Deep Learning Virtual Contrast-Enhanced T1 Mapping for Contrast-Free Myocardial Extracellular Volume Assessment.

BACKGROUND: The acquisition of contrast-enhanced T1 maps to calculate extracellular volume (ECV) requires contrast agent administration and is time consuming. This study investigates generative adversarial networks for contrast-free, virtual extracellular volume (vECV) by generating virtual contrast-enhanced T1 maps. METHODS AND RESULTS: This retrospective study includes 2518 registered native and contrast-enhanced T1 maps from 1000 patients who underwent cardiovascular magnetic resonance at 1.5 Tesla. Recent hematocrit values of 123 patients (hold-out test) and 96 patients from a different institution (external evaluation) allowed for calculation of conventional ECV. A generative adversarial network was trained to generate virtual contrast-enhanced T1 maps from native T1 maps for vECV creation. Mean and SD of the difference per patient (ΔECV) were calculated and compared by permutation of the 2-sided t test with 10 000 resamples. For ECV and vECV, differences in area under the receiver operating characteristic curve (AUC) for discriminating hold-out test patients with normal cardiovascular magnetic resonance versus myocarditis or amyloidosis were tested with Delong's test. ECV and vECV showed a high agreement in patients with myocarditis (ΔECV: hold-out test, 2.0%±1.5%; external evaluation, 1.9%±1.7%) and normal cardiovascular magnetic resonance (ΔECV: hold-out test, 1.9%±1.4%; external evaluation, 1.5%±1.2%), but variations in amyloidosis were higher (ΔECV: hold-out test, 6.2%±6.0%; external evaluation, 15.5%±6.4%). In the hold-out test, ECV and vECV had a comparable AUC for the diagnosis of myocarditis (ECV AUC, 0.77 versus vECV AUC, 0.76; P=0.76) and amyloidosis (ECV AUC, 0.99 versus vECV AUC, 0.96; P=0.52). CONCLUSIONS: Generation of vECV on the basis of native T1 maps is feasible. Multicenter training data are required to further enhance generalizability of vECV in amyloidosis.

Computer tomography-based assessment of perivascular adipose tissue in patients with abdominal aortic aneurysms.

This retrospective study investigates perivascular adipose tissue (PVAT) alterations in CT as a marker of inflammation in patients with abdominal aortic aneurysms (AAA). 100 abdominal CT scans of patients with abdominal aortic aneurysms and 100 age and sex matched controls without underlying aortic disease were included. Artificial Intelligence (AI) assisted segmentation of the aorta and the surrounding adipose tissue was performed. Adipose tissue density was measured in Hounsfield units (HU) close (2-5mm, HUclose) and distant (10-12mm, HUdistant) to the aortic wall. To investigate alterations in adipose tissue density close to the aorta (HUclose) as a potential marker of inflammation, we calculated the difference HUΔ = HUclose-HUdistant and the fat attenuation ratio HUratio = HUclose/HUdistant as normalized attenuation measures. These two markers were compared i) inter-individually between AAA patients and controls and ii) intra-individually between the aneurysmal and non-aneurysmal segments in AAA patients. Since most AAAs are generally observed infrarenal, the aneurysmal section of the AAA patients was compared with the infrarenal section of the aorta of the control patients. In inter-individual comparisons, higher HUΔ and a lower HUratio were observed (aneurysmal: 8.9 ± 5.1 HU vs. control: 6.9 ± 4.8 HU, p-value = 0.006; aneurysmal: 89.8 ± 5.7% vs. control: 92.1 ± 5.5% p-value = 0.004). In intra-individual comparisons, higher HUΔ and lower HUratio were observed (aneurysmal: 8.9 ± 5.1 HU vs. non-aneurysmal: 5.5 ± 4.1 HU, p-value < 0.001; aneurysmal: 89.8 ± 5.7% vs. non-aneurysmal 93.3 ± 4.9%, p-value < 0.001). The results indicate PVAT density alterations in AAA patients. This motivates further research to establish non-invasive imaging markers for vascular and perivascular inflammation in AAA.

Fetal Cardiovascular Magnetic Resonance Feature Tracking Myocardial Strain Analysis in Congenital Heart Disease.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is an emerging imaging modality for assessing anatomy and function of the fetal heart in congenital heart disease (CHD). This study aimed to evaluate myocardial strain using fetal CMR feature tracking (FT) in different subtypes of CHD. METHODS: Fetal CMR FT analysis was retrospectively performed on four-chamber cine images acquired with Doppler US gating at 3 Tesla. Left ventricular (LV) global longitudinal strain (GLS), LV global radial strain (GRS), LV global longitudinal systolic strain rate (SR), and right ventricular (RV) GLS were quantified using a dedicated software optimized for fetal strain analysis. Analysis was performed in normal fetuses and different CHD subtypes (d-Transposition of the great arteries (dTGA), hypoplastic left heart syndrome (HLHS), coarctation of the aorta (CoA), tetralogy of Fallot (TOF), RV-dominant atrioventricular septal defect (AVSD), and critical pulmonary stenosis or atresia (PS/PA)). Analyses of variance (ANOVA) with Tukey post-hoc test was used for group comparisons. RESULTS: A total of 60 fetuses were analyzed (8/60 (13%) without CHD, 52/60 (87%) with CHD). Myocardial strain was successfully assessed in 113/120 ventricles (94%). Compared to controls, LV GLS was significantly reduced in fetuses with HLHS (-18.6±2.7% vs. -6.2±5.6%; p<0.001) and RV-dominant AVSD (-18.6±2.7% vs. -7.7±5.0%; p=0.003) and higher in fetuses with CoA (-18.6±2.7% vs. -25.0±4.3%; p=0.038). LV GRS was significantly reduced in fetuses with HLHS (25.7±7.5% vs. 11.4±9.7%; p=0.024). Compared to controls, RV GRS was significantly reduced in fetuses with PS/PA (-16.1±2.8% vs. -8.3±4.2%; p=0.007). Across all strain parameters, no significant differences were present between controls and fetuses diagnosed with dTGA and TOF. CONCLUSIONS: Fetal myocardial strain assessment with CMR FT in CHD is feasible. Distinct differences are present between various types of CHD, suggesting potential implications for clinical decision-making and prognostication in fetal CHD.

Autofluorescence-based tissue characterization enhances clinical prospects of light-sheet-microscopy.

Light sheet fluorescence microscopy (LSFM) is a transformative imaging method that enables the visualization of non-dissected specimen in real-time 3D. Optical clearing of tissues is essential for LSFM, typically employing toxic solvents. Here, we test the applicability of a non-hazardous alternative, ethyl cinnamate (ECi). We comprehensively characterized autofluorescence (AF) spectra in diverse murine tissues-ocular globe, knee, and liver-employing LSFM under various excitation wavelengths (405-785 nm) to test the feasibility of unstained samples for diagnostic purposes, in particular regarding percutaneous biopsies, as they constitute to most harvested type of tissue sample in clinical routine. Ocular globe structures were best discerned with 640 nm excitation. Knee tissue showed complex variation in AF spectra variation influenced by tissue depth and structure. Liver exhibited a unique AF pattern, likely linked to vasculature. Hepatic tissue samples were used to demonstrate the compatibility of our protocol for antibody staining. Furthermore, we employed machine learning to augment raw images and segment liver structures based on AF spectra. Radiologists rated representative samples transferred to the clinical assessment software. Learning-generated images scored highest in quality. Additionally, we investigated an actual murine biopsy. Our study pioneers the application of AF spectra for tissue characterization and diagnostic potential of optically cleared unstained percutaneous biopsies, contributing to the clinical translation of LSFM.

Medical imaging in cancer cachexia.

Cancer cachexia, often referred to as "wasting syndrome," is characterized by fatigue, weakness, and involuntary weight loss. This syndrome is concomitant with progressive skeletal muscle atrophy with or without adipose tissue loss and is frequently accompanied by systemic inflammation. Understanding the complexities of cancer cachexia is crucial for early detection and intervention, and it is also paramount for enhancing patient outcomes. Medical imaging, comprising diverse imaging modalities, plays a pivotal role in this context, facilitating the diagnosis and surveillance assessment of both the disease extent and the body composition changes that offer valuable information and insights into disease progression. This article provides a comprehensive discourse of the pathophysiological mechanisms and clinical manifestations of cancer cachexia as well as the role of medical imaging in this setting. Particular emphasis is placed on contemporary multidisciplinary and translational research efforts for the development of diagnostic and treatment tools, aiming to mitigate the devastating consequences of cancer cachexia.

Self-conducted sonographic monitoring of the knee in patients with haemophilia-A feasibility study.

INTRODUCTION/AIM: To evaluate whether patients with haemophilia (PwH) can be enabled to perform ultrasonography (US) of their knees without supervision according to the Haemophilia Early Arthropathy Detection with Ultrasound (HEAD-US) protocol and whether they would be able to recognize pathologies. METHODS: Five PwH (mean age 29.6 years, range 20-48 years) were taught the use of a portable US device and the HEAD-US protocol. Subsequently, the patients performed US unsupervised at home three times a week for a total of 6 weeks with a reteaching after 2 weeks. All images were checked for mapping of the landmarks defined in the HEAD-US protocol by a radiologist. In a final test after the completion of the self-sonography period, participants were asked to identify scanning plane and potential pathology from US images of other PwH. RESULTS: On the images of the self-performed scans, 82.7% of the possible anatomic landmarks could be identified and 67.5% of the requested images were unobjectionable, depicting 100% of the required landmarks. There was a highly significant improvement in image quality following reteaching after 2 weeks (74.80 ± 36.88% vs. 88.31 ± 19.87%, p < .001). In the final test, the participants identified the right scanning plane in 85.0% and they correctly identified pathology in 90.0% of images. CONCLUSION: Appropriately trained PwH can perform the HEAD-US protocol of their knee with high quality and are capable to identify pathologic findings on these standardized images. Asynchronous tele-sonography could enable early therapy adjustment and thereby possibly reduce costs.

Parametric mapping using cardiovascular magnetic resonance for the differentiation of light chain amyloidosis and transthyretin-related amyloidosis.

AIMS: To evaluate different cardiovascular magnetic resonance (CMR) parameters for the differentiation of light chain amyloidosis (AL) and transthyretin-related amyloidosis (ATTR). METHODS AND RESULTS: In total, 75 patients, 53 with cardiac amyloidosis {20 patients with AL [66 ± 12 years, 14 males (70%)] and 33 patients with ATTR [78 ± 5 years, 28 males (88%)]} were retrospectively analysed regarding CMR parameters such as T1 and T2 mapping, extracellular volume (ECV), late gadolinium enhancement (LGE) distribution patterns, and myocardial strain, and compared to a control cohort with other causes of left ventricular hypertrophy {LVH; 22 patients [53 ± 16 years, 17 males (85%)]}. One-way ANOVA and receiver operating characteristic analysis were used for statistical analysis. ECV was the single best parameter to differentiate between cardiac amyloidosis and controls [area under the curve (AUC): 0.97, 95% confidence intervals (CI): 0.89-0.99, P < 0.0001, cut-off: >30%]. T2 mapping was the best single parameter to differentiate between AL and ATTR amyloidosis (AL: 63 ± 4 ms, ATTR: 58 ± 2 ms, P < 0.001, AUC: 0.86, 95% CI: 0.74-0.94, cut-off: >61 ms). Subendocardial LGE was predominantly observed in AL patients (10/20 [50%] vs. 5/33 [15%]; P = 0.002). Transmural LGE was predominantly observed in ATTR patients (23/33 [70%] vs. 2/20 [10%]; P < 0.001). The diagnostic performance of T2 mapping to differentiate between AL and ATTR amyloidosis was further increased with the inclusion of LGE patterns [AUC: 0.96, 95% CI: (0.86-0.99); P = 0.05]. CONCLUSION: ECV differentiates cardiac amyloidosis from other causes of LVH. T2 mapping combined with LGE differentiates AL from ATTR amyloidosis with high accuracy on a patient level.

Inverted U-shape-like functional connectivity alterations in cognitive resting-state networks depending on exercise intensity: An fMRI study.

Acute physical activity influences cognitive performance. However, the relationship between exercise intensity, neural network activity, and cognitive performance remains poorly understood. This study examined the effects of different exercise intensities on resting-state functional connectivity (rsFC) and cognitive performance. Twenty male athletes (27.3 ± 3.6 years) underwent cycling exercises of different intensities (high, low, rest/control) on different days in randomized order. Before and after, subjects performed resting-state functional magnetic resonance imaging and a behavioral Attention Network Test (ANT). Independent component analysis and Linear mixed effects models examined rsFC changes within ten resting-state networks. No significant changes were identified in ANT performance. Resting-state analyses revealed a significant interaction in the Left Frontoparietal Network, driven by a non-significant rsFC increase after low-intensity and a significant rsFC decrease after high-intensity exercise, suggestive of an inverted U-shape relationship between exercise intensity and rsFC. Similar but trend-level rsFC interactions were observed in the Dorsal Attention Network (DAN) and the Cerebellar Basal Ganglia Network. Explorative correlation analysis revealed a significant positive association between rsFC increases in the right superior parietal lobule (part of DAN) and better ANT orienting in the low-intensity condition. Results indicate exercise intensity-dependent subacute rsFC changes in cognition-related networks, but their cognitive-behavioral relevance needs further investigation.

Post-radiotherapy stage III/IV non-small cell lung cancer radiomics research: a systematic review and comparison of CLEAR and RQS frameworks.

BACKGROUND: Lung cancer, the second most common cancer, presents persistently dismal prognoses. Radiomics, a promising field, aims to provide novel imaging biomarkers to improve outcomes. However, clinical translation faces reproducibility challenges, despite efforts to address them with quality scoring tools. OBJECTIVE: This study had two objectives: 1) identify radiomics biomarkers in post-radiotherapy stage III/IV nonsmall cell lung cancer (NSCLC) patients, 2) evaluate research quality using the CLEAR (CheckList_for_EvaluAtion_of_Radiomics_research), RQS (Radiomics_Quality_Score) frameworks, and formulate an amalgamated CLEAR-RQS tool to enhance scientific rigor. MATERIALS AND METHODS: A systematic literature review (Jun-Aug 2023, MEDLINE/PubMed/SCOPUS) was conducted concerning stage III/IV NSCLC, radiotherapy, and radiomic features (RF). Extracted data included study design particulars, such as sample size, radiotherapy/CT technique, selected RFs, and endpoints. CLEAR and RQS were merged into a CLEAR-RQS checklist. Three readers appraised articles utilizing CLEAR, RQS, and CLEAR-RQS metrics. RESULTS: Out of 871 articles, 11 met the inclusion/exclusion criteria. The Median cohort size was 91 (range: 10-337) with 9 studies being single-center. No common RF were identified. The merged CLEAR-RQS checklist comprised 61 items. Most unreported items were within CLEAR's "methods" and "open-source," and within RQS's "phantom-calibration," "registry-enrolled prospective-trial-design," and "cost-effective-analysis" sections. No study scored above 50% on RQS. Median CLEAR scores were 55.74% (32.33/58 points), and for RQS, 17.59% (6.3/36 points). CLEAR-RQS article ranking fell between CLEAR and RQS and aligned with CLEAR. CONCLUSION: Radiomics research in post-radiotherapy stage III/IV NSCLC exhibits variability and frequently low-quality reporting. The formulated CLEAR-RQS checklist may facilitate education and holds promise for enhancing radiomics research quality. CLINICAL RELEVANCE STATEMENT: Current radiomics research in the field of stage III/IV postradiotherapy NSCLC is heterogenous, lacking reproducibility, with no identified imaging biomarker. Radiomics research quality assessment tools may enhance scientific rigor and thereby facilitate radiomics translation into clinical practice. KEY POINTS: There is heterogenous and low radiomics research quality in postradiotherapy stage III/IV nonsmall cell lung cancer. Barriers to reproducibility are small cohort size, nonvalidated studies, missing technical parameters, and lack of data, code, and model sharing. CLEAR (CheckList_for_EvaluAtion_of_Radiomics_research), RQS (Radiomics_Quality_Score), and the amalgamated CLEAR-RQS tool are useful frameworks for assessing radiomics research quality and may provide a valuable resource for educational purposes in the field of radiomics.