The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

BACKGROUND: Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. PURPOSE: To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. STUDY TYPE: Prospective analysis of retrospectively acquired data. SUBJECTS: A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]). FIELD STRENGTH/SEQUENCE: 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. ASSESSMENT: Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience. STATISTICAL TESTS: Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used. RESULTS: Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2 ; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11). DATA CONCLUSION: Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

The neutrophil to lymphocyte ratio associates with markers of Alzheimer's disease pathology in cognitively unimpaired elderly people.

BACKGROUND: An elevated neutrophil-lymphocyte ratio (NLR) in blood has been associated with Alzheimer's disease (AD). However, an elevated NLR has also been implicated in many other conditions that are risk factors for AD, prompting investigation into whether the NLR is directly linked with AD pathology or a result of underlying comorbidities. Herein, we explored the relationship between the NLR and AD biomarkers in the cerebrospinal fluid (CSF) of cognitively unimpaired (CU) subjects. Adjusting for sociodemographics, APOE4, and common comorbidities, we investigated these associations in two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the M.J. de Leon CSF repository at NYU. Specifically, we examined associations between the NLR and cross-sectional measures of amyloid-ß42 (Aß42), total tau (t-tau), and phosphorylated tau181 (p-tau), as well as the trajectories of these CSF measures obtained longitudinally. RESULTS: A total of 111 ADNI and 190 NYU participants classified as CU with available NLR, CSF, and covariate data were included. Compared to NYU, ADNI participants were older (73.79 vs. 61.53, p < 0.001), had a higher proportion of males (49.5% vs. 36.8%, p = 0.042), higher BMIs (27.94 vs. 25.79, p < 0.001), higher prevalence of hypertensive history (47.7% vs. 16.3%, p < 0.001), and a greater percentage of Aß-positivity (34.2% vs. 20.0%, p = 0.009). In the ADNI cohort, we found cross-sectional associations between the NLR and CSF Aß42 (ß = -12.193, p = 0.021), but not t-tau or p-tau. In the NYU cohort, we found cross-sectional associations between the NLR and CSF t-tau (ß = 26.812, p = 0.019) and p-tau (ß = 3.441, p = 0.015), but not Aß42. In the NYU cohort alone, subjects classified as Aß + (n = 38) displayed a stronger association between the NLR and t-tau (ß = 100.476, p = 0.037) compared to Aß- subjects or the non-stratified cohort. In both cohorts, the same associations observed in the cross-sectional analyses were observed after incorporating longitudinal CSF data. CONCLUSIONS: We report associations between the NLR and Aß42 in the older ADNI cohort, and between the NLR and t-tau and p-tau in the younger NYU cohort. Associations persisted after adjusting for comorbidities, suggesting a direct link between the NLR and AD. However, changes in associations between the NLR and specific AD biomarkers may occur as part of immunosenescence.

Longitudinal trajectories of Alzheimer's disease CSF biomarkers and blood pressure in cognitively healthy subjects.

INTRODUCTION: We examined whether hypertension (HTN) was associated with Alzheimer's disease-related biomarkers in cerebrospinal fluid (CSF) and how changes in blood pressure (BP) related to changes in CSF biomarkers over time. METHODS: A longitudinal observation of cognitively healthy normotensive subjects (n = 134, BP < 140/90, with no antihypertensive medication), controlled HTN (n = 36, BP < 140/90, taking antihypertensive medication), and 35 subjects with uncontrolled HTN (BP ≥ 140/90). The follow-up range was 0.5to15.6 years. RESULTS: Total tau (T-tau) and phospho-tau181 (P-tau 181) increased in all but controlled HTN subjects (group×time interaction: p < 0.05 for both), but no significant Aß42 changes were seen. Significant BP reduction was observed in uncontrolled HTN, and it was related to increase in T-tau (p = 0.001) and P-tau 181 (p < 0.001). DISCUSSION: Longitudinal increases in T-tau and P-tau 181 were observed in most subjects; however, only uncontrolled HTN had both markers increase alongside BP reductions. We speculate cumulative vascular injury renders the brain susceptible to relative hypoperfusion with BP reduction. HIGHLIGHTS: Over the course of the study, participants with uncontrolled HTN at baseline showed greater accumulation of CSF total tau and phospho-tau181 (P-tau 181) than subjects with normal BP or with controlled HTN. In the group with uncontrolled HTN, increases in total tau and P-tau 181 coincided with reduction in BP. We believe this highlights the role of HTN in vascular injury and suggests decline in cerebral perfusion resulting in increased biomarker concentrations in CSF. Medication use was the main factor differentiating controlled from uncontrolled HTN, indicating that earlier treatment was beneficial for preventing accumulations of pathology.

Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study.

Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.

Quantitative imaging features predict spinal tap response in normal pressure hydrocephalus.

PURPOSE: Gait improvement following high-volume lumbar puncture (HVLP) and continuous lumbar drain (cLD) is widely used to predict shunt response in patients with suspected normal pressure hydrocephalus (NPH). Here, we investigate differences in MRI volumetric and traditional measures between HVLP/cLD responders and non-responders to identify imaging features that may help predict HVLP/cLD response. METHODS: Eighty-two patients with suspected NPH were studied retrospectively. Gait testing was performed before and immediately/24 h/72 h after HVLP/cLD. A positive response was defined as improvement in gait post-procedure. Thirty-six responders (26 men; mean age 79.3 ± 6.3) and 46 non-responders (25 men; mean age 77.2 ± 6.1) underwent pre-procedure brain MRI including a 3D T1-weighted sequence. Subcortical regional volumes were segmented using FreeSurfer. After normalizing for total intracranial volume, two-way type III ANCOVA test and chi-square test were used to characterize statistical group differences. Evans' index, callosal angle (CA), and disproportionately enlarged subarachnoid space hydrocephalus were assessed. Multivariable logistic regression models were tested using Akaike information criterion to determine which combination of metrics most accurately predicts HVLP/cLD response. RESULTS: Responders and non-responders demonstrated no differences in total ventricular and white/gray matter volumes. CA (men only) and third and fourth ventricular volumes were smaller; and hippocampal volume was larger in responders (p < 0.05). Temporal horns volume correlated with degree of improvement in gait velocity in responders (p = 0.0006). The regression model was 76.8% accurate for HVLP/cLD response. CONCLUSION: CA and third and fourth ventricular volumes and hippocampal volume may serve as potentially useful imaging features that may help predict spinal tap response and hence potentially shunt response.

Deep Learning Achieves Neuroradiologist-Level Performance in Detecting Hydrocephalus Requiring Treatment.

In large clinical centers a small subset of patients present with hydrocephalus that requires surgical treatment. We aimed to develop a screening tool to detect such cases from the head MRI with performance comparable to neuroradiologists. We leveraged 496 clinical MRI exams collected retrospectively at a single clinical site from patients referred for any reason. This diagnostic dataset was enriched to have 259 hydrocephalus cases. A 3D convolutional neural network was trained on 16 manually segmented exams (ten hydrocephalus) and subsequently used to automatically segment the remaining 480 exams and extract volumetric anatomical features. A linear classifier of these features was trained on 240 exams to detect cases of hydrocephalus that required treatment with surgical intervention. Performance was compared to four neuroradiologists on the remaining 240 exams. Performance was also evaluated on a separate screening dataset of 451 exams collected from a routine clinical population to predict the consensus reading from four neuroradiologists using images alone. The pipeline was also tested on an external dataset of 31 exams from a 2nd clinical site. The most discriminant features were the Magnetic Resonance Hydrocephalic Index (MRHI), ventricle volume, and the ratio between ventricle and brain volume. At matching sensitivity, the specificity of the machine and the neuroradiologists did not show significant differences for detection of hydrocephalus on either dataset (proportions test, p > 0.05). ROC performance compared favorably with the state-of-the-art (AUC 0.90-0.96), and replicated in the external validation. Hydrocephalus cases requiring treatment can be detected automatically from MRI in a heterogeneous patient population based on quantitative characterization of brain anatomy with performance comparable to that of neuroradiologists.

Assessment of Renal Cell Carcinoma by Texture Analysis in Clinical Practice: A Six-Site, Six-Platform Analysis of Reliability.

BACKGROUND. Multiple commercial and open-source software applications are available for texture analysis. Nonstandard techniques can cause undesirable variability that impedes result reproducibility and limits clinical utility. OBJECTIVE. The purpose of this study is to measure agreement of texture metrics extracted by six software packages. METHODS. This retrospective study included 40 renal cell carcinomas with contrast-enhanced CT from The Cancer Genome Atlas and Imaging Archive. Images were analyzed by seven readers at six sites. Each reader used one of six software packages to extract commonly studied texture features. Inter- and intrareader agreement for segmentation was assessed with intraclass correlation coefficients (ICCs). First-order (available in six packages) and second-order (available in three packages) texture features were compared between software pairs using Pearson correlation. RESULTS. Inter- and intrareader agreement was excellent (ICC, 0.93-1). First-order feature correlations were strong (r ≥ 0.8, p < .001) between 75% (21/28) of software pairs for mean intensity and SD, 48% (10/21) for entropy, 29% (8/28) for skewness, and 25% (7/28) for kurtosis. Of 15 second-order features, only cooccurrence matrix correlation, gray-level nonuniformity, and run-length nonuniformity showed strong correlation between software packages (r = 0.90-1, p < .001). CONCLUSION. Variability in first- and second-order texture features was common across software configurations and produced inconsistent results. Standardized algorithms and reporting methods are needed before texture data can be reliably used for clinical applications. CLINICAL IMPACT. It is important to be aware of variability related to texture software processing and configuration when reporting and comparing outputs.

Prostate cancer heterogeneity: texture analysis score based on multiple magnetic resonance imaging sequences for detection, stratification and selection of lesions at time of biopsy.

OBJECTIVE: To undertake an early proof-of-concept study on a novel, semi-automated texture-based scoring system in order to enhance the association between magnetic resonance imaging (MRI) lesions and clinically significant prostate cancer (SPCa). PATIENTS AND METHODS: With ethics approval, 536 imaging volumes were generated from 20 consecutive patients who underwent multiparametric MRI (mpMRI) at time of biopsy. Volumes of interest (VOIs) included zonal anatomy segmentation and suspicious MRI lesions for cancer (Likert Scale score >2). Entropy (E), measuring heterogeneity, was computed from VOIs and plotted as a multiparametric score defined as the entropy score (ES) = E ADC + E Ktrans + E Ve + E T2WI. The reference test that was used to define the ground truth comprised systematic saturation biopsies coupled with MRI-targeted sampling. This generated 422 cores in all that were individually labelled and oriented in three-dimensions. Diagnostic accuracy for detection of SPCa, defined as Gleason score ≥3 + 4 or >3 mm of any grade of cancer on a single core, was assessed using receiver operating characteristics, correlation, and descriptive statistics. The proportion of cancerous lesions detected by ES and visual scoring (VS) were statistically compared using the paired McNemar test. RESULTS: Any cancer (Gleason score 6-8) was found in 12 of the 20 (60%) patients, with a median PSA level of 8.22 ng/mL. SPCa (mean [95% confidence interval, CI] ES = 17.96 [0.72] NATural information unit [NAT]) had a significantly higher ES than non-SPCa (mean [95% CI] ES = 15.33 [0.76] NAT). The ES correlated with Gleason score (rs = 0.568, P = 0.033) and maximum cancer core length (ρ = 0.781; P < 0.001). The area under the curve for the ES (0.89) and VS (0.91) were not significantly different (P = 0.75) for the detection of SPCa amongst MRI lesions. Best ES estimated numerical threshold of 16.61 NAT led to a sensitivity of 100% and negative predictive value of 100%. The proportion of MRI lesions that were found to be positive for SPCa using this ES threshold (54%) was significantly higher (P < 0.001) than using the VS (24% of score 3, 4, 5) in a paired analysis using the McNemar test. In all, 53% of MRI lesions would have avoided biopsy sampling without missing significant disease. CONCLUSION: Capturing heterogeneity of prostate cancer across multiple MRI sequences with the ES yielded high performances for the detection and stratification of SPCa. The ES outperformed the VS in predicting positivity of lesions, holding promise in the selection of targets for biopsy and calling for further understanding of this association.

Quantitative evaluation of tau PET tracers 18F-THK5351 and 18F-AV-1451 in Alzheimer's disease with standardized uptake value peak-alignment (SUVP) normalization.

PURPOSE: Off-target binding in the reference region is a challenge for recent tau tracers 18F-AV-1451 and 18F-THK5351. The conventional standardized uptake value ratio (SUVR) method relies on the average uptake from an unaffected tissue sample, and therefore is susceptible to biases from off-target binding as well as variability among individuals in the reference region. We propose a new method, standardized uptake value peak-alignment (SUVP), to reduce the bias of the SUVR, and improve the quantitative assessment of tau deposition. METHODS: The SUVP normalizes uptake values by their mode and standard deviation. Instead of using a reference region, the SUVP derives the contrast from unaffected voxels over the whole brain. Using SUVP and SUVR methods, we evaluated the global and regional tau binding of 18F-THK5351 and 18F-AV-1451 on two independent cohorts (N = 18 and 32, respectively), each with cognitively normal (NL) subjects and Alzheimer's disease (AD) subjects. RESULTS: Both tracers showed significantly increased binding for AD in the targeted cortical areas. In the temporal cortex, SUVP had a higher classification success rate (CSR) than SUVR (0.96 vs 0.89 for 18F-THK5351; 0.86 vs 0.75 for 18F-AV-1451), as well as higher specificity under fixed sensitivity around 0.80 (0.70 vs 0.45 specificity for 18F-THK5351; 1.00 vs 0.78 for 18F-AV-1451). In the cerebellar cortex, an AD-NL group difference with effect size (Cohen's d) of 0.62 was observed for AV-1451, confirming the limitation of the SUVR approach using this region as a reference. A smaller cerebellar effect size (0.09) was observed for THK5351. CONCLUSION: The SUVP method reduces the bias of the reference region and improves the NL-AD classification compared to the SUVR approach.

REnal Flow and Microstructure AnisotroPy (REFMAP) MRI in Normal and Peritumoral Renal Tissue.

BACKGROUND: Diffusion-weighted imaging (DWI) provides insight into the pathophysiology underlying renal dysfunction. Variants of DWI include intravoxel incoherent motion (IVIM), which differentiates between microstructural diffusion and vascular or tubular flow, and diffusion tensor imaging (DTI), which quantifies diffusion directionality. PURPOSE: To investigate the reproducibility of joint IVIM-DTI and compare controls to presurgical renal mass patients. STUDY TYPE: Prospective cross-sectional. SUBJECTS: Thirteen healthy controls and ten presurgical renal mass patients were scanned. Ten controls were scanned twice to investigate reproducibility. FIELD STRENGTH/SEQUENCE: Subjects were scanned on a 3T system using 10 b-values and 20 diffusion directions for IVIM-DTI in a study approved by the local Institutional Review Board. ASSESSMENT: Retrospective coregistration and measurement of joint IVIM-DTI parameters were performed. STATISTICAL ANALYSIS: Parameter reproducibility was defined as intraclass correlation coefficient (ICC) >0.7 and coefficient of variation (CV) <30%. Patient data were stratified by lesion side (contralateral/ipsilateral) for comparison with controls. Corticomedullary differentiation was evaluated. RESULTS: In controls, the reproducible subset of REnal Flow and Microstructure AnisotroPy (REFMAP) parameters had average ICC = 0.82 and CV = 7.5%. In renal mass patients, medullary fractional anisotropy (FA) was significantly lower than in controls (0.227 ± 0.072 vs. 0.291 ± 0.044, P = 0.016 for the kidney contralateral to the mass and 0.228 ± 0.070 vs. 0.291 ± 0.044, P = 0.018 for the kidney ipsilateral). In the kidney ipsilateral to the mass, cortical Dp,radial was significantly higher than in controls (P = 0.012). Conversely, medullary Dp,axial was significantly lower in contralateral than ipsilateral kidneys (P = 0.027) and normal controls (P = 0.044). DATA CONCLUSION: REFMAP-MRI parameters provide unique information regarding renal dysfunction. In presurgical renal mass patients, directional flow changes were noted that were not identified with IVIM analysis alone. Both contralateral and ipsilateral kidneys in patients show reductions in structural diffusivities and anisotropy, while flow metrics showed opposing changes in contralateral vs. ipsilateral kidneys. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Comparison between qualitative and quantitative assessment of background parenchymal enhancement on breast MRI.

BACKGROUND: Potential clinical implications of the level of background parenchymal enhancement (BPE) on breast MRI are increasing. Currently, BPE is typically evaluated subjectively. Tests of concordance between subjective BPE assessment and computer-assisted quantified BPE have not been reported. PURPOSE OR HYPOTHESIS: To compare subjective radiologist assessment of BPE with objective quantified parenchymal enhancement (QPE). STUDY TYPE: Cross-sectional observational study. POPULATION: Between 7/24/2015 and 11/27/2015, 104 sequential patients (ages 23 - 81 years, mean 49 years) without breast cancer underwent breast MRI and were included in this study. FIELD STRENGTH/SEQUENCE: 3T; fat suppressed axial T2, axial T1, and axial fat suppressed T1 before and after intravenous contrast. ASSESSMENT: Four breast imagers graded BPE at 90 and 180 s after contrast injection on a 4-point scale (a-d). Fibroglandular tissue masks were generated using a phantom-validated segmentation algorithm, and were co-registered to pre- and postcontrast fat suppressed images to define the region of interest. QPE was calculated. STATISTICAL TESTS: Receiver operating characteristic (ROC) analyses and kappa coefficients (k) were used to compare subjective BPE with QPE. RESULTS: ROC analyses indicated that subjective BPE at 90 s was best predicted by quantified QPE ≤20.2 = a, 20.3-25.2 = b, 25.3-50.0 = c, >50.0 = d, and at 180 s by quantified QPE ≤ 32.2 = a, 32.3-38.3 = b, 38.4-74.5 = c, >74.5 = d. Agreement between subjective BPE and QPE was slight to fair at 90 s (k = 0.20-0.36) and 180 s (k = 0.19-0.28). At higher levels of QPE, agreement between subjective BPE and QPE significantly decreased for all four radiologists at 90 s (P ≤ 0.004) and for three of four radiologists at 180 s (P ≤ 0.004). DATA CONCLUSION: Radiologists were less consistent with QPE as QPE increased. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1685-1691.

Proton MR spectroscopy of lesion evolution in multiple sclerosis: Steady-state metabolism and its relationship to conventional imaging.

Although MRI assessment of white matter lesions is essential for the clinical management of multiple sclerosis, the processes leading to the formation of lesions and underlying their subsequent MRI appearance are incompletely understood. We used proton MR spectroscopy to study the evolution of N-acetyl-aspartate (NAA), creatine (Cr), choline (Cho), and myo-inositol (mI) in pre-lesional tissue, persistent and transient new lesions, as well as in chronic lesions, and related the results to quantitative MRI measures of T1-hypointensity and T2-volume. Within 10 patients with relapsing-remitting course, there were 180 regions-of-interest consisting of up to seven semi-annual follow-ups of normal-appearing white matter (NAWM, n = 10), pre-lesional tissue giving rise to acute lesions which resolved (n = 3) or persisted (n = 3), and of moderately (n = 9) and severely hypointense (n = 6) chronic lesions. Compared with NAWM, pre-lesional tissue had higher Cr and Cho, while compared with lesions, pre-lesional tissue had higher NAA. Resolving acute lesions showed similar NAA levels pre- and post-formation, suggesting no long-term axonal damage. In chronic lesions, there was an increase in mI, suggesting accumulating astrogliosis. Lesion volume was a better predictor of axonal health than T1-hypointensity, with lesions larger than 1.5 cm3 uniformly exhibiting very low (<4.5 millimolar) NAA concentrations. A positive correlation between longitudinal changes in Cho and in lesion volume in moderately hypointense lesions implied that lesion size is mediated by chronic inflammation. These and other results are integrated in a discussion on the steady-state metabolism of lesion evolution in multiple sclerosis, viewed in the context of conventional MRI measures. Hum Brain Mapp 38:4047-4063, 2017. © 2017 Wiley Periodicals, Inc.

Diagnosis of Normal-Pressure Hydrocephalus: Use of Traditional Measures in the Era of Volumetric MR Imaging.

Purpose To assess the diagnostic performance of the callosal angle (CA) and Evans index (EI) measures and to determine their role versus automated volumetric methods in clinical radiology. Materials and Methods Magnetic resonance (MR) examinations performed before surgery (within 1-5 months of the MR examination) in 36 shunt-responsive patients with normal-pressure hydrocephalus (NPH; mean age, 75 years; age range, 58-87 years; 26 men, 10 women) and MR examinations of age- and sex-matched patients with Alzheimer disease (n = 34) and healthy control volunteers (n = 36) were studied. Three blinded observers independently measured EI and CA for each patient. Volumetric segmentation of global gray matter, white matter, ventricles, and hippocampi was performed by using software. These measures were tested by using multivariable logistic regression models to determine which combination of metrics is most accurate in diagnosis. Results The model that used CA and EI demonstrated 89.6%-93.4% accuracy and average area under the curve of 0.96 in differentiating patients with NPH from patients without NPH (ie, Alzheimer disease and healthy control). The regression model that used volumetric predictors of gray matter and white matter was 94.3% accurate. Conclusion CA and EI may serve as a screening tool to help the radiologist differentiate patients with NPH from patients without NPH, which would allow for designation of patients for further volumetric assessment. © RSNA, 2017.

Lung Adenocarcinoma: Correlation of Quantitative CT Findings with Pathologic Findings.

Purpose To identify the ability of computer-derived three-dimensional (3D) computed tomographic (CT) segmentation techniques to help differentiate lung adenocarcinoma subtypes. Materials and Methods This study had institutional research board approval and was HIPAA compliant. Pathologically classified resected lung adenocarcinomas (n = 41) with thin-section CT data were identified. Two readers independently placed over-inclusive volumes around nodules from which automated computer measurements were generated: mass (total mass) and volume (total volume) of the nodule and of any solid portion, in addition to the solid percentage of the nodule volume (percentage solid volume) or mass (percentage solid mass). Interobserver agreement and differences in measurements among pathologic entities were evaluated by using t tests. A multinomial logistic regression model was used to differentiate the probability of three diagnoses: invasive non-lepidic-predominant adenocarcinoma (INV), lepidic-predominant adenocarcinoma (LPA), and adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). Results Mean percentage solid volume of INV was 35.4% (95% confidence interval [CI]: 26.2%, 44.5%)-higher than the 14.5% (95% CI: 10.3%, 18.7%) for LPA (P = .002). Mean percentage solid volume of AIS/MIA was 8.2% (95% CI: 2.7%, 13.7%) and had a trend toward being lower than that for LPA (P = .051). Accuracy of the model based on total volume and percentage solid volume was 73.2%; accuracy of the model based on total mass and percentage solid mass was 75.6%. Conclusion Computer-assisted 3D measurement of nodules at CT had good reproducibility and helped differentiate among subtypes of lung adenocarcinoma. (©) RSNA, 2016.

Assessment of renal function using intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI.

PURPOSE: To assess the correlation between each of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in renal parenchyma with renal function, in a cohort of patients with chronic liver disease. MATERIALS AND METHODS: Thirty patients with liver disease underwent abdominal MRI at 1.5T, including a coronal respiratory-triggered IVIM-DWI sequence and a coronal 3D FLASH DCE-MRI acquisition. Diffusion signals in the renal cortex and medulla were fitted to the IVIM model to estimate the diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (PF). The apparent diffusion coefficient (ADC) was calculated using all b-values. The glomerular filtration rate (GFR), cortical and medullary renal plasma flow (RPF), mean transit times (MTT) of vascular and tubular compartments and the whole kidney, were calculated from DCE-MRI data by fitting to a three-compartment model. The estimated GFR (eGFR) was calculated from serum creatinine measured 30 ± 27 days of MRI. RESULTS: ADC, PF, and RPF were significantly higher in renal cortex vs. medulla (P < 10(-5) ). DCE-MRI GFR significantly correlated with, but underestimated, eGFR (Spearman's r/P = 0.49/0.01). IVIM-DWI parameters were not significantly correlated with eGFR. DCE-MRI GFR correlated weakly with D (cortex, r/P = 0.3/0.03; medulla r/P = 0.27/0.05) and ADC (cortex r/P = 0.28/0.04; medulla r/P = 0.34/0.01). Weak correlations were observed for pooled cortical and medullar RPF with PF (r/P = 0.32/10(-3) ) and with ADC (r/P = 0.29/0.0025). Significant negative correlations were observed for vascular MTT with cortical D* (r/P = -0.38/0.004) and D*×PF (r/P = -0.34/0.01). CONCLUSION: The weak correlations between renal IVIM and DCE-MRI perfusion parameters imply that these functional measures could be complementary. J. Magn. Reson. Imaging 2016;44:317-326.

Likert score 3 prostate lesions: Association between whole-lesion ADC metrics and pathologic findings at MRI/ultrasound fusion targeted biopsy.

BACKGROUND: To assess associations between whole-lesion apparent diffusion coefficient (ADC) metrics and pathologic findings of Likert score 3 prostate lesions at MRI/ultrasound fusion targeted biopsy. METHODS: This retrospective Institutional Review Board-approved study received a waiver of consent. We identified patients receiving a highest lesion score of 3 on 3 Tesla multiparametric MRI reviewed by a single experienced radiologist using a 5-point Likert scale and who underwent fusion biopsy. A total of 188 score 3 lesions in 158 patients were included. Three-dimensional volumes-of-interest encompassing each lesion were traced on ADC maps. Logistic regression was used to predict biopsy results based on whole-lesion ADC metrics and patient biopsy history. Biopsy yield was compared between metrics. RESULTS: By lesion, targeted biopsy identified tumor in 22.3% and Gleason score (GS) > 6 tumor in 8.5%, although results varied by biopsy history: biopsy-naïve (n = 80), 20.0%/8.8%; prior negative biopsy (n = 53), 9.4%/1.9%; prior positive biopsy (n = 55): 40.0%/14.5%. Biopsy history, whole-lesion mean ADC, whole-lesion ADC10-25 , and whole-lesion ADC25-50 were each significantly associated with tumor or GS > 6 tumor at fusion biopsy (P ≤ 0.047). In men without prior negative prostate biopsy, whole-lesion ADC25-50 ≤ 1.04*10(-3) mm2 /s achieved 90.0% sensitivity and 50.0% specificity for GS > 6 tumor, which was significantly higher (P < 0.001) than specificity of PSA (17.5%) at identical sensitivity. CONCLUSION: For score 3 lesions in patients without prior negative biopsy, whole-lesion ADC metrics help detect GS > 6 cancer while avoiding negative biopsies. However, deferral of fusion biopsy may be considered for score 3 lesions in patients with prior negative biopsy (without applying whole-lesion ADC metrics) given exceedingly low (∼ 2%) frequency of GS > 6 tumor in this group.

Use of MRI in Differentiation of Papillary Renal Cell Carcinoma Subtypes: Qualitative and Quantitative Analysis.

OBJECTIVE: The purpose of this study was to determine whether qualitative and quantitative MRI feature analysis is useful for differentiating type 1 from type 2 papillary renal cell carcinoma (PRCC). MATERIALS AND METHODS: This retrospective study included 21 type 1 and 17 type 2 PRCCs evaluated with preoperative MRI. Two radiologists independently evaluated various qualitative features, including signal intensity, heterogeneity, and margin. For the quantitative analysis, a radiology fellow and a medical student independently drew 3D volumes of interest over the entire tumor on T2-weighted HASTE images, apparent diffusion coefficient parametric maps, and nephrographic phase contrast-enhanced MR images to derive first-order texture metrics. Qualitative and quantitative features were compared between the groups. RESULTS: For both readers, qualitative features with greater frequency in type 2 PRCC included heterogeneous enhancement, indistinct margin, and T2 heterogeneity (all, p < 0.035). Indistinct margins and heterogeneous enhancement were independent predictors (AUC, 0.822). Quantitative analysis revealed that apparent diffusion coefficient, HASTE, and contrast-enhanced entropy were greater in type 2 PRCC (p < 0.05; AUC, 0.682-0.716). A combined quantitative and qualitative model had an AUC of 0.859. Qualitative features within the model had interreader concordance of 84-95%, and the quantitative data had intraclass coefficients of 0.873-0.961. CONCLUSION: Qualitative and quantitative features can help discriminate between type 1 and type 2 PRCC. Quantitative analysis may capture useful information that complements the qualitative appearance while benefiting from high interobserver agreement.

Accelerated Brain Atrophy on Serial Computed Tomography: Potential Marker of the Progression of Alzheimer Disease.

OBJECTIVE: The aim of this study was to validate computed tomography (CT)-based longitudinal markers of the progression of Alzheimer disease (AD). MATERIALS AND METHODS: We retrospectively studied 33 AD patients and 39 nondemented patients with other neurological illnesses (non-AD) having 4 to 12 CT examinations of the head, with over a mean (SD) of 3.9 (1.7) years. At each time point, we applied an automatic software to measure whole brain, cerebrospinal fluid, and intracranial space volumes. Longitudinal measures were then related to disease status and time since the first scan using hierarchical models. RESULTS: Absolute brain volume loss accelerated for non-AD patients by 0.86 mL/y (95% confidence interval [CI], 0.64-1.08 mL/y) and 1.5× faster, that is, 1.32 mL/y (95% CI, 1.09-1.56 mL/y) for AD patients (P = 0.006). In terms of brain volume normalized to intracranial space, the acceleration in atrophy rate for non-AD patients was 0.0578%/y (95% CI, 0.0389%/y to 0.0767%/y), again 1.5× faster, that is, 0.0919%/y (95% CI, 0.0716%/y to 0.1122%/y) for AD patients (P = 0.017). This translates to an increase in atrophy rate from 0.5% to 1.4% in AD versus to 1.1% in non-AD group after 10 years. CONCLUSIONS: Brain volumetry on CT reliably detected accelerated volume loss in AD and significantly lower acceleration factor in age-matched non-AD patients, leading to the possibility of its use to monitor the progression of cognitive decline and dementia.

A semi-automated "blanket" method for renal segmentation from non-contrast T1-weighted MR images.

OBJECTIVE: To investigate the precision and accuracy of a new semi-automated method for kidney segmentation from single-breath-hold non-contrast MRI. MATERIALS AND METHODS: The user draws approximate kidney contours on every tenth slice, focusing on separating adjacent organs from the kidney. The program then performs a sequence of fully automatic steps: contour filling, interpolation, non-uniformity correction, sampling of representative parenchyma signal, and 3D binary morphology. Three independent observers applied the method to images of 40 kidneys ranging in volume from 94.6 to 254.5 cm(3). Manually constructed reference masks were used to assess accuracy. RESULTS: The volume errors for the three readers were: 4.4% ± 3.0%, 2.9% ± 2.3%, and 3.1% ± 2.7%. The relative discrepancy across readers was 2.5% ± 2.1%. The interactive processing time on average was 1.5 min per kidney. CONCLUSIONS: Pending further validation, the semi-automated method could be applied for monitoring of renal status using non-contrast MRI.