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.

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.

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.

Non-destructive, whole-plant phenotyping reveals dynamic changes in water use efficiency, photosynthesis, and rhizosphere acidification of sorghum accessions under osmotic stress.

Noninvasive phenotyping can quantify dynamic plant growth processes at higher temporal resolution than destructive phenotyping and can reveal phenomena that would be missed by end-point analysis alone. Additionally, whole-plant phenotyping can identify growth conditions that are optimal for both above- and below-ground tissues. However, noninvasive, whole-plant phenotyping approaches available today are generally expensive, complex, and non-modular.

Evaluating Plant Drought Resistance with a Raspberry Pi and Time-lapse Photography.

Identifying genetic variations or treatments that confer greater resistance to drought is paramount to ensuring sustainable crop productivity. Accurate and reproducible measurement of drought stress symptoms can be achieved via automated, image-based phenotyping. Many phenotyping platforms are either cost-prohibitive, require specific technical expertise, or are simply more complex than necessary to effectively evaluate drought resistance.