).

Imaging has become a central part of the evaluation of lesions of the central nervous system. Despite patterns of the appearances of several types of central nervous system malignancies and improving resolution of imaging techniques, there are other processes that can display similar characteristics. Time and again, vascular, inflammatory, and vascular lesions will mimic a neoplastic process, requiring tissue diagnosis. With the introduction of advanced magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging in the evaluation of the brain tumor, there has been improvement in determining whether a lesion is neoplastic, and further advances may lead to noninvasive pathological and molecular diagnoses.

Validation of a multiomic model of plasma extracellular vesicle PD-L1 and radiomics for prediction of response to immunotherapy in NSCLC.

BACKGROUND: Immune-checkpoint inhibitors (ICIs) have showed unprecedent efficacy in the treatment of patients with advanced non-small cell lung cancer (NSCLC). However, not all patients manifest clinical benefit due to the lack of reliable predictive biomarkers. We showed preliminary data on the predictive role of the combination of radiomics and plasma extracellular vesicle (EV) PD-L1 to predict durable response to ICIs. MAIN BODY: Here, we validated this model in a prospective cohort of patients receiving ICIs plus chemotherapy and compared it with patients undergoing chemotherapy alone. This multiparametric model showed high sensitivity and specificity at identifying non-responders to ICIs and outperformed tissue PD-L1, being directly correlated with tumor change. SHORT CONCLUSION: These findings indicate that the combination of radiomics and EV PD-L1 dynamics is a minimally invasive and promising biomarker for the stratification of patients to receive ICIs.

Associating T1-Weighted and T2-Weighted Magnetic Resonance Imaging Radiomic Signatures With Preoperative Symptom Severity in Patients With Cervical Spondylotic Myelopathy.

BACKGROUND: Preoperative symptom severity in cervical spondylotic myelopathy (CSM) can be variable. Radiomic signatures could provide an imaging biomarker for symptom severity in CSM. This study utilizes radiomic signatures of T1-weighted and T2-weighted magnetic resonance imaging images to correlate with preoperative symptom severity based on modified Japanese Orthopaedic Association (mJOA) scores for patients with CSM. METHODS: Sixty-two patients with CSM were identified. Preoperative T1-weighted and T2-weighted magnetic resonance imaging images for each patient were segmented from C2-C7. A total of 205 texture features were extracted from each volume of interest. After feature normalization, each second-order feature was further subdivided to yield a total of 400 features from each volume of interest for analysis. Supervised machine learning was used to build radiomic models. RESULTS: The patient cohort had a median mJOA preoperative score of 13; of which, 30 patients had a score of >13 (low severity) and 32 patients had a score of ≤13 (high severity). Radiomic analysis of T2-weighted imaging resulted in 4 radiomic signatures that correlated with preoperative mJOA with a sensitivity, specificity, and accuracy of 78%, 89%, and 83%, respectively (P < 0.004). The area under the curve value for the ROC curves were 0.69, 0.70, and 0.77 for models generated by independent T1 texture features, T1 and T2 texture features in combination, and independent T2 texture features, respectively. CONCLUSIONS: Radiomic models correlate with preoperative mJOA scores using T2 texture features in patients with CSM. This may serve as a surrogate, objective imaging biomarker to measure the preoperative functional status of patients.