Neuropsychiatric symptoms and brain morphology in patients with mild cognitive impairment, cerebrovascular disease and Parkinson disease: A cross sectional and longitudinal study.

OBJECTIVES: Neuropsychiatric symptoms (NPS) increase risk of developing dementia and are linked to various neurodegenerative conditions, including mild cognitive impairment (MCI due to Alzheimer's disease [AD]), cerebrovascular disease (CVD), and Parkinson's disease (PD). We explored the structural neural correlates of NPS cross-sectionally and longitudinally across various neurodegenerative diagnoses. METHODS: The study included individuals with MCI due to AD, (n = 74), CVD (n = 143), and PD (n = 137) at baseline, and at 2-years follow-up (MCI due to AD, n = 37, CVD n = 103, and PD n = 84). We assessed the severity of NPS using the Neuropsychiatric Inventory Questionnaire. For brain structure we included cortical thickness and subcortical volume of predefined regions of interest associated with corticolimbic and frontal-executive circuits. RESULTS: Cross-sectional analysis revealed significant negative correlations between appetite with both circuits in the MCI and CVD groups, while apathy was associated with these circuits in both the MCI and PD groups. Longitudinally, changes in apathy scores in the MCI group were negatively linked to the changes of the frontal-executive circuit. In the CVD group, changes in agitation and nighttime behavior were negatively associated with the corticolimbic and frontal-executive circuits, respectively. In the PD group, changes in disinhibition and apathy were positively associated with the corticolimbic and frontal-executive circuits, respectively. CONCLUSIONS: The observed correlations suggest that underlying pathological changes in the brain may contribute to alterations in neural activity associated with MBI. Notably, the difference between cross-sectional and longitudinal results indicates the necessity of conducting longitudinal studies for reproducible findings and drawing robust inferences.

Link among apolipoprotein E E4, gait, and cognition in neurodegenerative diseases: ONDRI study.

INTRODUCTION: Apolipoprotein E E4 allele (APOE E4) and slow gait are independently associated with cognitive impairment and dementia. However, it is unknown whether their coexistence is associated with poorer cognitive performance and its underlying mechanism in neurodegenerative diseases. METHODS: Gait speed, APOE E4, cognition, and neuroimaging were assessed in 480 older adults with neurodegeneration. Participants were grouped by APOE E4 presence and slow gait. Mediation analyses were conducted to determine if brain structures could explain the link between these factors and cognitive performance. RESULTS: APOE E4 carriers with slow gait had the lowest global cognitive performance and smaller gray matter volumes compared to non-APOE E4 carriers with normal gait. Coexistence of APOE E4 and slow gait best predicted global and domain-specific poorer cognitive performances, mediated by smaller gray matter volume. DISCUSSION: Gait slowness in APOE E4 carriers with neurodegenerative diseases may indicate extensive gray matter changes associated with poor cognition. HIGHLIGHTS: APOE E4 and slow gait are risk factors for cognitive decline in neurodegenerative diseases. Slow gait and smaller gray matter volumes are associated, independently of APOE E4. Worse cognition in APOE E4 carriers with slow gait is explained by smaller GM volume. Gait slowness in APOE E4 carriers indicates poorer cognition-related brain changes.

Perivascular spaces, plasma GFAP, and speeded executive function in neurodegenerative diseases.

INTRODUCTION: We investigated the effect of perivascular spaces (PVS) volume on speeded executive function (sEF), as mediated by white matter hyperintensities (WMH) volume and plasma glial fibrillary acidic protein (GFAP) in neurodegenerative diseases. METHODS: A mediation analysis was performed to assess the relationship between neuroimaging markers and plasma biomarkers on sEF in 333 participants clinically diagnosed with Alzheimer's disease/mild cognitive impairment, frontotemporal dementia, or cerebrovascular disease from the Ontario Neurodegenerative Disease Research Initiative. RESULTS: PVS was significantly associated with sEF (c = -0.125 ± 0.054, 95% bootstrap confidence interval [CI] [-0.2309, -0.0189], p = 0.021). This effect was mediated by both GFAP and WMH. DISCUSSION: In this unique clinical cohort of neurodegenerative diseases, we demonstrated that the effect of PVS on sEF was mediated by the presence of elevated plasma GFAP and white matter disease. These findings highlight the potential utility of imaging and plasma biomarkers in the current landscape of therapeutics targeting dementia. HIGHLIGHTS: Perivascular spaces (PVS) and white matter hyperintensities (WMH) are imaging markers of small vessel disease. Plasma glial fibrillary protein acidic protein (GFAP) is a biomarker of astroglial injury. PVS, WMH, and GFAP are relevant in executive dysfunction from neurodegeneration. PVS's effect on executive function was mediated by GFAP and white matter disease.

ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI.

Deep artificial neural networks (DNNs) have moved to the forefront of medical image analysis due to their success in classification, segmentation, and detection challenges. A principal challenge in large-scale deployment of DNNs in neuroimage analysis is the potential for shifts in signal-to-noise ratio, contrast, resolution, and presence of artifacts from site to site due to variances in scanners and acquisition protocols. DNNs are famously susceptible to these distribution shifts in computer vision. Currently, there are no benchmarking platforms or frameworks to assess the robustness of new and existing models to specific distribution shifts in MRI, and accessible multi-site benchmarking datasets are still scarce or task-specific. To address these limitations, we propose ROOD-MRI: a novel platform for benchmarking the Robustness of DNNs to Out-Of-Distribution (OOD) data, corruptions, and artifacts in MRI. This flexible platform provides modules for generating benchmarking datasets using transforms that model distribution shifts in MRI, implementations of newly derived benchmarking metrics for image segmentation, and examples for using the methodology with new models and tasks. We apply our methodology to hippocampus, ventricle, and white matter hyperintensity segmentation in several large studies, providing the hippocampus dataset as a publicly available benchmark. By evaluating modern DNNs on these datasets, we demonstrate that they are highly susceptible to distribution shifts and corruptions in MRI. We show that while data augmentation strategies can substantially improve robustness to OOD data for anatomical segmentation tasks, modern DNNs using augmentation still lack robustness in more challenging lesion-based segmentation tasks. We finally benchmark U-Nets and vision transformers, finding robustness susceptibility to particular classes of transforms across architectures. The presented open-source platform enables generating new benchmarking datasets and comparing across models to study model design that results in improved robustness to OOD data and corruptions in MRI.

White matter hyperintensity burden predicts cognitive but not motor decline in Parkinson's disease: results from the Ontario Neurodegenerative Diseases Research Initiative.

BACKGROUND AND PURPOSE: The pathophysiology of Parkinson's disease (PD) negatively affects brain network connectivity, and in the presence of brain white matter hyperintensities (WMHs) cognitive and motor impairments seem to be aggravated. However, the role of WMHs in predicting accelerating symptom worsening remains controversial. The objective was to investigate whether location and segmental brain WMH burden at baseline predict cognitive and motor declines in PD after 2 years. METHODS: Ninety-eight older adults followed longitudinally from Ontario Neurodegenerative Diseases Research Initiative with PD of 3-8 years in duration were included. Percentages of WMH volumes at baseline were calculated by location (deep and periventricular) and by brain region (frontal, temporal, parietal, occipital lobes and basal ganglia + thalamus). Cognitive and motor changes were assessed from baseline to 2-year follow-up. Specifically, global cognition, attention, executive function, memory, visuospatial abilities and language were assessed as were motor symptoms evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III, spatial-temporal gait variables, Freezing of Gait Questionnaire and Activities Specific Balance Confidence Scale. RESULTS: Regression analysis adjusted for potential confounders showed that total and periventricular WMHs at baseline predicted decline in global cognition (p < 0.05). Also, total WMH burden predicted the decline of executive function (p < 0.05). Occipital WMH volumes also predicted decline in global cognition, visuomotor attention and visuospatial memory declines (p < 0.05). WMH volumes at baseline did not predict motor decline. CONCLUSION: White matter hyperintensity burden at baseline predicted cognitive but not motor decline in early to mid-stage PD. The motor decline observed after 2 years in these older adults with PD is probably related to the primary neurodegenerative process than comorbid white matter pathology.

Rare neurovascular genetic and imaging markers across neurodegenerative diseases.

INTRODUCTION: Cerebral small vessel disease (SVD) is common in patients with cognitive impairment and neurodegenerative diseases such as Alzheimer's and Parkinson's. This study investigated the burden of magnetic resonance imaging (MRI)-based markers of SVD in patients with neurodegenerative diseases as a function of rare genetic variant carrier status. METHODS: The Ontario Neurodegenerative Disease Research Initiative study included 520 participants, recruited from 14 tertiary care centers, diagnosed with various neurodegenerative diseases and determined the carrier status of rare non-synonymous variants in five genes (ABCC6, COL4A1/COL4A2, NOTCH3/HTRA1). RESULTS: NOTCH3/HTRA1 were found to significantly influence SVD neuroimaging outcomes; however, the mechanisms by which these variants contribute to disease progression or worsen clinical correlates are not yet understood. DISCUSSION: Further studies are needed to develop genetic and imaging neurovascular markers to enhance our understanding of their potential contribution to neurodegenerative diseases.

Perivascular spaces mediate a relationship between diabetes and other cerebral small vessel disease markers in cerebrovascular and neurodegenerative diseases.

Type 2 diabetes mellitus (T2DM) and hypertension are risk factors for cerebral small vessel disease (SVD); however, few studies have characterised their relationships with MRI-visible perivascular spaces (PVS). MRI was used to quantify deep (d) and periventricular (p) white matter hyperintensities (WMH), lacunes, PVS in the white matter (wmPVS) or basal ganglia (bgPVS), and diffusion metrics in white matter. Patients with T2DM had greater wmPVS volume and there were greater wmPVS volumes in patients with T2DM and hypertension together. Counterfactual moderated mediation models found indirect effects of T2DM on volumes of other SVD and diffusion markers that were mediated by wmPVS: pWMH, dWMH, periventricular lacunes, and deep lacunes, and progression of deep lacunes over 1 year, in patients with hypertension, but not in patients without hypertension. Studying the regulation of cortical perivascular fluid dynamics may reveal mechanisms that mediate the impact of T2DM on cerebral small vessels.

Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation.

White matter hyperintensities (WMHs) are frequently observed on structural neuroimaging of elderly populations and are associated with cognitive decline and increased risk of dementia. Many existing WMH segmentation algorithms produce suboptimal results in populations with vascular lesions or brain atrophy, or require parameter tuning and are computationally expensive. Additionally, most algorithms do not generate a confidence estimate of segmentation quality, limiting their interpretation. MRI-based segmentation methods are often sensitive to acquisition protocols, scanners, noise-level, and image contrast, failing to generalize to other populations and out-of-distribution datasets. Given these concerns, we propose a novel Bayesian 3D convolutional neural network with a U-Net architecture that automatically segments WMH, provides uncertainty estimates of the segmentation output for quality control, and is robust to changes in acquisition protocols. We also provide a second model to differentiate deep and periventricular WMH. Four hundred thirty-two subjects were recruited to train the CNNs from four multisite imaging studies. A separate test set of 158 subjects was used for evaluation, including an unseen multisite study. We compared our model to two established state-of-the-art techniques (BIANCA and DeepMedic), highlighting its accuracy and efficiency. Our Bayesian 3D U-Net achieved the highest Dice similarity coefficient of 0.89 ± 0.08 and the lowest modified Hausdorff distance of 2.98 ± 4.40 mm. We further validated our models highlighting their robustness on "clinical adversarial cases" simulating data with low signal-to-noise ratio, low resolution, and different contrast (stemming from MRI sequences with different parameters). Our pipeline and models are available at: https://hypermapp3r.readthedocs.io.

Small and Large Magnetic Resonance Imaging-Visible Perivascular Spaces in the Basal Ganglia of Parkinson's Disease Patients.

BACKGROUND: Although previously thought to be asymptomatic, recent studies have suggested that magnetic resonance imaging-visible perivascular spaces (PVS) in the basal ganglia (BG-PVS) of patients with Parkinson's disease (PD) may be markers of motor disability and cognitive decline. In addition, a pathogenic and risk profile difference between small (≤3-mm diameter) and large (>3-mm diameter) PVS has been suggested. OBJECTIVE: The aim of this study was to examine associations between quantitative measures of large and small BG-PVS, global cognition, and motor/nonmotor features in a multicenter cohort of patients with PD. METHODS: We performed a cross-sectional study examining the association between large and small BG-PVS with Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts I-IV and cognition (Montreal Cognitive Assessment) in 133 patients with PD enrolled in the Ontario Neurodegenerative Disease Research Initiative study. RESULTS: Patients with PD with small BG-PVS demonstrated an association with MDS-UPDRS Parts I (P = 0.008) and II (both P = 0.02), whereas patients with large BG-PVS demonstrated an association with MDS-UPDRS Parts III (P < 0.0001) and IV (P < 0.001). BG-PVS were not correlated with cognition. CONCLUSIONS: Small BG-PVS are associated with motor and nonmotor aspects of experiences in daily living, while large BG-PVS are associated with the motor symptoms and motor complications. © 2022 International Parkinson and Movement Disorder Society.

Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study.

Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies.

Diagnostic Neuroradiology Subspecialty Training: 1 Versus 2 Years; the Canadian Perspective.

BACKGROUND: Canada began a national reform of its post-graduate medical education training programs to a Competence By Design (CBD) model. Trends from accredited neuroradiology programs from the past 10 years were investigated to inform educators and stakeholders for this process. METHODS: A 13-question electronic survey was sent to program directors of all 8 accredited neuroradiology training programs in Canada. Data was requested for each year on the 2008-2019 graduating classes. Questions pertained to program enrolment; program completion; post-training employment; and the sufficiency of 1-year training programs. RESULTS: Response rate was 100%. Over the timeframe studied, the 2-year programs increased in size (P = 0.007), while the 1-year programs remained steady (P = 0.27). 12.2% of trainees enrolled in the 2-year program dropped out after 1 year, and were considered 1-year trainees thereafter. A higher proportion of 2-year trainees obtain positions within academic institutions (89.5 vs 67.2%, P = 0.0007), whereas a higher proportion of 1-year trainees obtain positions within non-academic institutions (29.3 vs 8.1%, P = 0.0007). A higher proportion of those with Canadian board certification in diagnostic radiology who completed a 2-year program obtained a position within a Canadian academic institution compared to non-certified 2-year trainees (P < 0.001). 71.4% of program directors agreed that a 1-year program was sufficient for non-academic staff positions. CONCLUSION: The length of the training program has significant impact on employment in academic vs non-academic institutions. This information can be used to guide the upcoming CBD initiative for neuroradiology programs.

Parkinson's Disease, NOTCH3 Genetic Variants, and White Matter Hyperintensities.

BACKGROUND: White matter hyperintensities (WMH) on magnetic resonance imaging may influence clinical presentation in patients with Parkinson's disease (PD), although their significance and pathophysiological origins remain unresolved. Studies examining WMH have identified pathogenic variants in NOTCH3 as an underlying cause of inherited forms of cerebral small vessel disease. METHODS: We examined NOTCH3 variants, WMH volumes, and clinical correlates in 139 PD patients in the Ontario Neurodegenerative Disease Research Initiative cohort. RESULTS: We identified 13 PD patients (~9%) with rare (<1% of general population), nonsynonymous NOTCH3 variants. Bayesian linear modeling demonstrated a doubling of WMH between variant negative and positive patients (3.1 vs. 6.9 mL), with large effect sizes for periventricular WMH (d = 0.8) and lacunes (d = 1.2). Negative correlations were observed between WMH and global cognition (r = -0.2). CONCLUSION: The NOTCH3 rare variants in PD may significantly contribute to increased WMH burden, which in turn may negatively influence cognition. © 2020 International Parkinson and Movement Disorder Society.

Hypoxia Detection in Infiltrative Astrocytoma: Ferumoxytol-based Quantitative BOLD MRI with Intraoperative and Histologic Validation.

Purpose To validate ferumoxytol-based quantitative blood oxygenation level-dependent (BOLD) MRI for mapping oxygenation of human infiltrative astrocytomas by using intraoperative measurement of tissue oxygen tension and histologic staining. Materials and Methods Fifteen patients with infiltrative astrocytomas were recruited into this prospective multicenter study between July 2014 and December 2016. Prior to treatment, participants underwent preoperative quantitative BOLD MRI with ferumoxytol to generate tissue oxygen saturation (StO2) maps. Two intratumoral sites were identified, one with low StO2 and one with high StO2. Neuronavigation was used to locate sites intraoperatively for insertion of oxygen-sensing probes to measure local tissue oxygen tension (PtO2). Biopsies from both sites were taken and stained for markers of hypoxia (hypoxia-inducible factor 1α, carbonic anhydrase IX) and neoangiogenesis (vascular endothelial growth factor, endoglin [CD105]). Spearman correlation and nonparametric sign-rank tests were used to analyze data. Results Ten patients with median age of 58.5 years (interquartile range, 25 years; four men and six women) completed the study. Because there is no linear relationship between StO2 and PtO2, the ratios of low to high StO2 versus low to high PtO2 in each patient were compared and a significant correlation was found (r = 0.73; P = .01). Pathologic analyses revealed differences between carbonic anhydrase IX (P = .03) for sites of low StO2 versus high StO2. CD105 displayed a similar trend but was not significant (P = .09). Conclusion Ferumoxytol-based quantitative blood oxygenation level-dependent MRI can potentially be used as a noninvasive surrogate for oxygenation mapping in infiltrative astrocytomas. This technique can potentially be integrated in treatment planning for aggressive targeting of hypoxic areas in tumors.

Differentiating radiation necrosis from tumor progression in brain metastases treated with stereotactic radiotherapy: utility of intravoxel incoherent motion perfusion MRI and correlation with histopathology.

Radiation necrosis is a serious potential adverse event of stereotactic radiosurgery that cannot be reliably differentiated from recurrent tumor using conventional imaging techniques. Intravoxel incoherent motion (IVIM) is a magnetic resonance imaging (MRI) based method that uses a diffusion-weighted sequence to estimate quantitative perfusion and diffusion parameters. This study evaluated the IVIM-derived apparent diffusion coefficient (ADC) and perfusion fraction (f), and compared the results to the gold standard histopathological-defined outcomes of radiation necrosis or recurrent tumor. Nine patients with ten lesions were included in this study; all lesions exhibited radiographic progression after stereotactic radiosurgery for brain metastases that subsequently underwent surgical resection due to uncertainty regarding the presence of radiation necrosis versus recurrent tumor. Pre-surgical IVIM was performed to obtain f and ADC values and the results were compared to histopathology. Five lesions exhibited pathological radiation necrosis and five had predominantly recurrent tumor. The IVIM perfusion fraction reliably differentiated tumor recurrence from radiation necrosis (fmean = 10.1 ± 0.7 vs. 8.3 ± 1.2, p = 0.02; cutoff value of 9.0 yielding a sensitivity/specificity of 100%/80%) while the ADC did not distinguish between the two (ADCmean = 1.1 ± 0.2 vs. 1.2 ± 0.4, p = 0.6). IVIM shows promise in differentiating recurrent tumor from radiation necrosis for brain metastases treated with radiosurgery, but needs to be validated in a larger cohort.

Temporal evolution of perfusion parameters in brain metastases treated with stereotactic radiosurgery: comparison of intravoxel incoherent motion and dynamic contrast enhanced MRI.

Intravoxel incoherent motion (IVIM) is a magnetic resonance imaging (MRI) technique that is seeing increasing use in neuro-oncology and offers an alternative to contrast-enhanced perfusion techniques for evaluation of tumor blood volume after stereotactic radiosurgery (SRS). To date, IVIM has not been validated against contrast enhanced techniques for brain metastases after SRS. In the present study, we measure blood volume for 20 brain metastases (15 patients) at baseline, 1 week and 1 month after SRS using IVIM and dynamic contrast enhanced (DCE)-MRI. Correlation between blood volume measurements made with IVIM and DCE-MRI show poor correlation at baseline, 1 week, and 1 month post SRS (r = 0.33, 0.14 and 0.30 respectively). At 1 week after treatment, no significant change in tumor blood volume was found using IVIM or DCE-MRI (p = 0.81 and 0.41 respectively). At 1 month, DCE-MRI showed a significant decrease in blood volume (p = 0.0002). IVIM, on the other hand, demonstrated the opposite effect and showed a significant increase in blood volume at 1 month (p = 0.03). The results of this study indicate that blood volume measured with IVIM and DCE-MRI are not equivalent. While this may relate to differences in the type of perfusion information each technique is providing, it could also reflect a limitation of tumor blood volume measurements made with IVIM after SRS. IVIM measurements of tumor blood volume in the month after SRS should therefore be interpreted with caution.

The Ontario Neurodegenerative Disease Research Initiative (ONDRI).

Because individuals develop dementia as a manifestation of neurodegenerative or neurovascular disorder, there is a need to develop reliable approaches to their identification. We are undertaking an observational study (Ontario Neurodegenerative Disease Research Initiative [ONDRI]) that includes genomics, neuroimaging, and assessments of cognition as well as language, speech, gait, retinal imaging, and eye tracking. Disorders studied include Alzheimer's disease, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson's disease, and vascular cognitive impairment. Data from ONDRI will be collected into the Brain-CODE database to facilitate correlative analysis. ONDRI will provide a repertoire of endophenotyped individuals that will be a unique, publicly available resource.

Perfusion reduction in the absence of structural differences in cognitively impaired versus unimpaired RRMS patients.

BACKGROUND: Cognitive impairment affects 40%-68% of relapsing-remitting multiple sclerosis (RRMS) patients. Gray matter (GM) demyelination is complicit in cognitive impairment, yet cortical lesions are challenging to image clinically. We wanted to determine whether cortical cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) differences exist between cognitively impaired (CI) and unimpaired (NI) RRMS. METHODS: Prospective study of healthy controls (n = 19), CI (n = 20), and NI (n = 19) undergoing magnetic resonance imaging (MRI) and cognitive testing <1 week apart. White matter (WM) T2 hyperintense lesions and T1 black holes were traced. General linear regression assessed the relationship between lobar WM volume and cortical and WM CBF, CBV, and MTT. Relationship between global and lobar cortical CBF, CBV, and MTT and cognitive impairment was tested using a generalized linear model. Adjusted Bonferroni p < 0.005 was considered significant. RESULTS: No significant differences for age, gender, disease duration, and any fractional brain or lesion volume were demonstrated for RRMS subgroups. Expanded Disability Status Scale (EDSS) and Hospital Anxiety and Depression Scale-Depression (HADS-D) were higher in CI. Lobar cortical CBF and CBV were associated with cognitive impairment (p < 0.0001) after controlling for confounders. Cortical CBV accounted for 7.2% of cognitive impairment increasing to 8.7% with cortical CBF (p = 0.06), while WM and cortical CBF accounted for 8.2% of variance (p = 0.04). CONCLUSION: Significant cortical CBF and CBV reduction was present in CI compared to NI in the absence of structural differences.

Radiologic Differences between Human Papillomavirus-Related and Human Papillomavirus-Unrelated Oropharyngeal Carcinoma on Diffusion-Weighted Imaging.

BACKGROUND AND PURPOSE: Human papilloma virus-related oropharyngeal carcinoma (HPV+ OPC) is a unique entity compared to HPV-unrelated (HPV-) OPC. Previous studies were inconclusive regarding the differences between HPV+ and HPV- OPCs on diffusion-weighted imaging (DWI). This study sought to determine if there is an association between HPV status and apparent diffusion coefficient (ADC) values as an imaging biomarker in OPCs. MATERIALS AND METHODS: OPC patients with pretreatment MRI including DWI were retrospectively reviewed and analyzed as a blinded, controlled cohort. HPV status was biopsy-ascertained with p16 staining. ADC values were determined by placing the largest possible circular region of interest in solid portions of primary tumors and/or metastatic lymph nodes. Necrotic and cystic portions were excluded. RESULTS: Twenty-eight HPV+ and 12 HPV- patients were included. Adjusted for age and sex, ADC values were significantly lower in HPV+ OPC primary tumors (p = 0.013) and lymph node metastases (p = 0.013). The area under the curve (AUC) was 0.85 and 0.90, respectively. A model with a linear combination of the 2 variables yielded an AUC of 0.92. CONCLUSION: ADC values were significantly lower in both the primary tumors and lymph node metastases in HPV+ OPCs compared to HPV- OPCs. These results confirm the results of prior studies.

Validation of the 9-Point and 24-Point Hematoma Expansion Prediction Scores and Derivation of the PREDICT A/B Scores.

BACKGROUND AND PURPOSE: Nine- and 24-point prediction scores have recently been published to predict hematoma expansion (HE) in acute intracerebral hemorrhage. We sought to validate these scores and perform an independent analysis of HE predictors. METHODS: We retrospectively studied 301 primary or anticoagulation-associated intracerebral hemorrhage patients presenting <6 hours post ictus prospectively enrolled in the Predicting Hematoma Growth and Outcome in Intracerebral Hemorrhage Using Contrast Bolus Computed Tomography (PREDICT) study. Patients underwent baseline computed tomography angiography and 24-hour noncontrast computed tomography follow-up for HE analysis. Discrimination and calibration of the 9- and 24-point scores was assessed. Independent predictors of HE were identified using multivariable regression and incorporated into the PREDICT A/B scores, which were then compared with existing scores. RESULTS: The 9- and 24-point HE scores demonstrated acceptable discrimination for HE>6 mL or 33% and >6 mL, respectively (area under the curve of 0.706 and 0.755, respectively). The 24-point score demonstrated appropriate calibration in the PREDICT cohort (χ2 statistic, 11.5; P=0.175), whereas the 9-point score demonstrated poor calibration (χ2 statistic, 34.3; P<0.001). Independent HE predictors included spot sign number, time from onset, warfarin use or international normalized ratio>1.5, Glasgow Coma Scale, and National Institutes of Health Stroke Scale and were included in PREDICT A/B scores. PREDICT A showed improved discrimination compared with both existing scores, whereas performance of PREDICT B varied by definition of expansion. CONCLUSIONS: The 9- and 24-point expansion scores demonstrate acceptable discrimination in an independent multicenter cohort; however, calibration was suboptimal for the 9-point score. The PREDICT A score showed improved discrimination for HE prediction but requires independent validation.

Multicenter accuracy and interobserver agreement of spot sign identification in acute intracerebral hemorrhage.

BACKGROUND AND PURPOSE: Rapid, accurate, and reliable identification of the computed tomography angiography spot sign is required to identify patients with intracerebral hemorrhage for trials of acute hemostatic therapy. We sought to assess the accuracy and interobserver agreement for spot sign identification. METHODS: A total of 131 neurology, emergency medicine, and neuroradiology staff and fellows underwent imaging certification for spot sign identification before enrolling patients in 3 trials targeting spot-positive intracerebral hemorrhage for hemostatic intervention (STOP-IT, SPOTLIGHT, STOP-AUST). Ten intracerebral hemorrhage cases (spot-positive/negative ratio, 1:1) were presented for evaluation of spot sign presence, number, and mimics. True spot positivity was determined by consensus of 2 experienced neuroradiologists. Diagnostic performance, agreement, and differences by training level were analyzed. RESULTS: Mean accuracy, sensitivity, and specificity for spot sign identification were 87%, 78%, and 96%, respectively. Overall sensitivity was lower than specificity (P<0.001) because of true spot signs incorrectly perceived as spot mimics. Interobserver agreement for spot sign presence was moderate (k=0.60). When true spots were correctly identified, 81% correctly identified the presence of single or multiple spots. Median time needed to evaluate the presence of a spot sign was 1.9 minutes (interquartile range, 1.2-3.1 minutes). Diagnostic performance, interobserver agreement, and time needed for spot sign evaluation were similar among staff physicians and fellows. CONCLUSIONS: Accuracy for spot identification is high with opportunity for improvement in spot interpretation sensitivity and interobserver agreement particularly through greater reliance on computed tomography angiography source data and awareness of limitations of multiplanar images. Further prospective study is needed.