Pearls & Oy-sters: Bibrachial Amyotrophy From a Dural Tear.

Bibrachial amyotrophy signifies a clinical phenotype characterized by weakness in both upper extremities with preserved strength in the face, neck, and lower extremities. The underlying causes of bibrachial amyotrophy are broad. We report a patient exhibiting bibrachial amyotrophy who initially received a diagnosis of amyotrophic lateral sclerosis (ALS); however, his clinical course and NCS/EMG were atypical for ALS. Further evaluation demonstrated dural tears with CSF leak, resulting in a compressive extradural fluid collection, ventral myelopathy, and intracranial hypotension. Dural tear and ALS have overlapping features, including the manifestation of the bibrachial amyotrophy phenotype and the presence of T2 hyperintensities in the anterior horn cells, recognized by an "owl's eye" appearance on spine MRI. Clinical and radiologic vigilance is required to identify rare cases of dural tear causing ventral myelopathy that manifest as bibrachial amyotrophy.

Now that the door is open: an update on ischemic stroke pharmacotherapeutics for the neurointerventionalist.

The last 10 years have seen a major shift in management of large vessel ischemic stroke with changes towards ever-expanding use of reperfusion therapies (intravenous thrombolysis and mechanical thrombectomy). These strategies 'open the door' to acute therapeutics for ischemic tissue, and we should investigate novel therapeutic approaches to enhance survival of recently reperfused brain. Key insights into new approaches have been provided through translational research models and preclinical paradigms, and through detailed research on ischemic mechanisms. Additional recent clinical trials offer exciting salvos into this new strategy of pairing reperfusion with neuroprotective therapy. This pairing strategy can be employed using drugs that have shown neuroprotective efficacy; neurointerventionalists can administer these during or immediately after reperfusion therapy. This represents a crucial moment when we emphasize reperfusion, and have the technological capability along with the clinical trial experience to lead the way in multiprong approaches to stroke treatment.

Inflammatory-associated proteomic predictors of cognitive outcome in subjects with ELVO treated by mechanical thrombectomy.

BACKGROUND: Emergent Large Vessel Occlusion (ELVO) stroke causes devastating vascular events which can lead to significant cognitive decline and dementia. In the subset of ELVO subjects treated with mechanical thrombectomy (MT) at our institution, we aimed to identify systemic and intracranial proteins predictive of cognitive function at time of discharge and at 90-days. These proteomic biomarkers may serve as prognostic indicators of recovery, as well as potential targets for novel/existing therapeutics to be delivered during the subacute stage of stroke recovery. METHODS: At the University of Kentucky Center for Advanced Translational Stroke Sciences, the BACTRAC tissue registry (clinicaltrials.gov; NCT03153683) of human biospecimens acquired during ELVO stroke by MT is utilized for research. Clinical data are collected on each enrolled subject who meets inclusion criteria. Blood samples obtained during thrombectomy were sent to Olink Proteomics for proteomic expression values. Montreal Cognitive Assessments (MoCA) were evaluated with categorical variables using ANOVA and t-tests, and continuous variables using Pearson correlations. RESULTS: There were n = 52 subjects with discharge MoCA scores and n = 28 subjects with 90-day MoCA scores. Several systemic and intracranial proteins were identified as having significant correlations to discharge MoCA scores as well as 90-day MoCA scores. Highlighted proteins included s-DPP4, CCL11, IGFBP3, DNER, NRP1, MCP1, and COMP. CONCLUSION: We set out to identify proteomic predictors and potential therapeutic targets related to cognitive outcomes in ELVO subjects undergoing MT. Here, we identify several proteins which predicted MoCA after MT, which may serve as therapeutic targets to lessen post-stroke cognitive decline.

Plasma protein alterations during human large vessel stroke: A controlled comparison study.

BACKGROUND: Stroke is a major cause of death and disability in the United States. Mechanical thrombectomy (MT) and tissue plasminogen activator are the current treatments for ischemic stroke, which have improved clinical outcomes. Despite these treatments, functional and cognitive deficits still occur demonstrating a need for predictive biomarkers for beneficial clinical outcomes which can be used as therapeutic targets for pharmacotherapy. The aim of this study compares the proteomic expression of systemic arterial blood collected at the time of MT to those from a matched cerebrovascular disease (CVD) control cohort. METHODS: The Blood And Clot Thrombectomy Registry And Collaboration (BACTRAC) (clinicaltrials.gov NCT03153683) collects and banks arterial blood, both distal and proximal to the thrombus, from ischemic stroke subjects undergoing MT. Arterial blood from patients undergoing a diagnostic angiogram was also collected and banked as CVD controls. Changes in cardiometabolic and inflammatory proteins between stroke and CVD controls were analyzed via Olink Proteomics. RESULTS: Proteins including ARTN, TWEAK, HGF, CCL28, FGF-5, CXCL9, TRANCE and GDNF were found to be decreased in stroke subjects when compared to CVD controls. CXCL1, CCL5, OSM, GP1BA, IL6, MMP-1, and CXCL5 were increased in stroke subjects when compared to CVD controls. These proteins were also significantly correlated to stroke outcome metrics such as NIHSS, infarct volume and MoCA scoring. CONCLUSION: Overall, acute stroke patients had an increase in inflammatory proteins with a decrease in trophic proteins systemically compared to matched CVD controls. Using our CVD controls, proteins of interest were directly compared to stroke patients with the same cerebrovascular risk factors instead of statistically controlling for comorbidities. The novel methodology of matching an arterial blood CVD control group to a stroke group, as well as controlling for age and comorbid status add to the literature on prognostic stroke biomarkers, which are specific targets for future therapeutics.

Influence of BMI on adenosine deaminase and stroke outcomes in mechanical thrombectomy subjects.

BACKGROUND: Emergent Large Vessel Occlusion (ELVO) strokes are ischemic vascular events for which novel biomarkers and therapies are needed. The purpose of this study is to investigate the role of Body Mass Index (BMI) on protein expression and signaling at the time of ELVO intervention. Additionally, we highlight the protein adenosine deaminase (ADA), which is a deaminating enzyme that degrades adenosine, which has been shown to be neuroprotective in ischemia. We investigate the relationship between ADA and BMI, stroke outcomes, and associated proteomic networks which might aid in personalizing prognosis and future treatment of ELVO stroke. METHODS: The Blood And Clot Thrombectomy And Collaboration (BACTRAC) study is a continually enrolling tissue bank (clinicaltrials.gov NCT03153683) and registry from stroke patients undergoing mechanical thrombectomy (MT). N â€‹= â€‹61 human carotid plasma samples were analyzed for inflammatory and cardiometabolic protein expression by Olink Proteomics. Statistical analyses used t-tests, linear, logistic, and robust regressions, to assess the relationship between BMI, proteomic expression, and stroke-related outcomes. RESULTS: The 61 subjects studied were broken into three categories: normal weight (BMI 18.5-24.9) which contained 19 subjects, overweight (BMI 25-30) which contained 25 subjects, and obese (BMI ≥30) which contained 17 subjects. Normal BMI group was a significantly older population (mean 76 years) when compared to overweight (mean 66 years) and obese (mean 61 years) with significance of p â€‹= â€‹0.041 and p â€‹= â€‹0.005, respectively. When compared to normal weight and overweight categories, the obese category had significantly higher levels of adenosine deaminase (ADA) expression (p â€‹= â€‹0.01 and p â€‹= â€‹0.039, respectively). Elevated levels of ADA were found to have a significant positive correlation with both infarct volume and edema volume (p â€‹= â€‹0.013 and p â€‹= â€‹0.041, respectively), and were associated with a more severe stroke (NIHSS on discharge) and greater stroke related disability (mRS on discharge) with significance of p â€‹= â€‹0.053 and p â€‹= â€‹0.032, respectively. CONCLUSIONS: When examined according to BMI, subjects undergoing MT for ELVO demonstrate significant differences in the expression of certain plasma proteins, including ADA. Levels of ADA were found to be significantly higher in the obese population when compared to normal or overweight groups. Increased levels of ADA in the obese group were predictive of increased infarct volume, edema volume, and worse NIHSS scores and mRS at discharge. These data provide novel biomarker candidates as well as treatment targets while increasing the personalization of stroke prognosis and treatment.

Alterations in Local Peri-Infarct Blood Gases in Stroke Patients Undergoing Thrombectomy.

BACKGROUND: Ischemic stroke is a prevalent, devastating disease with high morbidity and mortality. Despite extensive research using animal models, significant gaps remain in understanding the pathological processes in human stroke. We previously developed a tissue bank to analyze the blood immediately proximal and distal to an intracranial thrombus in patients undergoing mechanical thrombectomy (ClinicalTrials.gov identifier, NCT03153683). Our goal for the present project was to evaluate the blood gas changes and acid/base balance during stroke and determine how vascular collateralization affects these changes. METHODS: We analyzed the blood samples and computed tomography angiography collateral scores from the first 62 patients in the BACTRAC (Blood and Clot Thrombectomy Registry and Collaboration) registry. The bicarbonate, partial pressure of oxygen, and partial pressure of carbon dioxide (pCO2) values of the intracranial (distal) and systemic (proximal) arterial blood relative to the occlusive thrombus were analyzed. Analysis of the group differences in systemic and intracranial blood gas values was also performed. RESULTS: The partial pressure of oxygen, pCO2, and bicarbonate levels were all significantly higher in the systemic blood than in the intracranial blood (P < 0.001 for all) at thrombectomy. Collateralization did not significantly affect the distal blood gas values. Compared with the female patients, the male patients had had higher systemic pCO2 values (39.8 vs. 36.6 mm Hg; P = 0.0065) and lower systemic and intracranial pH values (7.351 vs. 7.392; P = 0.0047). CONCLUSIONS: The arterial blood gases differed immediately proximal and distal to thrombi in large vessel occlusive stroke. Although vascular collateralization did not appear to affect the blood gas changes, some blood gas values differed between men and women. The changes in bicarbonate and pCO2 suggested a compensatory acid-base process occurring at the time of infarction.

T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology.

OBJECTIVES: To explore the associations between T1 and T2 magnetic resonance fingerprinting (MRF) measurements and corresponding tissue compartment ratios (TCRs) on whole mount histopathology of prostate cancer (PCa) and prostatitis. MATERIALS AND METHODS: A retrospective, IRB-approved, HIPAA-compliant cohort consisting of 14 PCa patients who underwent 3 T multiparametric MRI along with T1 and T2 MRF maps prior to radical prostatectomy was used. Correspondences between whole mount specimens and MRI and MRF were manually established. Prostatitis, PCa, and normal peripheral zone (PZ) regions of interest (ROIs) on pathology were segmented for TCRs of epithelium, lumen, and stroma using two U-net deep learning models. Corresponding ROIs were mapped to T2-weighted MRI (T2w), apparent diffusion coefficient (ADC), and T1 and T2 MRF maps. Their correlations with TCRs were computed using Pearson's correlation coefficient (R). Statistically significant differences in means were assessed using one-way ANOVA. RESULTS: Statistically significant differences (p < 0.01) in means of TCRs and T1 and T2 MRF were observed between PCa, prostatitis, and normal PZ. A negative correlation was observed between T1 and T2 MRF and epithelium (R = - 0.38, - 0.44, p < 0.05) of PCa. T1 MRF was correlated in opposite directions with stroma of PCa and prostatitis (R = 0.35, - 0.44, p < 0.05). T2 MRF was positively correlated with lumen of PCa and prostatitis (R = 0.57, 0.46, p < 0.01). Mean T2 MRF showed significant differences (p < 0.01) between PCa and prostatitis across both transition zone (TZ) and PZ, while mean T1 MRF was significant (p = 0.02) in TZ. CONCLUSION: Significant associations between MRF (T1 in the TZ and T2 in the PZ) and tissue compartments on corresponding histopathology were observed. KEY POINTS: • Mean T2 MRF measurements and ADC within cancerous regions of interest dropped with increasing ISUP prognostic groups (IPG). • Mean T1 and T2 MRF measurements were significantly different (p < 0.001) across IPGs, prostatitis, and normal peripheral zone (NPZ). • T2 MRF showed stronger correlations in the peripheral zone, while T1 MRF showed stronger correlations in the transition zone with histopathology for prostate cancer.

Relationship between Mammographic Findings and Breast Abnormalities in a Nigerian Population.

PURPOSE: This study aims to describe the mammographic findings in a population of Nigerian women and to explore the relationships between abnormal mammographic findings, breast malignancy, and breast composition. METHODOLOGY: This was a retrospective study of consecutive mammograms carried out at Union Diagnostics and Clinical Services in Lagos, Nigeria from 2016 to 2018. Demographic information, indications for and findings on mammographic evaluation were obtained. A logistic regression fit model was used to establish the correlation between mammographic findings, breast density, and suspicion for breast malignancy (higher BIRADS scores). P ≤ 0.05 represented a statistically significant result. RESULTS: A total of 304 patients were involved in this study (age range 20-80 years, mean age 49.0 ± 10.5 years). The patients between 40 and 49 years formed the largest age group with 128 patients (42.4%). Most patients were referred for a breast mass/lump (115/304-38.6%); 56 patients (18.8%) presenting for routine screening. The most common finding on the mammograms was BIRADS 4 in both breasts in 96 patients (31.6%). Most patients had heterogeneous breast density (195 patients - 64.1%). Multivariate logistic regression analysis showed a significant correlation between history of mass, poorly defined margins, and suspicion of malignancy. There was no statistically significant association between abnormal mammographic findings and higher breast density. CONCLUSION: Poorly defined margins were positively correlated with BIRADS ratings suspicious for malignancy. The presence of a breast mass was positively correlated with a higher BIRADS score when other possible cofounding variables were not accounted for. Patient age did not correlate with breast density in this study.

Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study.

Background: Prostate cancer (PCa) influences its surrounding habitat, which tends to manifest as different phenotypic appearances on magnetic resonance imaging (MRI). This region surrounding the PCa lesion, or the peri-tumoral region, may encode useful information that can complement intra-tumoral information to enable better risk stratification. Purpose: To evaluate the role of peri-tumoral radiomic features on bi-parametric MRI (T2-weighted and Diffusion-weighted) to distinguish PCa risk categories as defined by D'Amico Risk Classification System. Materials and Methods: We studied a retrospective, HIPAA-compliant, 4-institution cohort of 231 PCa patients (n = 301 lesions) who underwent 3T multi-parametric MRI prior to biopsy. PCa regions of interest (ROIs) were delineated on MRI by experienced radiologists following which peri-tumoral ROIs were defined. Radiomic features were extracted within the intra- and peri-tumoral ROIs. Radiomic features differentiating low-risk from: (1) high-risk (L-vs.-H), and (2) (intermediate- and high-risk (L-vs.-I + H)) lesions were identified. Using a multi-institutional training cohort of 151 lesions (D1, N = 116 patients), machine learning classifiers were trained using peri- and intra-tumoral features individually and in combination. The remaining 150 lesions (D2, N = 115 patients) were used for independent hold-out validation and were evaluated using Receiver Operating Characteristic (ROC) analysis and compared with PI-RADS v2 scores. Results: Validation on D2 using peri-tumoral radiomics alone resulted in areas under the ROC curve (AUCs) of 0.84 and 0.73 for the L-vs.-H and L-vs.-I + H classifications, respectively. The best combination of intra- and peri-tumoral features resulted in AUCs of 0.87 and 0.75 for the L-vs.-H and L-vs.-I + H classifications, respectively. This combination improved the risk stratification results by 3-6% compared to intra-tumoral features alone. Our radiomics-based model resulted in a 53% accuracy in differentiating L-vs.-H compared to PI-RADS v2 (48%), on the validation set. Conclusion: Our findings suggest that peri-tumoral radiomic features derived from prostate bi-parametric MRI add independent predictive value to intra-tumoral radiomic features for PCa risk assessment.

Quantifying Perfusion Properties with DCE-MRI Using a Dictionary Matching Approach.

Perfusion properties can be estimated from pharmacokinetic models applied to DCE-MRI data using curve fitting algorithms; however, these suffer from drawbacks including the local minimum problem and substantial computational time. Here, a dictionary matching approach is proposed as an alternative. Curve fitting and dictionary matching were applied to simulated data using the dual-input single-compartment model with known perfusion property values and 5 in vivo DCE-MRI datasets. In simulation at SNR 60 dB, the dictionary estimate had a mean percent error of 0.4-1.0% for arterial fraction, 0.5-1.4% for distribution volume, and 0.0% for mean transit time. The curve fitting estimate had a mean percent error of 1.1-2.1% for arterial fraction, 0.5-1.3% for distribution volume, and 0.2-1.8% for mean transit time. In vivo, dictionary matching and curve fitting showed no statistically significant differences in any of the perfusion property measurements in any of the 10 ROIs between the methods. In vivo, the dictionary method performed over 140-fold faster than curve fitting, obtaining whole volume perfusion maps in just over 10 s. This study establishes the feasibility of using a dictionary matching approach as a new and faster way of estimating perfusion properties from pharmacokinetic models in DCE-MRI.

Simultaneous Mapping of T1 and T2 Using Cardiac Magnetic Resonance Fingerprinting in a Cohort of Healthy Subjects at 1.5T.

BACKGROUND: Cardiac MR fingerprinting (cMRF) is a novel technique for simultaneous T1 and T2 mapping. PURPOSE: To compare T1 /T2 measurements, repeatability, and map quality between cMRF and standard mapping techniques in healthy subjects. STUDY TYPE: Prospective. POPULATION: In all, 58 subjects (ages 18-60). FIELD STRENGTH/SEQUENCE: cMRF, modified Look-Locker inversion recovery (MOLLI), and T2 -prepared balanced steady-state free precession (bSSFP) at 1.5T. ASSESSMENT: T1 /T2 values were measured in 16 myocardial segments at apical, medial, and basal slice positions. Test-retest and intrareader repeatability were assessed for the medial slice. cMRF and conventional mapping sequences were compared using ordinal and two alternative forced choice (2AFC) ratings. STATISTICAL TESTS: Paired t-tests, Bland-Altman analyses, intraclass correlation coefficient (ICC), linear regression, one-way analysis of variance (ANOVA), and binomial tests. RESULTS: Average T1 measurements were: basal 1007.4±96.5 msec (cMRF), 990.0±45.3 msec (MOLLI); medial 995.0±101.7 msec (cMRF), 995.6±59.7 msec (MOLLI); apical 1006.6±111.2 msec (cMRF); and 981.6±87.6 msec (MOLLI). Average T2 measurements were: basal 40.9±7.0 msec (cMRF), 46.1±3.5 msec (bSSFP); medial 41.0±6.4 msec (cMRF), 47.4±4.1 msec (bSSFP); apical 43.5±6.7 msec (cMRF), 48.0±4.0 msec (bSSFP). A statistically significant bias (cMRF T1 larger than MOLLI T1 ) was observed in basal (17.4 msec) and apical (25.0 msec) slices. For T2 , a statistically significant bias (cMRF lower than bSSFP) was observed for basal (-5.2 msec), medial (-6.3 msec), and apical (-4.5 msec) slices. Precision was lower for cMRF-the average of the standard deviation measured within each slice was 102 msec for cMRF vs. 61 msec for MOLLI T1 , and 6.4 msec for cMRF vs. 4.0 msec for bSSFP T2 . cMRF and conventional techniques had similar test-retest repeatability as quantified by ICC (0.87 cMRF vs. 0.84 MOLLI for T1 ; 0.85 cMRF vs. 0.85 bSSFP for T2 ). In the ordinal image quality comparison, cMRF maps scored higher than conventional sequences for both T1 (all five features) and T2 (four features). DATA CONCLUSION: This work reports on myocardial T1 /T2 measurements in healthy subjects using cMRF and standard mapping sequences. cMRF had slightly lower precision, similar test-retest and intrareader repeatability, and higher scores for map quality. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;52:1044-1052.

Cerebral vessel anatomy as a predictor of first-pass effect in mechanical thrombectomy for emergent large-vessel occlusion.

OBJECTIVE: Mechanical thrombectomy is effective in acute ischemic stroke secondary to emergent large-vessel occlusion, but optimal efficacy is contingent on fast and complete recanalization. First-pass recanalization does not occur in the majority of patients. The authors undertook this study to determine if anatomical parameters of the intracranial vessels impact the likelihood of first-pass complete recanalization. METHODS: The authors retrospectively evaluated data obtained in 230 patients who underwent mechanical thrombectomy for acute ischemic stroke secondary to large-vessel occlusion at their institution from 2016 to 2018. Eighty-six patients were identified as having pure M1 occlusions, and 76 were included in the final analysis. The authors recorded and measured clinical and anatomical parameters and evaluated their relationships to the first-pass effect. RESULTS: The first-pass effect was achieved in 46% of the patients. When a single device was employed, aspiration thrombectomy was more effective than stent retriever thrombectomy. A larger M1 diameter (p = 0.001), decreased vessel diameter tapering between the petrous segment of the internal carotid artery (ICA) and M1 (p < 0.001), and distal collateral grading (p = 0.044) were associated with first-pass recanalization. LASSO (least absolute shrinkage and selection operator) was used to generate a predictive model for recanalization using anatomical variables. CONCLUSIONS: The authors demonstrated that a larger M1 vessel diameter, low rate of vessel diameter tapering along the course of the intracranial ICA, and distal collateral status are associated with first-pass recanalization for patients with M1 occlusions.

Three-dimensional MR Fingerprinting for Quantitative Breast Imaging.

Purpose To develop a fast three-dimensional method for simultaneous T1 and T2 quantification for breast imaging by using MR fingerprinting. Materials and Methods In this prospective study, variable flip angles and magnetization preparation modules were applied to acquire MR fingerprinting data for each partition of a three-dimensional data set. A fast postprocessing method was implemented by using singular value decomposition. The proposed technique was first validated in phantoms and then applied to 15 healthy female participants (mean age, 24.2 years ± 5.1 [standard deviation]; range, 18-35 years) and 14 female participants with breast cancer (mean age, 55.4 years ± 8.8; range, 39-66 years) between March 2016 and April 2018. The sensitivity of the method to B1 field inhomogeneity was also evaluated by using the Bloch-Siegert method. Results Phantom results showed that accurate and volumetric T1 and T2 quantification was achieved by using the proposed technique. The acquisition time for three-dimensional quantitative maps with a spatial resolution of 1.6 × 1.6 × 3 mm3 was approximately 6 minutes. For healthy participants, averaged T1 and T2 relaxation times for fibroglandular tissues at 3.0 T were 1256 msec ± 171 and 46 msec ± 7, respectively. Compared with normal breast tissues, higher T2 relaxation time (68 msec ± 13) was observed in invasive ductal carcinoma (P < .001), whereas no statistical difference was found in T1 relaxation time (1183 msec ± 256; P = .37). Conclusion A method was developed for breast imaging by using the MR fingerprinting technique, which allows simultaneous and volumetric quantification of T1 and T2 relaxation times for breast tissues. © RSNA, 2018 Online supplemental material is available for this article.

Diagnostic Accuracy of a Rapid Biparametric MRI Protocol for Detection of Histologically Proven Prostate Cancer.

OBJECTIVE: To evaluate the performance of a rapid, low cost, noncontrast MRI examination as a secondary screening tool in detection of clinically significant prostate cancer. METHODS: In this prospective single institution study, 129 patients with elevated prostate-specific antigen levels or abnormal digital rectal examination findings underwent MRI with an abbreviated biparamatric MRI protocol consisting of high-resolution axial T2- and diffusion-weighted images. Index lesions were classified according to modified Prostate Imaging - Reporting and Data System (mPI-RADS) version 2.0. All patients underwent standard transrectal ultrasound-guided biopsy after MRI with the urologist being blinded to MRI results. Subsequently, all patients with suspicious lesions (mPI-RADS 3, 4, or 5) underwent cognitively guided targeted biopsy after discussion of MRI results with the urologist. Sensitivity and negative predictive value for identification of clinically significant prostate cancer (Gleason score 3+4 and above) were determined. RESULTS: Rapid biparametric MRI discovered 176 lesions identified in 129 patients. Rapid MRI detected clinically significant cancers with a sensitivity of 95.1% with a negative predictive value of 95.1% and positive predictive value of 53.2%, leading to a change in management in 10.8% of the patients. False negative rate of biparametric (bp) MRI was 4.7%. CONCLUSION: We found that a bp-MRI examination can detect clinically significant lesions and changed patient management in 10.8% of the patients. A rapid MRI protocol can be used as a useful secondary screening tool in men presenting with suspicion of prostate cancer.

Quantitative perfusion imaging of neoplastic liver lesions: A multi-institution study.

We describe multi-institutional experience using free-breathing, 3D Spiral GRAPPA-based quantitative perfusion MRI in characterizing neoplastic liver masses. 45 patients (age: 48-72 years) were prospectively recruited at University Hospitals, Cleveland, USA on a 3 Tesla (T) MRI, and at Zhongshan Hospital, Shanghai, China on a 1.5 T MRI. Contrast-enhanced volumetric T1-weighted images were acquired and a dual-input single-compartment model used to derive arterial fraction (AF), distribution volume (DV) and mean transit time (MTT) for the lesions and normal parenchyma. The measurements were compared using two-tailed Student's t-test, with Bonferroni correction applied for multiple-comparison testing. 28 hepatocellular carcinoma (HCC) and 17 metastatic lesions were evaluated. No significant difference was noted in perfusion parameters of normal liver parenchyma and neoplastic masses at two centers (p = 0.62 for AF, 0.015 for DV, 0.42 for MTT for HCC, p = 0.13 for AF, 0.97 for DV, 0.78 for MTT for metastases). There was statistically significant difference in AF, DV, and MTT of metastases and AF and DV of HCC compared to normal liver parenchyma (p < 0.5/9 = 0.0055). A statistically significant difference was noted in the MTT of metastases compared to hepatocellular carcinoma (p < 0.001*10-5). In conclusion, 3D Spiral-GRAPPA enabled quantitative free-breathing perfusion MRI exam provides robust perfusion parameters.

Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings.

BACKGROUND: Radiomic analysis is defined as computationally extracting features from radiographic images for quantitatively characterizing disease patterns. There has been recent interest in examining the use of MRI for identifying prostate cancer (PCa) aggressiveness in patients on active surveillance (AS). PURPOSE: To evaluate the performance of MRI-based radiomic features in identifying the presence or absence of clinically significant PCa in AS patients. STUDY TYPE: Retrospective. SUBJECTS MODEL: MRI/TRUS (transperineal grid ultrasound) fusion-guided biopsy was performed for 56 PCa patients on AS who had undergone prebiopsy. FIELD STRENGTH/SEQUENCE: 3T, T2 -weighted (T2 w) and diffusion-weighted (DW) MRI. ASSESSMENT: A pathologist histopathologically defined the presence of clinically significant disease. A radiologist manually delineated lesions on T2 w-MRs. Then three radiologists assessed MRIs using PIRADS v2.0 guidelines. Tumors were categorized into four groups: MRI-negative-biopsy-negative (Group 1, N = 15), MRI-positive-biopsy-positive (Group 2, N = 16), MRI-negative-biopsy-positive (Group 3, N = 10), and MRI-positive-biopsy-negative (Group 4, N = 15). In all, 308 radiomic features (First-order statistics, Gabor, Laws Energy, and Haralick) were extracted from within the annotated lesions on T2 w images and apparent diffusion coefficient (ADC) maps. The top 10 features associated with clinically significant tumors were identified using minimum-redundancy-maximum-relevance and used to construct three machine-learning models that were independently evaluated for their ability to identify the presence and absence of clinically significant disease. STATISTICAL TESTS: Wilcoxon rank-sum tests with P < 0.05 considered statistically significant. RESULTS: Seven T2 w-based (First-order Statistics, Haralick, Laws, and Gabor) and three ADC-based radiomic features (Laws, Gradient and Sobel) exhibited statistically significant differences (P < 0.001) between malignant and normal regions in the training groups. The three constructed models yielded overall accuracy improvement of 33, 60, 80% and 30, 40, 60% for patients in testing groups, when compared to PIRADS v2.0 alone. DATA CONCLUSION: Radiomic features could help in identifying the presence and absence of clinically significant disease in AS patients when PIRADS v2.0 assessment on MRI contradicted pathology findings of MRI-TRUS prostate biopsies. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Free-Breathing 3D Liver Perfusion Quantification Using a Dual-Input Two-Compartment Model.

The purpose of this study is to test the feasibility of applying a dual-input two-compartment liver perfusion model to patients with different pathologies. A total of 7 healthy subjects and 11 patients with focal liver lesions, including 6 patients with metastatic adenocarcinoma and 5 with hepatocellular carcinoma (HCC), were examined. Liver perfusion values were measured from both focal liver lesions and cirrhotic tissues (from the 5 HCC patients). Compared to results from volunteer livers, significantly higher arterial fraction, fractional volume of the interstitial space, and lower permeability-surface area product were observed for metastatic lesions, and significantly higher arterial fraction and lower vascular transit time were observed for HCCs (P < 0.05). Significantly lower arterial fraction and higher vascular transit time, fractional volume of the vascular space, and fractional volume of the interstitial space were observed for metastases in comparison to HCCs (P < 0.05). For cirrhotic livers, a significantly lower total perfusion, lower fractional volume of the vascular space, higher fractional volume of the interstitial space, and lower permeability-surface area product were noted in comparison to volunteer livers (P < 0.05). Our findings support the possibility of using this model with 3D free-breathing acquisitions for lesion and diffuse liver disease characterization.

Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation.

Multi-modal image co-registration via optimizing mutual information (MI) is based on the assumption that intensity distributions of multi-modal images follow a consistent relationship. However, images with a substantial difference in appearance violate this assumption, thus MI directly based on image intensity alone may be inadequate to drive similarity based co-registration. To address this issue, we introduce a novel approach for multi-modal co-registration called Multi-scale Spectral Embedding Registration (MSERg). MSERg involves the construction of multi-scale spectral embedding (SE) representations from multimodal images via texture feature extraction, scale selection, independent component analysis (ICA) and SE to create orthogonal representations that decrease the dissimilarity between the fixed and moving images to facilitate better co-registration. To validate the MSERg method, we aligned 45 pairs of in vivo prostate MRI and corresponding ex vivo histopathology images. The dataset was split into a learning set and a testing set. In the learning set, length scales of 5 × 5, 7 × 7 and 17 × 17 were selected. In the independent testing set, we compared MSERg with intensity-based registration, multi-attribute combined mutual information (MACMI) registration and scale-invariant feature transform (SIFT) flow registration. Our results suggest that multi-scale SE representations generated by MSERg are found to be more appropriate for radiology-pathology co-registration.