A Bivalent Omicron-BA.4/BA.5-Adapted BNT162b2 Booster in ≥12-Year-Olds.

BACKGROUND: Protection against contemporary SARS-CoV-2 variants requires sequence-adapted vaccines. METHODS: In this ongoing phase 2/3 trial, 12-17-year-olds (n=108), 18-55-year-olds (n=313), and >55-year-olds (n=306) who previously received 3 original BNT162b2 30-µg doses, received a fourth dose (second booster) of 30-µg bivalent original/Omicron-BA.4/BA.5-adapted BNT162b2 (BNT162b2-Omi.BA.4/BA.5). For comparisons with original BNT162b2, participants were selected from another phase 3 trial. Immunologic superiority 1-month post-vaccination, with respect to 50% neutralizing titers (GMR lower bound [LB] 2-sided 95%CI >1), and noninferiority with respect to seroresponse rates (rate-difference LB 2-sided 95%CI >-5%), for Omicron BA.4/BA.5 were assessed in >55-year-olds versus original BNT162b2 as a second booster. Noninferiority with respect to neutralizing titer level (GMR LB 2-sided 95%CI >0.67) and seroresponse rate (rate-difference LB 2-sided 95%CI >-10%) of Omicron BA.4/BA.5 immune response for BNT162b2-Omi.BA.4/BA.5 in 18‒55-year-olds versus >55-year-olds was assessed. RESULTS: One-month post-vaccination in >55-year-olds, model-adjusted GMR of Omicron BA.4/BA.5 neutralizing titers for the BNT162b2-Omi.BA.4/BA.5 versus BNT162b2 group (2.91; 95%CI 2.45-3.44) demonstrated superiority of BNT162b2-Omi.BA.4/BA.5. Adjusted difference in percentages of >55-year-olds with seroresponse (26.77%; 95%CI 19.59-33.95) showed noninferiority of BNT162b2-Omi.BA.4/BA.5 to BNT162b2. Noninferiority of BNT162b2-Omi.BA.4/BA.5 in 18‒55-year-olds to >55-year-olds was met for model-adjusted GMR and seroresponse. GMTs in 12-17-year-olds increased from baseline to 1-month post-vaccination. The BNT162b2-Omi.BA.4/BA.5 safety profile was similar to booster doses of bivalent Omicron BA.1-modified BNT162b2 and original BNT162b2 reported in previous studies. CONCLUSIONS: Based on immunogenicity and safety data up to 1-month post-vaccination in participants who previously received 3 original BNT162b2 doses, a BNT162b2-Omi.BA.4/BA.5 30 µg booster has a favorable benefit-risk profile. CLINICAL TRIAL REGISTRATION: NCT05472038.

Imaging-based stratification of adult gliomas prognosticates survival and correlates with the 2021 WHO classification.

BACKGROUND: Because of the lack of global accessibility, delay, and cost-effectiveness of genetic testing, there is a clinical need for an imaging-based stratification of gliomas that can prognosticate survival and correlate with the 2021-WHO classification. METHODS: In this retrospective study, adult primary glioma patients with pre-surgery/pre-treatment MRI brain images having T2, FLAIR, T1, T1 post-contrast, DWI sequences, and survival information were included in TCIA training-dataset (n = 275) and independent validation-dataset (n = 200). A flowchart for imaging-based stratification of adult gliomas(IBGS) was created in consensus by three authors to encompass all adult glioma types. Diagnostic features used were T2-FLAIR mismatch sign, central necrosis with peripheral enhancement, diffusion restriction, and continuous cortex sign. Roman numerals (I, II, and III) denote IBGS types. Two independent teams of three and two radiologists, blinded to genetic, histology, and survival information, manually read MRI into three types based on the flowchart. Overall survival-analysis was done using age-adjusted Cox-regression analysis, which provided both hazard-ratio (HR) and area-under-curve (AUC) for each stratification system(IBGS and 2021-WHO). The sensitivity and specificity of each IBSG type were analyzed with cross-table to identify the corresponding 2021-WHO genotype. RESULTS: Imaging-based stratification was statistically significant in predicting survival in both datasets with good inter-observer agreement (age-adjusted Cox-regression, AUC > 0.5, k > 0.6, p < 0.001). IBGS type-I, type-II, and type-III gliomas had good specificity in identifying IDHmut 1p19q-codel oligodendroglioma (training - 97%, validation - 85%); IDHmut 1p19q non-codel astrocytoma (training - 80%, validation - 85.9%); and IDHwt glioblastoma (training - 76.5%, validation- 87.3%) respectively (p-value < 0.01). CONCLUSIONS: Imaging-based stratification of adult diffuse gliomas predicted patient survival and correlated well with 2021-WHO glioma classification.

MRI features predict tumor grade in isocitrate dehydrogenase (IDH)-mutant astrocytoma and oligodendroglioma.

PURPOSE: Nearly all literature for predicting tumor grade in astrocytoma and oligodendroglioma pre-dates the molecular classification system. We investigated the association between contrast enhancement, ADC, and rCBV with tumor grade separately for IDH-mutant astrocytomas and molecularly-defined oligodendrogliomas. METHODS: For this retrospective study, 44 patients with IDH-mutant astrocytomas (WHO grades II, III, or IV) and 39 patients with oligodendrogliomas (IDH-mutant and 1p/19q codeleted) (WHO grade II or III) were enrolled. Two readers independently assessed preoperative MRI for contrast enhancement, ADC, and rCBV. Inter-reader agreement was calculated, and statistical associations between MRI metrics and WHO grade were determined per reader. RESULTS: For IDH-mutant astrocytomas, both readers found a stepwise positive association between contrast enhancement and WHO grade (Reader A: OR 7.79 [1.97, 30.80], p = 0.003; Reader B: OR 6.62 [1.70, 25.82], p = 0.006); both readers found that ADC was negatively associated with WHO grade (Reader A: OR 0.74 [0.61, 0.90], p = 0.002); Reader B: OR 0.80 [0.66, 0.96], p = 0.017), and both readers found that rCBV was positively associated with WHO grade (Reader A: OR 2.33 [1.35, 4.00], p = 0.002; Reader B: OR 2.13 [1.30, 3.57], p = 0.003). For oligodendrogliomas, both readers found a positive association between contrast enhancement and WHO grade (Reader A: OR 15.33 [2.56, 91.95], p = 0.003; Reader B: OR 20.00 [2.19, 182.45], p = 0.008), but neither reader found an association between ADC or rCBV and WHO grade. CONCLUSIONS: Contrast enhancement predicts WHO grade for IDH-mutant astrocytomas and oligodendrogliomas. ADC and rCBV predict WHO grade for IDH-mutant astrocytomas, but not for oligodendrogliomas.

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.

Advance Care Planning Among Patients With Advanced Illness Presenting to the Emergency Department.

BACKGROUND: Advance care planning (ACP) benefits emergency department (ED) patients with advanced illness. Although Medicare implemented physician reimbursement for ACP discussions in 2016, early studies found limited uptake. OBJECTIVE: We conducted a pilot study to assess ACP documentation and billing to inform the development of ED-based interventions to increase ACP. METHODS: We conducted a retrospective chart review to quantify the proportion of ED patients with advanced illness with Physician Orders for Life-Sustaining Treatment (POLST) or coding of ACP discussion in the medical record. We surveyed a subset of patients via phone to evaluate ACP participation. RESULTS: Of 186 patients included in the chart review, 68 (37%) had a POLST and none had ACP discussions billed. Of 50 patients surveyed, 18 (36%) recalled prior ACP discussions. CONCLUSIONS: Given the low uptake of ACP discussions in ED patients with advanced illness, the ED may be an underused setting for interventions to increase ACP discussions and documentation.

Brain Tumor Segmentation for Multi-Modal MRI with Missing Information.

Deep convolutional neural networks (DCNNs) have shown promise in brain tumor segmentation from multi-modal MRI sequences, accommodating heterogeneity in tumor shape and appearance. The fusion of multiple MRI sequences allows networks to explore complementary tumor information for segmentation. However, developing a network that maintains clinical relevance in situations where certain MRI sequence(s) might be unavailable or unusual poses a significant challenge. While one solution is to train multiple models with different MRI sequence combinations, it is impractical to train every model from all possible sequence combinations. In this paper, we propose a DCNN-based brain tumor segmentation framework incorporating a novel sequence dropout technique in which networks are trained to be robust to missing MRI sequences while employing all other available sequences. Experiments were performed on the RSNA-ASNR-MICCAI BraTS 2021 Challenge dataset. When all MRI sequences were available, there were no significant differences in performance of the model with and without dropout for enhanced tumor (ET), tumor (TC), and whole tumor (WT) (p-values 1.000, 1.000, 0.799, respectively), demonstrating that the addition of dropout improves robustness without hindering overall performance. When key sequences were unavailable, the network with sequence dropout performed significantly better. For example, when tested on only T1, T2, and FLAIR sequences together, DSC for ET, TC, and WT increased from 0.143 to 0.486, 0.431 to 0.680, and 0.854 to 0.901, respectively. Sequence dropout represents a relatively simple yet effective approach for brain tumor segmentation with missing MRI sequences.

The landscape of brain tumor mimics in neuro-oncology practice.

BACKGROUND AND OBJECTIVE: Differentiating neoplastic and non-neoplastic brain lesions is essential to make management recommendations and convey prognosis, but the distinction between brain tumors and their mimics in practice may prove challenging. The aim of this study is to provide the incidence of brain tumor mimics in the neuro-oncology setting and describe this patient subset. METHODS: Retrospective study of adult patients referred to the Division of Neuro-oncology for a presumed diagnosis of brain tumor from January 1, 2005 through December 31, 2017, who later satisfied the diagnosis of a non-neoplastic entity based on neuroimaging, clinical course, and/or histopathology evaluation. We classified tumor mimic entities according to clinical, radiologic, and laboratory characteristics that correlated with the diagnosis. RESULTS: The incidence of brain tumor mimics was 3.4% (132/3897). The etiologies of the non-neoplastic entities were vascular (35%), inflammatory non-demyelinating (26%), demyelinating (15%), cysts (10%), infectious (9%), and miscellaneous (5%). In our study, 38% of patients underwent biopsy to determine diagnosis, but in 26%, the biopsy was inconclusive. DISCUSSION: Brain tumor mimics represent a small but important subset of the neuro-oncology referrals. Vascular, inflammatory, and demyelinating etiologies represent two-thirds of cases. Recognizing the clinical, radiologic and laboratory characteristics of such entities may improve resource utilization and prevent unnecessary as well as potentially harmful diagnostic and therapeutic interventions.

Extracting diffusion tensor fractional anisotropy and mean diffusivity from 3-direction DWI scans using deep learning.

PURPOSE: To develop and evaluate machine-learning methods that reconstruct fractional anisotropy (FA) values and mean diffusivities (MD) from 3-direction diffusion MRI (dMRI) acquisitions. METHODS: Two machine-learning models were implemented to map undersampled dMRI signals with high-quality FA and MD maps that were reconstructed from fully sampled DTI scans. The first model was a previously described multilayer perceptron (MLP), which maps signals and FA/MD values from a single voxel. The second was a convolutional neural network U-Net model, which maps dMRI slices to full FA/MD maps. Each method was trained on dMRI brain scans (N = 46), and reconstruction accuracies were compared with conventional linear-least-squares (LLS) reconstructions. RESULTS: In an independent testing cohort (N = 20), 3-direction U-Net reconstructions had significantly lower absolute FA error than both 3-direction MLP (U-Net3-dir : 0.06 ± 0.01 vs. MLP3-dir : 0.08 ± 0.01, P < 1 × 10-5 ) and 6-direction LLS (LLS6-dir : 0.09 ± 0.03, P = 1 × 10-5 ). The MD errors were not significantly different among 3-direction MLP (0.06 ± 0.01 × 10-3 mm2 /s), 3-direction U-Net (0.06 ± 0.01 × 10-3 mm2 /s), and 6-direction LLS (0.07 ± 0.02 × 10-3 mm2 /s, P > .1). CONCLUSION: The proposed U-Net model reconstructed FA from 3-direction dMRI scans with improved accuracy compared with both a previously described MLP approach and LLS fitting from 6-direction scans. The MD reconstruction accuracies did not differ significantly between reconstructions.

Fluid attenuation in non-contrast-enhancing tumor (nCET): an MRI Marker for Isocitrate Dehydrogenase (IDH) mutation in Glioblastoma.

PURPOSE: The WHO 2016 update classifies glioblastomas (WHO grade IV) according to isocitrate dehydrogenase (IDH) gene mutation status. We aimed to determine MRI-based metrics for predicting IDH mutation in glioblastoma. METHODS: This retrospective study included glioblastoma cases (n = 199) with known IDH mutation status and pre-operative MRI (T1WI, T2WI, FLAIR, contrast-enhanced T1W1 at minimum). Two neuroradiologists determined the following MRI metrics: (1) primary lobe of involvement (frontal or non-frontal); (2) presence/absence of contrast-enhancement; (3) presence/absence of necrosis; (4) presence/absence of fluid attenuation in the non-contrast-enhancing tumor (nCET); (5) maximum width of peritumoral edema (cm); (6) presence/absence of multifocal disease. Inter-reader agreement was determined. After resolving discordant measurements, multivariate association between consensus MRI metrics/patient age and IDH mutation status was determined. RESULTS: Among 199 glioblastomas, 16 were IDH-mutant. Inter-reader agreement was calculated for contrast-enhancement (ĸ = 0.49 [- 0.11-1.00]), necrosis (ĸ = 0.55 [0.34-0.76]), fluid attenuation in nCET (ĸ = 0.83 [0.68-0.99]), multifocal disease (ĸ = 0.55 [0.39-0.70]), and primary lobe (ĸ = 0.85 [0.80-0.91]). Mean difference for peritumoral edema width between readers was 0.3 cm [0.2-0.5], p < 0.001. Multivariate analysis uncovered significant associations between IDH-mutation and fluid attenuation in nCET (OR 82.9 [19.22, ∞], p < 0.001), younger age (OR 0.93 [0.86, 0.98], p = 0.009), frontal lobe location (OR 11.08 [1.14, 352.97], p = 0.037), and less peritumoral edema (OR 0.15 [0, 0.65], p = 0.044). CONCLUSIONS: Conventional MRI metrics and patient age predict IDH-mutation status in glioblastoma. Among MRI markers, fluid attenuation in nCET represents a novel marker with high inter-reader agreement that is strongly associated with Glioblastoma, IDH-mutant.

3D fast low-angle shot (FLASH) technique for 3T contrast-enhanced brain MRI in the inpatient and emergency setting: comparison with 3D magnetization-prepared rapid gradient echo (MPRAGE) technique.

PURPOSE: To retrospectively evaluate the diagnostic performance of a 1-min contrast-enhanced 3D-FLASH pulse sequence for detecting intracranial enhancing lesions compared to standard contrast-enhanced 3D-MPRAGE pulse sequence. METHODS: Contrast-enhanced 3D-FLASH (acquisition time 49 s) and contrast-enhanced 3D-MPRAGE (4 min 35 s) pulse sequences were performed consecutively in 110 inpatient/emergency department 3T MRI brain examinations and analyzed by two independent neuroradiologist readers. For each sequence, the readers recorded (1) number of enhancing intracranial lesions; (2) intracranial susceptibility artifact (presence or absence; mm depth of intracranial signal loss); and (3) motion artifact (none, mild, moderate, severe). Inter and intra-reader agreement and reader accuracy relative to a reference standard were determined, and sequence comparison with respect to susceptibility and motion artifacts was performed. RESULTS: There was substantial intra-reader, inter-sequence agreement [reader 1, κ = 0.70 (95% CI: [0.60, 0.81]); reader 2, κ = 0.70 (95% CI: [0.59, 0.82])] and substantial intra-sequence, inter-reader agreement [3D-MPRAGE assessment, κ = 0.76 (95% CI: [0.66, 0.86]); 3D-FLASH assessment, κ = 0.86 (95% CI: [0.77, 0.94]) for detection of intracranial enhancing lesions. For both readers, the diagnostic accuracy of 3D-FLASH and 3D-MPRAGE was similar (3D-MPRAGE: 86.4 and 88.1%; 3D-FLASH: 88.2 and 84.5%), with no inter-sequence diagnostic accuracy discordancy between the sequences for either reader. 3D-FLASH was associated with less susceptibility artifact (p < 0.001 both readers) and less motion artifact (p < 0.001 both readers). CONCLUSION: On 3T brain MRI in the inpatient and emergency department setting, 1-min 3D-FLASH pulse sequence achieved comparable diagnostic performance to 4.5 min 3D-MPRAGE pulse sequence for detecting enhancing intracranial lesions, with reduced susceptibility and motion artifacts.

MRI and CT Identify Isocitrate Dehydrogenase (IDH)-Mutant Lower-Grade Gliomas Misclassified to 1p/19q Codeletion Status with Fluorescence in Situ Hybridization.

Background Fluorescence in situ hybridization (FISH) is a standard method for 1p/19q codeletion testing in diffuse gliomas but occasionally renders erroneous results. Purpose To determine whether MRI/CT analysis identifies isocitrate dehydrogenase (IDH)-mutant gliomas misassigned to 1p/19q codeletion status with FISH. Materials and Methods Data in patients with IDH-mutant lower-grade gliomas (World Health Organization grade II/III) and 1p/19q codeletion status determined with FISH that were accrued from January 1, 2010 to October 1, 2017, were included in this retrospective study. Two neuroradiologist readers analyzed the pre-resection MRI findings (and CT findings, when available) to predict 1p/19q status (codeleted or noncodeleted) and provided a prediction confidence score (1 = low, 2 = moderate, 3 = high). Percentage concordance between the consensus neuroradiologist 1p/19q prediction and the FISH result was calculated. For gliomas where (a) consensus neuroradiologist 1p/19q prediction differed from the FISH result and (b) consensus neuroradiologist confidence score was 2 or greater, further 1p/19q testing was performed with chromosomal microarray analysis (CMA). Nine control specimens were randomly chosen from the remaining study sample for CMA. Percentage concordance between FISH and CMA among the CMA-tested cases was calculated. Results A total of 112 patients (median age, 38 years [interquartile range, 31-51 years]; 57 men) were evaluated (112 gliomas). Percentage concordance between the consensus neuroradiologist 1p/19q prediction and the FISH result was 84.8% (95 of 112; 95% confidence interval: 76.8%, 90.9%). Among the 17 neuroradiologist-FISH discordances, there were nine gliomas associated with a consensus neuroradiologist confidence score of 2 or greater. In six (66.7%) of these nine gliomas, the 1p/19q codeletion status as determined with CMA disagreed with the FISH result and agreed with the consensus neuroradiologist prediction. For the nine control specimens, there was 100% agreement between CMA and FISH for 1p/19q determination. Conclusion MRI and CT analysis can identify diffuse gliomas misassigned to 1p/19q codeletion status with fluorescence in situ hybridization (FISH). Further molecular testing should be considered for gliomas with discordant neuroimaging and FISH results. © RSNA, 2019 Online supplemental material is available for this article.

Automated apparent diffusion coefficient analysis for genotype prediction in lower grade glioma: association with the T2-FLAIR mismatch sign.

PURPOSE: The prognosis of lower grade glioma (LGG) patients depends (in large part) on both isocitrate dehydrogenase (IDH) gene mutation and chromosome 1p/19q codeletion status. IDH-mutant LGG without 1p/19q codeletion (IDHmut-Noncodel) often exhibit a unique imaging appearance that includes high apparent diffusion coefficient (ADC) values not observed in other subtypes. The purpose of this study was to develop an ADC analysis-based approach that can automatically identify IDHmut-Noncodel LGG. METHODS: Whole-tumor ADC metrics, including fractional tumor volume with ADC > 1.5 × 10-3mm2/s (VADC>1.5), were used to identify IDHmut-Noncodel LGG in a cohort of N = 134 patients. Optimal threshold values determined in this dataset were then validated using an external dataset containing N = 93 cases collected from The Cancer Imaging Archive. Classifications were also compared with radiologist-identified T2-FLAIR mismatch sign and evaluated concurrently to identify added value from a combined approach. RESULTS: VADC>1.5 classified IDHmut-Noncodel LGG in the internal cohort with an area under the curve (AUC) of 0.80. An optimal threshold value of 0.35 led to sensitivity/specificity = 0.57/0.93. Classification performance was similar in the validation cohort, with VADC>1.5 ≥ 0.35 achieving sensitivity/specificity = 0.57/0.91 (AUC = 0.81). Across both groups, 37 cases exhibited positive T2-FLAIR mismatch sign-all of which were IDHmut-Noncodel. Of these, 32/37 (86%) also exhibited VADC>1.5 ≥ 0.35, as did 23 additional IDHmut-Noncodel cases which were negative for T2-FLAIR mismatch sign. CONCLUSION: Tumor subregions with high ADC were a robust indicator of IDHmut-Noncodel LGG, with VADC>1.5 achieving > 90% classification specificity in both internal and validation cohorts. VADC>1.5 exhibited strong concordance with the T2-FLAIR mismatch sign and the combination of both parameters improved sensitivity in detecting IDHmut-Noncodel LGG.

Increased intratumoral infiltration in IDH wild-type lower-grade gliomas observed with diffusion tensor imaging.

PURPOSE: Diffuse lower grade gliomas (LGG) with isocitrate dehydrogenase (IDH) gene mutations (IDHMUT) have a distinct survival advantage compared with IDH wild-type (IDHWT) cases but the mechanism underlying this disparity is not well understood. Diffusion Tensor Imaging (DTI) has identified infiltrated non-enhancing tumor regions that are characterized by low isotropic (p) and high anisotropic (q) diffusion tensor components that associate with poor survival in glioblastoma. We hypothesized that similar regions are more prevalent in IDHWT (vs. IDHMUT) LGG. METHODS: p and q maps were reconstructed from preoperative DTI scans in N = 41 LGG patients with known IDH mutation and 1p/19q codeletion status. Enhancing and non-enhancing tumor volumes were autosegmented from standard (non-DTI) MRI scans. Percentage non-enhancing tumor volumes exhibiting low p and high q (Vinf) were then determined using threshold values (p = 2 × 10-3mm2/s, q = 3 × 10-4 mm2/s) and compared between IDHWT and IDHMUT LGG, and between IDHMUT LGG with and without 1p/19q codeletion. RESULTS: Vinf volumes were significantly larger in IDHWT LGG than in IDHMUT LGG (35.4 ± 18.3% vs. 15.9 ± 7.6%, P < 0.001). Vinf volumes did not significantly differ between IDHMUT LGG with and without 1p/19q codeletion (17.1 ± 9.5% vs. 14.8 ± 5.8%, P = 1.0). CONCLUSION: IDHWT LGG exhibited larger volumes with suppressed isotropic diffusion (p) and high anisotropic diffusion (q) which reflects regions with increased cell density but non-disrupted neuronal structures. This may indicate a greater prevalence of infiltrative tumor in IDHWT LGG.

Oligodendroglioma confers higher risk of radiation necrosis.

BACKGROUND: Radiation therapy (RT) remains a mainstay for the treatment of lower grade gliomas. Radiation neurotoxicity is a serious complication, carrying high morbidity in the absence of tumor progression. The incidence remains poorly categorized and known risk factors identified are related to the radiation modality. We hypothesized that patients with oligodendroglioma have a higher risk of radiation necrosis (RN) as compared to patients with astrocytoma. METHODS: We conducted a retrospective review of adults with lower grade diffuse gliomas over a 10-year span. The primary outcome was RN, either pathologically confirmed or clinically diagnosed. Cases without pathological confirmation must have been symptomatic, requiring administration of bevacizumab or high-dose steroids. Cox proportional hazard ratios were used for multivariate analyses. RESULTS: In 319 patients, we identified RN in 41 patients (12.9%): 28 patients (21.3%) with oligodendroglioma and 13 (6.9%) with astrocytoma (HR 3.42, p < 0.001). Patients with oligodendroglioma who received > 54 Gy had a higher incidence (31.2%) than those receiving ≤ 54 Gy (14.3%, HR 6.9, p = 0.002). There was no similar correlation among patients with astrocytoma. There was no difference in incidence based on use of concomitant temozolomide. Radiation necrosis appeared within 24 months from radiation in 80.5% of patients. CONCLUSION: Our study suggests that patients with oligodendroglioma are at higher risk of developing RN. The incidence increases with increasing radiation dose in patients with oligodendroglioma but not with astrocytoma. RN usually appears within 24 months from RT. Patients with oligodendroglioma receiving > 54 Gy are at highest risk.

Tumor pharmacokinetics and pharmacodynamics of the CDK4/6 inhibitor ribociclib in patients with recurrent glioblastoma.

INTRODUCTION: We conducted a phase Ib study (NCT02345824) to determine whether ribociclib, an inhibitor of cyclin-dependent kinases 4 and 6 (CDK4/6), penetrates tumor tissue and modulates downstream signaling pathways including retinoblastoma protein (Rb) in patients with recurrent glioblastoma (GBM). METHODS: Study participants received ribociclib (600 mg QD) for 8-21 days before surgical resection of their recurrent GBM. Total and unbound concentrations of ribociclib were measured in samples of tumor tissue, plasma, and cerebrospinal fluid (CSF). We analyzed tumor specimens obtained from the first (initial/pre-study) and second (recurrent/on-study) surgery by immunohistochemistry for Rb status and downstream signaling of CDK4/6 inhibition. Participants with Rb-positive recurrent tumors continued ribociclib treatment on a 21-day-on, 7-day-off schedule after surgery, and were monitored for toxicity and disease progression. RESULTS: Three participants with recurrent Rb-positive GBM participated in this study. Mean unbound (pharmacologically active) ribociclib concentrations in plasma, CSF, MRI-enhancing, MRI-non-enhancing, and tumor core regions were 0.337 µM, 0.632 µM, 1.242 nmol/g, 0.484 nmol/g, and 1.526 nmol/g, respectively, which exceeded the in vitro IC50 (0.04 µM) for inhibition of CDK4/6 in cell-free assay. Modulation of pharmacodynamic markers of ribociclib CDK 4/6 inhibition in tumor tissues were inconsistent between study participants. No participants experienced serious adverse events, but all experienced early disease progression. CONCLUSIONS: This study suggests that ribociclib penetrated recurrent GBM tissue at concentrations predicted to be therapeutically beneficial. Our study was unable to demonstrate tumor pharmacodynamic correlates of drug activity. Although well tolerated, ribociclib monotherapy seemed ineffective for the treatment of recurrent GBM.

There is an exception to every rule-T2-FLAIR mismatch sign in gliomas.

The T2-FLAIR mismatch sign, in which a low-grade glioma is hyperintense on T2-weighted MR and centrally hypointense on T2-weighted FLAIR MR, has been reported as 100% specific for IDH-mutant astrocytomas in several series. We report several cases of "false positive" T2-FLAIR mismatch sign occurring outside the context of IDH-mutant astrocytomas, predominantly in children or young adults with pediatric-type gliomas. These results suggest caution in the interpretation of the T2-FLAIR mismatch sign in the pediatric glioma population.

MR imaging phenotype correlates with extent of genome-wide copy number abundance in IDH mutant gliomas.

PURPOSE: There is variability in survival within IDH mutant gliomas determined by chromosomal events. Copy number variation (CNV) abundance associated with survival in low-grade and IDH mutant astrocytoma has been reported. Our purpose was to correlate the extent of genome-wide CNV abundance in IDH mutant astrocytomas with MRI features. METHODS: Presurgical MRI and CNV plots derived from Illumina 850k EPIC DNA methylation arrays of 18 cases of WHO grade II-IV IDH mutant astrocytomas were reviewed. IDH mutant astrocytomas were divided into CNV stable group (CNV-S) with ≤ 3 chromosomal gains or losses and lack of focal gene amplifications and CNV unstable group (CNV-U) with > 3 large chromosomal gains/losses and/or focal amplifications. The associations between MR features, relative cerebral blood volume (rCBV), CNV abundance, and time to progression were assessed. Tumor rCBV estimates were obtained using DSC T2* perfusion analysis. RESULTS: There were nine (50%) CNV-S and nine (50%) CNV-U IDH mutant astrocytomas. CNV-U tumors showed larger mean tumor size (P = 0.004) and maximum diameter on FLAIR (P = 0.004) and also demonstrated significantly higher median rCBV than CNV-S tumors (2.62 vs 0.78, P = 0.019). CNV-U tumors tended to have shorter time to progression although without statistical significance (P = 0.393). CONCLUSIONS: Larger size/diameter and higher rCBVs were seen associated CNV-U astrocytomas, suggesting a correlation of aggressive imaging phenotype with unstable and aggressive genotype in IDH mutant astrocytomas.

Heuristics and Cognitive Error in Medical Imaging.

OBJECTIVE: The field of cognitive science has provided important insights into mental processes underlying the interpretation of imaging examinations. Despite these insights, diagnostic error remains a major obstacle in the goal to improve quality in radiology. In this article, we describe several types of cognitive bias that lead to diagnostic errors in imaging and discuss approaches to mitigate cognitive biases and diagnostic error. CONCLUSION: Radiologists rely on heuristic principles to reduce complex tasks of assessing probabilities and predicting values into simpler judgmental operations. These mental shortcuts allow rapid problem solving based on assumptions and past experiences. Heuristics used in the interpretation of imaging studies are generally helpful but can sometimes result in cognitive biases that lead to significant errors. An understanding of the causes of cognitive biases can lead to the development of educational content and systematic improvements that mitigate errors and improve the quality of care provided by radiologists.