Soluble B-cell maturation antigen levels for disease monitoring in oligosecretory and nonsecretory relapsed multiple myeloma.

Soluble B-cell maturation antigen (sBCMA) is overexpressed on multiple myeloma (MM) cells. We investigated whether sBCMA levels correlated with other myeloma tumor volume indicators and its utility in monitoring oligo-secretory/non-secretory (O-S/Non-S) MM. In 115 patients with newly diagnosed MM, sBCMA was compared with M-protein levels, bone marrow plasma cells (BMPCs), circulating tumor cells (CTCs), and total diffusion volume (tDV; estimated by whole-body diffusion-weighted magnetic resonance imaging) at diagnosis. sBCMA levels increased significantly with International Staging System stage, chromosome 1q21 gain/amplification and CTC levels. sBCMA also correlated strongly with %BMPC (r = 0.65), moderately with tDV (r = 0.55) and paraprotein levels (involved immunoglobulin in IgG and IgA subtypes, r = 0.44 and 0.4; involved free light-chain levels in light-chain-only MM, r = 0.61, all P < 0.05). Longitudinal changes in sBCMA were consistent with disease status in both 17 O-S/Non-S and other secretory MM cases. Furthermore, sBCMA levels increased as early as 6 months pre-relapse in almost all O-S/Non-S relapsed patients. Thus, sBCMA correlates strongly with total tumor volume in MM, as assessed using different modalities. We suggest that sBCMA is useful, not only for monitoring responses in patients with O-S/Non-S MM but also for early relapse detection and prediction.

Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy.

BACKGROUND: Current cardiovascular magnetic resonance sequences cannot discriminate between different myocardial extracellular space (ECSs), including collagen, noncollagen, and inflammation. We sought to investigate whether cardiovascular magnetic resonance radiomics analysis can distinguish between noncollagen and inflammation from collagen in dilated cardiomyopathy. METHODS: We identified data from 132 patients with dilated cardiomyopathy scheduled for an invasive septal biopsy who underwent cardiovascular magnetic resonance at 3 T. Cardiovascular magnetic resonance imaging protocol included native and postcontrast T1 mapping and late gadolinium enhancement (LGE). Radiomic features were computed from the midseptal myocardium, near the biopsy region, on native T1, extracellular volume (ECV) map, and LGE images. Principal component analysis was used to reduce the number of radiomic features to 5 principal radiomics. Moreover, a correlation analysis was conducted to identify radiomic features exhibiting a strong correlation (r>0.9) with the 5 principal radiomics. Biopsy samples were used to quantify ECS, myocardial fibrosis, and inflammation. RESULTS: Four histopathological phenotypes were identified: low collagen (n=20), noncollagenous ECS expansion (n=49), mild to moderate collagenous ECS expansion (n=42), and severe collagenous ECS expansion (n=21). Noncollagenous expansion was associated with the highest risk of myocardial inflammation (65%). Although native T1 and ECV provided high diagnostic performance in differentiating severe fibrosis (C statistic, 0.90 and 0.90, respectively), their performance in differentiating between noncollagen and mild to moderate collagenous expansion decreased (C statistic: 0.59 and 0.55, respectively). Integration of ECV principal radiomics provided better discrimination and reclassification between noncollagen and mild to moderate collagen (C statistic, 0.79; net reclassification index, 0.83 [95% CI, 0.45-1.22]; P<0.001). There was a similar trend in the addition of native T1 principal radiomics (C statistic, 0.75; net reclassification index, 0.93 [95% CI, 0.56-1.29]; P<0.001) and LGE principal radiomics (C statistic, 0.74; net reclassification index, 0.59 [95% CI, 0.19-0.98]; P=0.004). Five radiomic features per sequence were identified with correlation analysis. They showed a similar improvement in performance for differentiating between noncollagen and mild to moderate collagen (native T1, ECV, LGE C statistic, 0.75, 0.77, and 0.71, respectively). These improvements remained significant when confined to a single radiomic feature (native T1, ECV, LGE C statistic, 0.71, 0.70, and 0.64, respectively). CONCLUSIONS: Radiomic features extracted from native T1, ECV, and LGE provide incremental information that improves our capability to discriminate noncollagenous expansion from mild to moderate collagen and could be useful for detecting subtle chronic inflammation in patients with dilated cardiomyopathy.

Expression of Tenascin-C Is Upregulated in the Early Stages of Radiation Pneumonitis/Fibrosis in a Novel Mouse Model.

The lung is a major dose-limiting organ for radiation therapy (RT) for cancer in the thoracic region, and the clarification of radiation-induced lung damage (RILD) is important. However, there have been few reports containing a detailed comparison of radiographic images with the pathological findings of radiation pneumonitis (RP)/radiation fibrosis (RF). We recently reported the upregulated expression of tenascin-C (TNC), an inflammation-associated extracellular matrix molecule, in surgically resected lung tissue, and elevated serum levels were elevated in a RILD patient. Therefore, we have developed a novel mouse model of partial lung irradiation and studied it with special attention paid to the computed tomography (CT) images and immunohistological findings. The right lungs of mice (BALB/c) were irradiated locally at 30 Gy/1fr, and the following two groups were created. In Group 1, sequential CT was performed to confirm the time-dependent changes in RILD. In Group 2, the CT images and histopathological findings of the lung were compared. RP findings were detected histologically at 16 weeks after irradiation; they were also observed on the CT images from 20 weeks. The immunostaining of TNC was observed before the appearance of RP on the CT images. The findings suggest that TNC could be an inflammatory marker preceding lung fibrosis.

Self-gated free-running 5D whole-heart MRI using blind source separation for automated cardiac motion extraction.

PURPOSE: To compare two blind source separation (BSS) techniques to principal component analysis and the electrocardiogram for the identification of cardiac triggers in self-gated free-running 5D whole-heart MRI. To ascertain the precision and robustness of the techniques, they were compared in three different noise and contrast regimes. METHODS: The repeated superior-inferior (SI) projections of a 3D radial trajectory were used to extract the physiological signals in three cardiac MRI cohorts: (1) 9 healthy volunteers without contrast agent injection at 1.5T, (2) 30 ferumoxytol-injected congenital heart disease patients at 1.5T, and (3) 12 gadobutrol-injected patients with suspected coronary artery disease at 3T. Self-gated cardiac triggers were extracted with the three algorithms (principal component analysis [PCA], second-order blind identification [SOBI], and independent component analysis [ICA]) and the difference with the electrocardiogram triggers was calculated. PCA and SOBI triggers were retained for image reconstruction. The image sharpness was ascertained on whole-heart 5D images obtained with PCA and SOBI and compared among the three cohorts. RESULTS: SOBI resulted in smaller trigger differences in Cohorts 1 and 3 compared to PCA (p < 0.01) and in all cohorts compared to ICA (p < 0.04). In Cohorts 1 and 3, the sharpness increased significantly in the reconstructed images when using SOBI instead of PCA (p < 0.03), but not in Cohort 2 (p = 0.4). CONCLUSION: We have shown that SOBI results in more precisely extracted self-gated triggers than PCA and ICA. The validation across three diverse cohorts demonstrates the robustness of the method against acquisition variability.

Novel deep-learning analysis for connective tissue disease -related interstitial lung disease extent assessment on CT: a preliminary cross-sectional study.

OBJECTIVES: Physician's evaluation of interstitial lung disease (ILD) extension with high-resolution computed tomography (HRCT) has limitations such as lack of objectivity and reproducibility. This study aimed to investigate the utility of computer-based deep-learning analysis using QZIP-ILD® software (DL-QZIP) compared with conventional approaches in connective tissue disease (CTD) -related ILD. METHODS: Patients with CTD-ILD visiting our Rheumatology Centre between December 2020 and April 2024 were recruited. Quantitative scores, including the percentage of lung involvement in ground-glass opacity (QGG), total fibrotic lesion (QFIB), and overall ILD extension encompassing both QGG and QFIB (QILD), calculated by DL-QZIP, were compared with semiquantitative visual method, employing intraclass correlation coefficients (ICC). We compared the capability of QILD scores to distinguish patients with forced vital capacity (FVC) % <70 in both methods determined by the area under the curve (AUC) by the receiver-operating characteristic curve analysis and DeLong's test. RESULTS: Eighty patients (median age, 66 years; 14 men) were included. Median QGG, QFIB, and QILD scores were 3.45%, 2.19%, and 5.35% using DL-QZIP, and 3.25%, 4.06%, and 8.48% using visual method, respectively. Correlations between DL-QZIP and visual method were 0.75 for QGG, 0.61 for QFIB, and 0.75 for QILD. The AUC of QILD scores for FVC% <70 was significantly higher with DL-QZIP (0.833) compared with visual method (0.660) (p < 0.01). CONCLUSION: QZIP-ILD® demonstrates superior capability in distinguishing patients with a radiological scenario correlated to severe physiological impairment, while showing relatively good correlations in quantifying the extent on HRCT compared with conventional method in CTD-ILD.

Relationship between microvascular status and diagnostic performance of stress dynamic CT perfusion imaging.

OBJECTIVES: This study aimed to investigate the relationship between microvascular status in the non-ischemic myocardium and the diagnostic performance of stress dynamic CT perfusion imaging (CTP) in detecting hemodynamically significant stenosis. MATERIALS AND METHODS: This study included 157 patients who underwent coronary computed tomography angiography (CTA), CTP, and invasive coronary angiography (ICA), including fractional flow reserve (FFR). Hemodynamically significant stenosis was defined by FFR and ICA. A relative myocardial blood flow (MBF) for each myocardial segment was normalized to the highest MBF (remote MBF) among 16 segments. RESULTS: The receiver operating characteristic curve analysis for detecting hemodynamically significant stenosis at the vessel level indicated that patients with lower, intermediate, and higher remote MBF had areas under the curve (AUC) of 0.66, 0.70, and 0.80, respectively, for absolute MBF and AUCs of 0.63, 0.70, and 0.83, respectively, for relative MBF. The optimal cut-off values for absolute MBF were proportional to the levels of remote MBFs, while the ones for relative MBF were more consistent across lower to higher remote MBFs. For the patients with high remote MBF, the relative MBF demonstrated a sensitivity of 69%, specificity of 88%, and accuracy of 85% in detecting hemodynamically significant stenosis. CONCLUSION: The microvascular status in the non-ischemic myocardium influenced the diagnostic performance of dynamic CTP and threshold values of absolute MBFs, suggesting the potential preference for relative MBF over absolute MBF in clinical settings. Dynamic CTP's quantification of MBF offers the benefit of indicating reliability in ischemia detection relative to microvascular status. KEY POINTS: Question The relationship between microvascular status and diagnostic performance of dynamic CTP imaging has not been fully investigated. Findings The diagnostic performance of dynamic CTP and threshold values of absolute MBF were impacted by microvascular status. Clinical relevance The differences in diagnostic accuracy of dynamic CTP related to varying remote MBF values necessitate a personalized evaluation of myocardial perfusion in dynamic CTP images.

Evaluation of Effectiveness of Thoracic Endovascular Treatment for Infectious Aortic Diseases.

PURPOSE: The aim of study is to investigate the efficacy of thoracic endovascular aortic repair for infectious aortic diseases. MATERIALS AND METHODS: Patients who underwent thoracic endovascular repair for infectious aortic diseases including mycotic thoracic aortic aneurysm, aorto-bronchial fistula and aorto-enteric fistula from December 2011 to October 2022 at four institutions were retrospectively studied. The primary outcome of the study was overall survival, whereas the secondary outcome was comprehensive adverse event. Comprehensive adverse events were defined as a combination of deaths, aortic events, and infectious adverse events. RESULTS: A total of 28 patients were included in the analysis, with 13 patients having mycotic thoracic aortic aneurysms, 12 having aorto-bronchial fistulas, and 3 having aorto-enteric fistulas. Seven patients (25%) underwent additional procedures (abscess drainage, 6 cases; total esophagectomy, 1 case). The mean follow-up period was 30.0 ± 33.9 months. The 1-year and 5-year survival rates were 85.7% and 67.9%, respectively. The 1-year and 5-year aorta-related complication-free survival rates were 64.3% and 42.9%, respectively. On univariate analysis, the presence of an aorto-bronchial fistula was associated with a higher risk of comprehensive adverse events (odds ratio [OR] = 11, P = 0.04). CONCLUSION: TEVAR might be a promising treatment for infectious thoracic aortic diseases. Among the infectious pathologies, ABF was considered ominous in terms of late outcomes.

Radiomics-based prediction of nonalcoholic fatty liver disease following pancreatoduodenectomy.

PURPOSE: Predicting nonalcoholic fatty liver disease (NAFLD) following pancreaticoduodenectomy (PD) is challenging, which delays therapeutic intervention and makes its prevention difficult. We conducted this study to assess the potential application of preoperative computed tomography (CT) radiomics for predicting NAFLD. METHODS: The subjects of this retrospective study were 186 patients with PD from a single institution. We extracted the predictors of NAFLD after PD statistically from conventional clinical and radiomic features of the estimated remnant pancreas and whole liver region on preoperative nonenhanced CT images. Based on these predictors, we developed a machine-learning predictive model, which integrated clinical and radiomic features. A comparative model used only clinical features as predictors. RESULTS: The incidence of NAFLD after PD was 43.5%. The variables of the clinicoradiomic model included one shape feature of the pancreas, two texture features of the liver, and sex; the variables of the clinical model were age, sex, and chemoradiotherapy. The accuracy%, precision%, recall%, F1 score, and area under the curve of the two models were 75.0, 72.7, 66.7, 69.6, and 0.80; and 69.6, 68.4, 54.2, 60.5, and 0.69, respectively. CONCLUSIONS: Preoperative CT-derived radiomic features from the pancreatic and liver regions are promising for the prediction of NAFLD post-PD. Using these features enhances the predictive model, enabling earlier intervention for high-risk patients.

Complementary prognostic value of stress perfusion imaging and global coronary flow reserve derived from cardiovascular magnetic resonance: a long-term cohort study.

BACKGROUND: Phase-contrast cine cardiovascular magnetic resonance (CMR) quantifies global coronary flow reserve (CFR) by measuring blood flow in the coronary sinus (CS), allowing assessment of the entire coronary circulation. However, the complementary prognostic value of stress perfusion CMR and global CFR in long-term follow-up has yet to be investigated. This study aimed to investigate the complementary prognostic value of stress myocardial perfusion imaging and global CFR derived from CMR in patients with suspected or known coronary artery disease (CAD) during long-term follow-up. METHODS: Participants comprised 933 patients with suspected or known CAD who underwent comprehensive CMR. Major adverse cardiac events (MACE) comprised cardiac death, non-fatal myocardial infarction, unstable angina, hospitalization for heart failure, stroke, ventricular arrhythmia, and late revascularization. RESULTS: During follow-up (median, 5.3 years), there were 223 MACE. Kaplan-Meier curve analysis revealed a significant difference in event-free survival among tertile groups for global CFR (log-rank, p < 0.001) and between patients with and without ischemia (p < 0.001). The combination of stress perfusion CMR and global CFR enhanced risk stratification (p < 0.001 for overall), and prognoses were comparable between the subgroup with ischemia and no impaired CFR and the subgroup with no ischemia and impaired CFR (p = 0.731). Multivariate Cox proportional hazard regression analysis showed that impaired CFR remained a significant predictor for MACE (hazard ratio, 1.6; p = 0.002) when adjusted for coronary risk factors and CMR predictors, including ischemia. The addition of impaired CFR to coronary risk factors and ischemia significantly increased the global chi-square value from 88 to 109 (p < 0.001). Continuous net reclassification improvement and integrated discrimination with the addition of global CFR to coronary risk factors plus ischemia improved to 0.352 (p < 0.001) and 0.017 (p < 0.001), respectively. CONCLUSIONS: During long-term follow-up, stress perfusion CMR and global CFR derived from CS flow measurement provided complementary prognostic value for prediction of cardiovascular events. Microvascular dysfunction or diffuse atherosclerosis as shown by impaired global CFR may play a role as important as that of ischemia due to epicardial coronary stenosis in the risk stratification of CAD patients.

Effect of Gaussian Smoothing Filter Size for CT-Based Attenuation Correction on Quantitative Assessment of Bone SPECT/CT: A Phantom Study.

This study aims to determine the effect of Gaussian filter size for CT-based attenuation correction (CTAC) on the quantitative assessment of bone SPECT. An experiment was performed using a cylindrical phantom containing six rods, of which one was filled with water and five were filled with various concentrations of K2HPO4 solution (120-960 mg/cm3) to simulate different bone densities. 99mTc-solution of 207 kBq/ml was also included within the rods. SPECT data were acquired at 120 views for 30 s/view. CT for attenuation correction were obtained at 120 kVp and 100 mA. Sixteen different CTAC maps processed with different Gaussian filter sizes (ranging from 0 to 30 mm in 2 mm increments) were generated. SPECT images were reconstructed for each of the 16 CTAC maps. Attenuation coefficients and radioactivity concentrations in the rods were compared with those in the water-filled rod without K2HPO4 solution as a reference. Gaussian filter sizes below 14-16 mm resulted in an overestimation of radioactivity concentrations for rods with high concentrations of K2HPO4 (≥ 666 mg/cm3). The overestimation of radioactivity concentration measurement was 3.8% and 5.5% for 666 mg/cm3 and 960 mg/cm3 K2HPO4 solutions, respectively. The difference in radioactivity concentration between the water rod and the K2HPO4 rods was minimal at 18-22 mm. The use of Gaussian filter sizes smaller than 14-16 mm caused an overestimation of radioactivity concentration in regions of high CT values. Setting the Gaussian filter size to 18-22 mm enables radioactivity concentration to be measured with the least influence on bone density.

Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method.

The purpose is to evaluate whether deep learning-based denoising (DLD) algorithm provides sufficient image quality for abdominal computed tomography (CT) with a 30% reduction in radiation dose, compared to standard-dose CT reconstructed with conventional hybrid iterative reconstruction (IR). The subjects consisted of 50 patients who underwent abdominal CT with standard dose and reconstructed with hybrid IR (ASiR-V50%) and another 50 patients who underwent abdominal CT with approximately 30% less dose and reconstructed with ASiR-V50% and DLD at low-, medium- and high-strength (DLD-L, DLD-M and DLD-H, respectively). The standard deviation of attenuation in liver parenchyma was measured as image noise. Contrast-to-noise ratio (CNR) for portal vein on portal venous phase was calculated. Lesion conspicuity in 23 abdominal solid mass on the reduced-dose CT was rated on a 5-point scale: 0 (best) to -4 (markedly inferior). Compared with hybrid IR of standard-dose CT, DLD-H of reduced-dose CT provided significantly lower image noise (portal phase: 9.0 (interquartile range, 8.7-9.4) HU vs 12.0 (11.4-12.7) HU, P < 0.0001) and significantly higher CNR (median, 5.8 (4.4-7.4) vs 4.3 (3.3-5.3), P = 0.0019). As for DLD-M of reduced-dose CT, no significant difference was found in image noise and CNR compared to hybrid IR of standard-dose CT (P > 0.99). Lesion conspicuity scores for DLD-H and DLD-M were significantly better than hybrid IR (P < 0.05). Dynamic contrast-enhanced abdominal CT acquired with approximately 30% lower radiation dose and generated with the DLD algorithm exhibit lower image noise and higher CNR compared to standard-dose CT with hybrid IR.

Therapeutic window for obtaining favorable remodeling after thoracic endovascular aortic repair of type B aortic dissection.

OBJECTIVE: The purpose of the present study was to determine the most appropriate timing for thoracic endovascular aortic repair (TEVAR) of type B aortic dissection (TBAD) in terms of remodeling of the aorta. METHODS: A total of 41 patients who had undergone TEVAR for the treatment of aortic dissection were included in the present study. The patients were divided into two groups: those who had undergone TEVAR in the acute or subacute phase (group A) and those who had undergone TEVAR in the chronic phase (group B). The indications for TEVAR as the treatment of TBAD were the presence of aortic rupture or malperfusion of the aortic branches, a maximum aortic diameter of ≥40 mm on the initial diagnostic computed tomography scan, and/or expansion of the aorta of ≥5 mm within 3 months for acute and subacute TBAD. The indication was a maximum aortic diameter of ≥50 mm or expansion of the aorta of ≥5 mm within 1 year for chronic TBAD. The diameters of the aorta, true lumen, and false lumen were measured at the level of the most dilated part of the descending aorta (level M) and at the diaphragm (level D) on the computed tomography scan obtained before TEVAR and at the 2-year follow-up examination. RESULTS: The median interval between TEVAR and the onset of TBAD was 0.2 month (interquartile range, 0.03-0.7 month) in group A (n = 21) and 32 months (interquartile range, 4.7-35.2 months) in group B (n = 20). Except for the aortic diameter at level D in group B, favorable remodeling was obtained at both levels in both groups. The diameter change ratio of the aorta at level D was significantly greater in group A than in group B (P = .02). Receiver operating characteristic curve analysis of the interval for a significant decrease in the aortic diameter at level D yielded 4.2 months as the optimal threshold for performing TEVAR (area under the curve, 0.859; 95% confidence interval, 0.7-1.0). CONCLUSIONS: TEVAR for TBAD will result in favorable outcomes, irrespective of the timing of the procedure. However, it might be more effective to perform TEVAR within 4.2 months of the onset of TBAD, provided that the TEVAR procedure can be performed safely.

Deep learning image reconstruction for improving image quality of contrast-enhanced dual-energy CT in abdomen.

OBJECTIVES: To evaluate the usefulness of deep learning image reconstruction (DLIR) to improve the image quality of dual-energy computed tomography (DECT) of the abdomen, compared to hybrid iterative reconstruction (IR). METHODS: This study included 40 patients who underwent contrast-enhanced DECT of the abdomen. Virtual monochromatic 40-, 50-, and 70-keV and iodine density images were reconstructed using three reconstruction algorithms, including hybrid IR (ASiR-V50%) and DLIR (TrueFidelity) at medium- and high-strength level (DLIR-M and DLIR-H, respectively). The standard deviation of attenuation in liver parenchyma was measured as image noise. The contrast-to-noise ratio (CNR) for the portal vein on portal venous phase CT was calculated. The vessel conspicuity and overall image quality were graded on a 5-point scale ranging from 1 (poor) to 5 (excellent). The comparative scale of lesion conspicuity in 47 abdominal solid lesions was evaluated on a 5-point scale ranging from 0 (best) to -4 (markedly inferior). RESULTS: The image noise of virtual monochromatic 40-, 50 -, and 70-keV and iodine density images was significantly decreased by DLIR compared to hybrid IR (p < 0.0001). The CNR was significantly higher in DLIR-H and DLIR-M than in hybrid IR (p < 0.0001). The vessel conspicuity and overall image quality scores were also significantly greater in DLIR-H and DLIR-M than in hybrid IR (p < 0.05). The lesion conspicuity scores for DLIR-M and DLIR-H were significantly higher than those for hybrid IR in the virtual monochromatic image of all energy levels (p ≤ 0.001). CONCLUSIONS: DLIR improves vessel conspicuity, CNR, and lesion conspicuity of virtual monochromatic and iodine density images in abdominal contrast-enhanced DECT, compared to hybrid IR. KEY POINTS: • Deep learning image reconstruction (DLIR) is useful for reducing image noise and improving the CNR of visual monochromatic 40-, 50-, and 70-keV images in dual-energy CT. • DLIR can improve lesion conspicuity of abdominal solid lesions on virtual monochromatic images compared to hybrid iterative reconstruction. • DLIR can also be applied to iodine density maps and significantly improves their image quality.

Evaluation of cortical superficial siderosis in patients with cognitive dysfunction using 3D FLAIR and 3D DIR.

OBJECTIVES: Our aim was to evaluate the detectability of cortical superficial siderosis (cSS) by 3D FLAIR and 3D DIR images in comparison with the SWI images in patients with cognitive dysfunction. METHODS: We studied 246 patients with cognitive dysfunction (144 women, 102 men; mean age: 75.5 ± 7.53 years) who visited a memory clinic at our hospital and underwent MR examinations at 3 T. Specifically, 16 patients with Alzheimer disease (AD) (n = 11) and AD with cerebrovascular disease (n = 5) manifested cSS based on SWI. Each set of MR images (3D FLAIR and 3D DIR) was reviewed by two reviewers separately for the detection of sulcal hyperintensity that suggested cSS. RESULTS: SWI detected a greater number of cSS sulci than 3D DIR and 3D FLAIR. The sensitivity and specificity for the detection of sulcal hyperintensity were the same between 3D FLAIR and 3D DIR (87.5%/100%). However, 3D DIR detected a greater number of cSS sulci than 3D FLAIR (p = .005). CONCLUSIONS: Our study showed that 3D DIR and 3D FLAIR can detect sulcal hyperintensity related to cSS although they are less sensitive to cSS lesions than SWI. KEY POINTS: • 3D FLAIR and 3D DIR can show sulcal signal abnormalities related to cSS in patients with cognitive dysfunction. • 3D FLAIR and 3D DIR detect sulcal hyperintensity of cSS, although they are less sensitive to cSS than SWI. • Signal alterations due to cSS are more detectable in 3D DIR than in 3D FLAIR.

Long-term prognostic value of whole-heart coronary magnetic resonance angiography.

BACKGROUND: Coronary magnetic resonance angiography (CMRA) allows non-ionizing visualization of luminal narrowing in coronary artery disease (CAD). Although a prior study showed the usefulness of CMRA for risk stratification in short-term follow-up, the long-term prognostic value of CMRA remains unclear. The purpose of this study was to evaluate the long-term prognostic value of CMRA. METHODS: A total of 506 patients without history of myocardial infarction or prior coronary artery revascularization underwent free-breathing whole-heart CMRA between 2009 and 2015. Images were acquired using a 1.5 T or 3 T scanner and visually evaluated as the consensus decisions of two observers. Obstructive CAD on CMRA was defined as luminal narrowing of ≥ 50% in at least one coronary artery. Major adverse cardiac events (MACE) comprised cardiac death, nonfatal myocardial infarction, and unstable angina. RESULTS: Obstructive CAD on CMRA was observed in 214 patients (42%). During follow-up (median, 5.6 years), 31 MACE occurred. Kaplan-Meier curve analysis revealed a significant difference in event-free survival between patients with and without obstructive CAD for MACE (log-rank, p = 0.003) and cardiac death (p = 0.012). Annualized event rates for MACE in patients with no obstructive CAD, 1-vessel disease, 2-vessel disease, and left-main or 3-vessel disease were 0.6%, 1.5%, 2.3%, and 3.6%, respectively (log-rank, p = 0.003). Cox proportional hazard regression analysis showed that, among obstructive CAD on CMRA and clinical risk factors (age, sex, hypertension, diabetes, dyslipidemia, smoking, and family history of CAD), obstructive CAD and diabetes were significant predictors of MACE (hazard ratios, 2.9 [p = 0.005] and 2.2 [p = 0.034], respectively). In multivariate analysis, obstructive CAD remained an independent predictor (adjusted hazard ratio, 2.6 [p = 0.010]) after adjusting for diabetes. Addition of obstructive CAD to clinical risk factors significantly increased the global chi-square result from 8.3 to 13.8 (p = 0.022). CONCLUSIONS: In long-term follow-up, free breathing whole heart CMRA allows non-invasive risk stratification for MACE and cardiac death and provides incremental prognostic value over conventional risk factors in patients without a history of myocardial infarction or prior coronary artery revascularization. The presence and severity of obstructive CAD detected by CMRA were associated with worse prognosis. Importantly, patients without obstructive CAD on CMRA displayed favorable prognosis.

Cardiovascular magnetic resonance in women with cardiovascular disease: position statement from the Society for Cardiovascular Magnetic Resonance (SCMR).

This document is a position statement from the Society for Cardiovascular Magnetic Resonance (SCMR) on recommendations for clinical utilization of cardiovascular magnetic resonance (CMR) in women with cardiovascular disease. The document was prepared by the SCMR Consensus Group on CMR Imaging for Female Patients with Cardiovascular Disease and endorsed by the SCMR Publications Committee and SCMR Executive Committee. The goals of this document are to (1) guide the informed selection of cardiovascular imaging methods, (2) inform clinical decision-making, (3) educate stakeholders on the advantages of CMR in specific clinical scenarios, and (4) empower patients with clinical evidence to participate in their clinical care. The statements of clinical utility presented in the current document pertain to the following clinical scenarios: acute coronary syndrome, stable ischemic heart disease, peripartum cardiomyopathy, cancer therapy-related cardiac dysfunction, aortic syndrome and congenital heart disease in pregnancy, bicuspid aortic valve and aortopathies, systemic rheumatic diseases and collagen vascular disorders, and cardiomyopathy-causing mutations. The authors cite published evidence when available and provide expert consensus otherwise. Most of the evidence available pertains to translational studies involving subjects of both sexes. However, the authors have prioritized review of data obtained from female patients, and direct comparison of CMR between women and men. This position statement does not consider CMR accessibility or availability of local expertise, but instead highlights the optimal utilization of CMR in women with known or suspected cardiovascular disease. Finally, the ultimate goal of this position statement is to improve the health of female patients with cardiovascular disease by providing specific recommendations on the use of CMR.

Cardiovascular magnetic resonance feature tracking for characterization of patients with heart failure with preserved ejection fraction: correlation of global longitudinal strain with invasive diastolic functional indices.

BACKGROUND: Left ventricular (LV) diastolic dysfunction is the main cause of heart failure with preserved ejection fraction (HFpEF), and is characterized by LV stiffness and relaxation. Abnormal LV global longitudinal strain (GLS) is frequently observed l in HFpEF, and was shown to be useful in identifying HFpEF patients at high risk for a cardiovascular event. Cardiovascular magnetic resonance (CMR) feature tracking (CMR-FT) enables the reproducible and non-invasive assessment of global strain from cine CMR images. However, the association between GLS and invasively measured parameters of diastolic function has not been investigated. We sought to determine the prevalence and severity of GLS impairment in patients with HFpEF by using CMR-FT, and to evaluate the correlation between GLS measured by CMR-FT and that measured by invasive diastolic functional indices. METHODS: Eighteen patients with HFpEF and 18 age- and sex-matched healthy control subjects were studied. All subjects underwent cine, pre- and post-contrast T1 mapping and late gadolinium-enhancement CMR. In the HFpEF patients, invasive pressure-volume loops were obtained to evaluate LV diastolic properties. GLS was quantified from cine CMR, and extracellular volume fraction (ECV) was quantified from pre- and post-contrast T1 mapping as a known imaging biomarker for predicting LV stiffness. RESULTS: GLS was significantly impaired in patients with HFpEF (- 14.8 ± 3.3 vs.-19.5 ± 2.8%, p < 0.001). Thirty nine percent (7/18) of HFpEF patients showed impaired GLS with a cut-off of - 13.9%. Statistically significant difference was found in ECV between HFpEF patients and controls (32.2 ± 3.8% vs. 29.9 ± 2.6%, p = 0.044). In HFpEF patients, the time constant of active LV relaxation (Tau) was strongly correlated with GLS (r = 0.817, p < 0.001), global circumferential strain (GCS) (r = 0.539, p = 0.021) and global radial strain (GRS) (r = - 0.552, p = 0.017). Multiple linear regression analysis revealed GLS as the only independent predictor of altered Tau (beta = 0.817, p < 0.001) among age, LV end-diastolic volume index, LV end-systolic volume index, LV mass index, GCS, GRS and GLS. CONCLUSIONS: CMR-FT is a noninvasive approach that enables identification of the subgroup of HFpEF patients with impaired GLS. CMR LV GLS independently predicts abnormal invasive LV relaxation index Tau measurements in HFpEF patients. These findings suggest that feature-tracking CMR analysis in conjunction with ECV, may enable evaluation of diastolic dysfunction in patients with HFpEF.

Evaluation of Intradural Ecchordosis Physaliphora With Three-Dimensional Fluid-Attenuated Inversion Recovery.

OBJECTIVE: This study evaluated the efficacy of 3-dimensional fluid-attenuated inversion recovery (3D FLAIR) for detecting intradural ecchordosis physaliphora (EP). METHODS: We retrospectively determined the presence or absence of intradural EP on 3D FLAIR for 3888 consecutive patients, classifying the EP as "classical" or "possible" and analyzing the prevalence, size, and presence or absence of an intraosseous stalk. Where available, magnetic resonance cisternography images were compared with the 3D FLAIR images. RESULTS: Intradural EP was identified in 50 patients (1.3%): 36 (0.9%) classical and 14 (0.4%) possible. The classical EPs were significantly larger than the possible EPs (P < 0.01). Nine EPs (18.0%) showed an osseous stalk. Magnetic resonance cisternography was performed for 19 EPs (16 classical, 3 possible), detecting all 16 classical EPs but none of the possible EPs. CONCLUSIONS: Classical EPs were detected by 3D FLAIR as with magnetic resonance cisternography. The 3D FLAIR findings suggested a new type of possible EP variant previously unreported.

Improving Image Resolution of Whole-Heart Coronary MRA Using Convolutional Neural Network.

Whole-heart coronary magnetic resonance angiography (WHCMRA) permits the noninvasive assessment of coronary artery disease without radiation exposure. However, the image resolution of WHCMRA is limited. Recently, convolutional neural networks (CNNs) have obtained increased interest as a method for improving the resolution of medical images. The purpose of this study is to improve the resolution of WHCMRA images using a CNN. Free-breathing WHCMRA images with 512 × 512 pixels (pixel size = 0.65 mm) were acquired in 80 patients with known or suspected coronary artery disease using a 1.5 T magnetic resonance (MR) system with 32 channel coils. A CNN model was optimized by evaluating CNNs with different structures. The proposed CNN model was trained based on the relationship of signal patterns between low-resolution patches (small regions) and the corresponding high-resolution patches using a training dataset collected from 40 patients. Images with 512 × 512 pixels were restored from 256 × 256 down-sampled WHCMRA images (pixel size = 1.3 mm) with three different approaches: the proposed CNN, bicubic interpolation (BCI), and the previously reported super-resolution CNN (SRCNN). High-resolution WHCMRA images obtained using the proposed CNN model were significantly better than those of BCI and SRCNN in terms of root mean squared error, peak signal to noise ratio, and structure similarity index measure with respect to the original WHCMRA images. The proposed CNN approach can provide high-resolution WHCMRA images with better accuracy than BCI and SRCNN. The high-resolution WHCMRA obtained using the proposed CNN model will be useful for identifying coronary artery disease.