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Abstract Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ( $$n = 36$$ n = 36 ) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was $$2.1\% \pm 2\%$$ 2.1 % ± 2 % compared to $$1.1\% \pm 1\%$$ 1.1 % ± 1 % ( $$p = 0.002$$ p = 0.002 ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or $$1.4\% \pm 1\%$$ 1.4 % ± 1 % ( $$p = 0.01$$ p = 0.01 ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( $$p = 0.05$$ p = 0.05 ) and PKD2 mutation ( $$p = 0.04$$ p = 0.04 ) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate.

Total kidney volume measured on MRI is an important biomarker for assessing the progression of autosomal dominant polycystic kidney disease and response to treatment. However, we have noticed that there can be substantial differences in the kidney volume measurements obtained from the various pulse sequences commonly included in an MRI exam. Here we examine kidney volume measurement variability among five commonly acquired MRI pulse sequences in abdominal MRI exams in 105 patients with ADPKD. Right and left kidney volumes were independently measured by three expert observers using model-assisted segmentation for axial T2, coronal T2, axial single-shot fast spin echo (SSFP), coronal SSFP, and axial 3D T1 images obtained on a single MRI from ADPKD patients. Outlier measurements were analyzed for data acquisition errors. Most of the outlier values (88%) were due to breathing during scanning causing slice misregistration with gaps or duplication of imaging slices (n = 35), slice misregistration from using multiple breath holds during acquisition (n = 25), composing of two overlapping acquisitions (n = 17), or kidneys not entirely within the field of view (n = 4). After excluding outlier measurements, the coefficient of variation among the five measurements decreased from 4.6% pre to 3.2%. Compared to the average of all sequences without errors, TKV measured on axial and coronal T2 weighted imaging were 1.2% and 1.8% greater, axial SSFP was 0.4% greater, coronal SSFP was 1.7% lower and axial T1 was 1.5% lower than the mean, indicating intrinsic measurement biases related to the different MRI contrast mechanisms. In conclusion, MRI data acquisition errors are common but can be identified using outlier analysis and excluded to improve organ volume measurement consistency. Bias toward larger volume measurements on T2 sequences and smaller volumes on axial T1 sequences can also be mitigated by averaging data from all error-free sequences acquired.

Abdominal imaging of autosomal dominant polycystic kidney disease (ADPKD) has historically focused on detecting complications such as cyst rupture, cyst infection, obstructing renal calculi, and pyelonephritis; discriminating complex cysts from renal cell carcinoma; and identifying sources of abdominal pain. Many imaging features of ADPKD are incompletely evaluated or not deemed to be clinically significant, and because of this, treatment options are limited. However, total kidney volume (TKV) measurement has become important for assessing the risk of disease progression (i.e., Mayo Imaging Classification) and predicting tolvaptan treatment’s efficacy. Deep learning for segmenting the kidneys has improved these measurements’ speed, accuracy, and reproducibility. Deep learning models can also segment other organs and tissues, extracting additional biomarkers to characterize the extent to which extrarenal manifestations complicate ADPKD. In this concept paper, we demonstrate how deep learning may be applied to measure the TKV and how it can be extended to measure additional features of this disease.

Background: Percutaneous cholecystostomy (PC) can be used as bridging or definitive therapy in some cases of acute cholecystitis. We aimed to compare hospital stay and survival of patients that underwent PC insertion because of acute calculus cholecystitis (ACC) compared to those who did not. Methods: This is a retrospective study in which patients with gangrenous cholecystitis and perforation were excluded. Regression models were used to evaluate the influence of PC on mortality and hospital stay. Results: Six hundred and eighty-three patients were admitted because of ACC, and 50 patients were referred to PC. Indication for PC insertion were high disease severity index (DSI, 8 pts) and failure of conservative treatment with total disease duration >7 days (42 pts). Those who underwent PC were older (76.0 ± 12.4 vs. 60.8 ± 19.2, P < 0.001); PC was associated with longer hospital stay (12.8 vs. 6.5 days) and higher one-year mortality (20% vs. 4.9%, P < 0.001). Among patients with non-severe disease severity index (DSI), PC was associated with longer length of hospital stay and higher one-year mortality compared to patients treated conservatively (9.9 ± 0.6 vs. 6.0 ± 0.2 days, and 16.7% vs. 4.0%, respectively, P < 0.001 for both). For patients with severe DSI, PC was associated with similar length of hospital stay and one-year mortality compared to similar patients treated conservatively (16.1 ± 8.1 vs. 18.4 ± 4.0 days, and 37.5% vs. 22.6%, respectively, P = 0.802 and P = 0.389, respectively). Conclusions: In patients with mild–moderate DSI unresponsive to conservative treatment, PC may be associated with deteriorated prognosis compared to conservative treatment. The decision to insert PC in patients unresponsive to conservative therapy even with disease duration >7 days must be re-evaluated.

Organ volume measurements are a key metric for managing ADPKD (the most common inherited renal disease). However, measuring organ volumes is tedious and involves manually contouring organ outlines on multiple cross-sectional MRI or CT images. The automation of kidney contouring using deep learning has been proposed, as it has small errors compared to manual contouring. Here, a deployed open-source deep learning ADPKD kidney segmentation pipeline is extended to also measure liver and spleen volumes, which are also important. This 2D U-net deep learning approach was developed with radiologist labeled T2-weighted images from 215 ADPKD subjects (70% training = 151, 30% validation = 64). Additional ADPKD subjects were utilized for prospective (n = 30) and external (n = 30) validations for a total of 275 subjects. Image cropping previously optimized for kidneys was included in training but removed for the validation and inference to accommodate the liver which is closer to the image border. An effective algorithm was developed to adjudicate overlap voxels that are labeled as more than one organ. Left kidney, right kidney, liver and spleen labels had average errors of 3%, 7%, 3%, and 1%, respectively, on external validation and 5%, 6%, 5%, and 1% on prospective validation. Dice scores also showed that the deep learning model was close to the radiologist contouring, measuring 0.98, 0.96, 0.97 and 0.96 on external validation and 0.96, 0.96, 0.96 and 0.95 on prospective validation for left kidney, right kidney, liver and spleen, respectively. The time required for manual correction of deep learning segmentation errors was only 19:17 min compared to 33:04 min for manual segmentations, a 42% time saving (p = 0.004). Standard deviation of model assisted segmentations was reduced to 7, 5, 11, 5 mL for right kidney, left kidney, liver and spleen respectively from 14, 10, 55 and 14 mL for manual segmentations. Thus, deep learning reduces the radiologist time required to perform multiorgan segmentations in ADPKD and reduces measurement variability.

Objective: Percutaneous nephrolithotomy (PCNL) is a well-described technique with high success rates and has become the gold standard procedure for the removal of large renal stones. Despite widespread use of the procedure, difficult situations may be encountered that challenge even the most experienced endourologists. Herein, we present educational videos that provide tips for overcoming specific challenging situations that may be encountered during PCNL.

Objectives To investigate the possible associations of muscle and visceral fat mass with the prognosis of patients hospitalized with acute pancreatitis. Methods Body composition analysis (Sliceomatic, TomoVision, Montreal, Canada) was performed on CT images at the L3 level in patients admitted with acute pancreatitis during 2008-2014. Regression analysis was used to examine associations of body composition with 1-year mortality and 1-year readmission rates. Results A total of 158 patients were included (mean age 63.7 [plus or minus] 17.4 years, 91 (57.6%) were male). Fat was the most abundant tissue (408 [plus or minus] 180 cm.sup.2 surface area). None of the prognostic factors examined were associated with 1-year mortality. Values below compared to above the medians for muscle mass and visceral fat were associated with higher mean 1-year readmissions: 1.7 versus 1.0, p = 0.02 and 1.6 versus 1.1, p = 0.09, respectively. Logistic regression analysis showed an association of high visceral fat with reduced 1-year readmission (OR 0.995, 95% CI 0.991-1.000, p = 0.03). Linear regression analysis showed an inverse correlation of visceral fat mass with the number of 1-year readmissions (HR -0.004, 95% CI -0.008-000, p = 0.070). Conclusions Higher amounts of visceral fat and muscle mass were positively associated with lower recurrent hospitalizations in patients admitted with acute pancreatitis. These results support the importance of nutritional rehabilitation in patients after admission due to acute pancreatitis., Author(s): Mordechai Shimonov [sup.1] [sup.2] , Zhana Abtomonova [sup.1] , Asnat Groutz [sup.2] [sup.3] , Hadar Amir [sup.2] [sup.3] , Israel Khanimov [sup.2] , Eyal Leibovitz [sup.4] Author Affiliations: (1) [...]

Introduction: Percutaneous nephrolithotomy (PCNL) remains the gold standard treatment for patients with complete staghorn stones, for which multiple access tracts may be required. In this study, we describe a series of patients undergoing PCNL with a minimum of five dilated access tracts. Materials and Methods: We performed a multi-institutional retrospective review of 10 patients with complete staghorn stones who underwent PCNL requiring five or more access tracts. We recorded patient demographics, stone characteristics postoperative complications, and stone-free rates (SFRs). The primary endpoint was any postoperative complication. Secondary endpoints included SFR, operative time, and length of stay. SFR was defined as absence of stones or residual fragments <4 mm. Results: A total of 10 patients from two institutions were included. Access tract number ranged from 5 to 11, and median stone volume was 233,042 mm3. Seven patients (70%) experienced postoperative complications, ranging from Clavien II to IVa. Three patients (30%) required blood transfusions. Median operative time was 312 minutes ranging from 180 to 560 minutes. Five patients (50%) were stone-free after the initial procedure. Of those with residual fragments, 4 (40%) required reoperation to be rendered stone-free. Median length of stay was 2.5 days, with a range of 1–6 days. Conclusion: To our knowledge, this is the largest series of patients undergoing PCNL with five or more access tracts reported to date. This study confirms that PCNL with five or more tracts is feasible and relatively safe, albeit with a high rate of complications in the immediate postoperative period. [ABSTRACT FROM AUTHOR]

This article describes a study examining the association between treatment with ACE inhibitors or angiotensin receptor blockers (ARBs) and incident hypoglycemia in patients with or without diabetes who were admitted to the internal medicine departments of a tertiary hospital in the Tel Aviv district of Israel. The authors found that treatment with ARBs, but not ACE inhibitors, compared with treatment with neither, was associated with a reduced risk of hypoglycemia regardless of diabetes status. [ABSTRACT FROM AUTHOR]

Background: Percutaneous cholecystostomy (PC) can be used as bridging or definitive therapy in some cases of acute cholecystitis. We aimed to compare hospital stay and survival of patients that underwent PC insertion because of acute calculus cholecystitis (ACC) compared to those who did not. Methods: This is a retrospective study in which patients with gangrenous cholecystitis and perforation were excluded. Regression models were used to evaluate the influence of PC on mortality and hospital stay. Results: Six hundred and eighty-three patients were admitted because of ACC, and 50 patients were referred to PC. Indication for PC insertion were high disease severity index (DSI, 8 pts) and failure of conservative treatment with total disease duration >7 days (42 pts). Those who underwent PC were older (76.0 ± 12.4 vs. 60.8 ± 19.2, P < 0.001); PC was associated with longer hospital stay (12.8 vs. 6.5 days) and higher one-year mortality (20% vs. 4.9%, P < 0.001). Among patients with non-severe disease severity index (DSI), PC was associated with longer length of hospital stay and higher one-year mortality compared to patients treated conservatively (9.9 ± 0.6 vs. 6.0 ± 0.2 days, and 16.7% vs. 4.0%, respectively, P < 0.001 for both). For patients with severe DSI, PC was associated with similar length of hospital stay and one-year mortality compared to similar patients treated conservatively (16.1 ± 8.1 vs. 18.4 ± 4.0 days, and 37.5% vs. 22.6%, respectively, P = 0.802 and P = 0.389, respectively). Conclusions: In patients with mild–moderate DSI unresponsive to conservative treatment, PC may be associated with deteriorated prognosis compared to conservative treatment. The decision to insert PC in patients unresponsive to conservative therapy even with disease duration >7 days must be re-evaluated. [ABSTRACT FROM AUTHOR]

Background: Total kidney volume (TKV) is an important biomarker for assessing kidney function, especially for autosomal dominant polycystic kidney disease (ADPKD). However, TKV measurements from a single MRI pulse sequence have limited reproducibility, ± ~5%, similar to ADPKD annual kidney growth rates. Purpose: To improve TKV measurement reproducibility on MRI by extending artificial intelligence algorithms to automatically segment kidneys on T1‐weighted, T2‐weighted, and steady state free precession (SSFP) sequences in axial and coronal planes and averaging measurements. Study Type: Retrospective training, prospective testing. Subjects: Three hundred ninety‐seven patients (356 with ADPKD, 41 without), 75% for training and 25% for validation, 40 ADPKD patients for testing and 17 ADPKD patients for assessing reproducibility. Field Strength/Sequence: T2‐weighted single‐shot fast spin echo (T2), SSFP, and T1‐weighted 3D spoiled gradient echo (T1) at 1.5 and 3T. Assessment: 2D U‐net segmentation algorithm was trained on images from all sequences. Five observers independently measured each kidney volume manually on axial T2 and using model‐assisted segmentations on all sequences and image plane orientations for two MRI exams in two sessions separated by 1–3 weeks to assess reproducibility. Manual and model‐assisted segmentation times were recorded. Statistical Tests: Bland–Altman, Schapiro–Wilk (normality assessment), Pearson's chi‐squared (categorical variables); Dice similarity coefficient, interclass correlation coefficient, and concordance correlation coefficient for analyzing TKV reproducibility. P‐value < 0.05 was considered statistically significant. Results: In 17 ADPKD subjects, model‐assisted segmentations of axial T2 images were significantly faster than manual segmentations (2:49 minute vs. 11:34 minute), with no significant absolute percent difference in TKV (5.9% vs. 5.3%, P = 0.88) between scans 1 and 2. Absolute percent differences between the two scans for model‐assisted segmentations on other sequences were 5.5% (axial T1), 4.5% (axial SSFP), 4.1% (coronal SSFP), and 3.2% (coronal T2). Averaging measurements from all five model‐assisted segmentations significantly reduced absolute percent difference to 2.5%, further improving to 2.1% after excluding an outlier. Data Conclusion: Measuring TKV on multiple MRI pulse sequences in coronal and axial planes is practical with deep learning model‐assisted segmentations and can improve TKV measurement reproducibility more than 2‐fold in ADPKD. Evidence Level: 2 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Abstract Background Patient preferences regarding the gender of their physicians is a highly sensitive issue, which can be particularly salient in intimate medical situations. Previously published studies found that women tend to prefer female physicians, especially in the case of obstetricians and gynecologists. Data regarding other intimate specialties, such as breast surgery, are scarce. The present study was undertaken to assess gender preferences of women regarding their choice of a breast surgeon. Methods Five hundred and fifteen consecutive women who attended breast clinics in two university-affiliated tertiary hospitals were prospectively enrolled. A 25-item anonymous questionnaire was completed by women independently and used to assess their preferences in selecting their breast surgeon. Of the 515 women, 500 (97 % response rate; mean age 50.6 ± 15.4 years) completed the anonymous questionnaire. Results Overall, 160 (32 %) women preferred to undergo breast examination by a female breast surgeon, 296 (59 %) had no preference, and only 44 (9 %) preferred a male surgeon. A same-gender preference was significantly and independently associated with younger age of the patients (Odds Ratio = 0.978, 95 % Confidence Interval 0.962–0.994, P = 0.007) and being married (Odds Ratio = 0.563, 95 % Confidence Interval 0.347–0.916, P = 0.021). However, only small and equal numbers of patients preferred to undergo breast surgery by a female (14 %) or a male (13 %) surgeon, and most patients (73 %) had no gender preferences. Furthermore, the three most important factors, which affected in general the actual selection, were surgical ability (93 %), experience (91.2 %) and knowledge (78.6 %), rather than physician gender per se. Conclusions Overall, about a third of women prefer a female breast surgeon for their breast examination. Embarrassment during the examination was the major reason for same-gender preference. In contrast, when it comes to breast operations, preference for a female surgeon is less pronounced, with the professional skills of the surgeons becoming the predominant consideration. The fact that almost a third of the potential patients prefer female surgeons with regard to their breast examinations emphasizes the need to increase the number of female surgeons. Such an increase can be achieved through academic and economic changes that will enable more women to specialize in general surgery. Trial registration Trial registration is not required for this type of research.