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Using age- and height-adjusted total kidney volume, the Mayo Clinic Imaging Classification provides a validated approach to assess the risk of chronic kidney disease (CKD) progression in autosomal dominant polycystic kidney disease (ADPKD), but requires excluding patients with atypical imaging patterns, whose clinical characteristics have been poorly defined. We report an analysis of the prevalence, clinical and genetic characteristics of patients with atypical polycystic kidney disease by imaging. Patients from the extended Toronto Genetic Epidemiology Study of Polycystic Kidney Disease recruited between 2016 and 2018 completed a standardized clinical questionnaire, kidney function assessment, genetic testing, and kidney imaging by magnetic resonance or computed tomography. We compared the prevalence, clinical features, genetics, and renal prognosis of atypical versus typical polycystic kidney disease by imaging. Forty-six of the 523 (8.8%) patients displayed atypical polycystic kidney disease by imaging; they were older (55 vs. 43 years; P < 0.001), and less likely to have a family history of ADPKD (26.1% vs. 74.6%; P < 0.001), a detectable PKD1 or PKD2 mutation (9.2% vs. 80.4%; P < 0.001), or progression to CKD stage 3 or stage 5 (P < 0.001). Patients with atypical polycystic kidney disease by imaging represent a distinct prognostic group with a low likelihood of progression to CKD. [ABSTRACT FROM AUTHOR]

Keywords: Empagliflozin; SGLT2 inhibitors; Diabetes; LV diastolic function EN Empagliflozin SGLT2 inhibitors Diabetes LV diastolic function 575 578 4 03/15/22 20220401 NES 220401 Introduction Sodium-glucose co-transporter 2 inhibitors (SGLT2i) have demonstrated promising results in reducing cardiovascular mortality and hospitalization due to heart failure (HF) in patients with type 2 diabetes mellitus (T2DM) and heart failure and reduced ejection fraction (HFrEF) [[1]]. Therefore, we sought to investigate the effect of the SGLT2i empagliflozin on LV diastolic function in patients with T2DM and coronary artery disease (CAD) using cardiac magnetic resonance imaging (CMR). Furthermore, all the patients in our trial had T2DM and CAD, whereas 35% of patients in EMPEROR Preserved trial had an ischemic cause of HF [[2], [5]]. [Extracted from the article]

Acromegaly secondary to extra-pituitary tumors secreting growth hormone releasing hormone (GHRH) is rarely encountered. We review the literature on ectopic acromegaly and present the index report of ectopic acromegaly secondary to GHRH secretion from a mediastinal paraganglioma. Clinical and pathological manifestations and therapeutic management of 99 patients with ectopic acromegaly are reviewed. Acromegaly secondary to ectopic GHRH secretion is usually caused by a neuroendocrine tumor in the lung and pancreas. We report an additional cause of ectopic acromegaly from a mediastinal paraganglioma. Diagnostic criteria of ectopic GHRH syndrome include biochemical and pathologic tumoral confirmation of GHRH secretion and expression. Management of ectopic acromegaly consists of surgical resection of the primary tumor and biochemical normalization, with possible adjuvant use of somatostatin analogs. The review demonstrates that there are several tumor types, including paragangliomas which may secrete GHRH, leading to acromegaly. Clinical and laboratory manifestations of the syndrome and challenges in diagnosis and management of these rarely encountered patients require early diagnosis and appropriate treatment to prevent long-term morbidity and mortality with ectopic acromegaly. [ABSTRACT FROM AUTHOR]

Our objective was to compare the diagnostic performance and diagnostic confidence of convolutional neural networks (CNN) to radiologists in characterizing small hypoattenuating hepatic nodules (SHHN) in colorectal carcinoma (CRC) on CT scans. Retrospective review of CRC CT scans over 6-years yielded 199 patients (550 SHHN) defined as < 1 cm in diameter. The reference standard was established through 1-year stability/MRI for benign or nodule evolution for malignant nodules. Five CNNs underwent supervised training on 150 patients (412 SHHN). The remaining 49 patients (138 SHHN) were used as testing-set to compare performance of 3 radiologists to CNN, measured through ROC AUC analysis of confidence rating assigned to each nodule by the radiologists. Multivariable modeling was used to compensate for radiologist bias from visible findings other than SHHN. In characterizing SHHN as benign or malignant, the radiologists' mean AUC ROC (0.96) was significantly higher than CNN (0.84, p = 0.0004) but equivalent to CNN adjusted through multivariable modeling for presence of synchronous ≥ 1 cm liver metastases (0.95, p = 0.9). The diagnostic confidence of radiologists and CNN were analyzed. There were significantly lower number of nodules rated with low confidence by CNN (19.6%) and CNN with liver metastatic status (18.1%) than two (38.4%, 44.2%, p < 0.0001) but not a third radiologist (11.1%, p = 0.09). We conclude that in CRC, CNN in combination with liver metastatic status equaled expert radiologists in characterizing SHHN but with better diagnostic confidence. [ABSTRACT FROM AUTHOR]

Total kidney volume (TKV) is a validated prognostic biomarker for risk assessment in autosomal dominant polycystic kidney disease (ADPKD). TKV by manual segmentation (MS) is the "gold standard" but is time-consuming and requires expertise. The purpose of this study was to compare TKV-based prognostic performance by ellipsoid (EL) vs. MS in a large cohort of patients. Cross-sectional study of 308 patients seen at a tertiary referral center; all had a standardized MRI with typical imaging of ADPKD. An experienced radiologist blinded to patient clinical results performed all TKV measurements by EL and MS. We assessed the agreement of TKV measurements by intraclass correlation(ICC) and Bland-Altman plot and also how the disagreement of the two methods impact the prognostic performance of the Mayo Clinic Imaging Classification (MCIC). We found a high ICC of TKV measurements (0.991, p < 0.001) between EL vs. MS; however, 5.5% of the cases displayed disagreement of TKV measurements >20%. We also found a high degree of agreement of the individual MCIC risk classes (i.e. 1A to 1E) with a Cohen's weighted-kappa of 0.89; but 42 cases (13.6%) were misclassified by EL with no misclassification spanning more than one risk class. The sensitivity and specificity of EL in distinguishing low-risk (1A-B) from high-risk (1C-E) MCIC prognostic grouping were 96.6% and 96.1%, respectively. Overall, we found an excellent agreement of TKV-based risk assessment between EL and MS. However, caution is warranted for patients with MCIC 1B and 1C, as misclassification can have therapeutic consequence. [ABSTRACT FROM AUTHOR]