INTRODUCTION:This study aimed to determine the positive predictive value (PPV) of magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) machine fusion prostate biopsies, and to identify factors associated with a positive biopsy. METHODS:With ethics approval, we retrospectively evaluated all MRI-TRUS machine fusion prostate biopsies at our institution from September 2022 to April 2025. True positive clinically significant prostate cancers (csPCa) were defined as Gleason ≥7. PPVs were calculated overall and for PI-RADS 3, 4 and 5 categories. A generalized linear mixed model (GLMM) was created evaluating the following factors as fixed effects: PI-RADS category; prostate-specific antigen (PSA) density (<0.10, 0.10-0.15, ≥0.15 ng/mL2); lesion size (<7, 7-15, ≥15 mm); lesion location (peripheral vs transition zone); ultrasound correlate (present/absent); prostate size (<60 vs ≥60 mL); interval from MRI to biopsy (<6 months or not); and biopsy operator (2 radiologists). Referring urologist (n = 19) and reporting radiologist (n = 8) were included as random effects. RESULTS:372 patients (mean age, 67 ± 7 years) with 529 lesions underwent biopsy. The overall PPV was 314/529 (59.4%). For PI-RADS 3 to 5, PPVs were 32/72 (44.4%), 123/243 (50.6%), and 159/214 (74.3%), respectively. In GLMM analysis, PI-RADS 5 versus 3 (OR 3.6, 95% CI, 1.7-7.4), PSA density ≥0.15 ng/mL2 (OR 2.2, 95% CI, 1.2-3.8), and presence of an ultrasound correlate (OR 2.7, 95% CI, 1.7-4.2) were associated with true positive biopsies. Small lesion size <7 mm was associated with a false positive biopsy (OR 0.4, 95% CI, 0.2-0.8). CONCLUSION:The yield of fusion prostate biopsies at our institution is high. PI-RADS 5, PSA density ≥0.15 ng/mL2, and an ultrasound correlate at biopsy were associated with csPCa, whereas sub-7 mm lesions were negatively associated with csPCa.

Objective Mammographic breast cancer detection depends on high-quality positioning, which is traditionally assessed and monitored subjectively. This study used artificial intelligence (AI) to evaluate mammography positioning on digital screening mammograms to identify and quantify unmet mammography positioning quality (MPQ). Methods Data were collected within an IRB-approved collaboration. In total, 126 367 digital mammography studies (553 339 images) were processed. Unmet MPQ criteria, including exaggeration, portion cutoff, posterior tissue missing, nipple not in profile, too high on image receptor, inadequate pectoralis length, sagging, and posterior nipple line (PNL) length difference, were evaluated using MPQ AI algorithms. The similarity of unmet MPQ occurrence and rank order was compared for each health system. Results Altogether, 163 759 and 219 785 unmet MPQ criteria were identified, respectively, at the health systems. The rank order and the probability distribution of the unmet MPQ criteria were not statistically significantly different between health systems (P = .844 and P = .92, respectively). The 3 most-common unmet MPQ criteria were: short PNL length on the craniocaudal (CC) view, inadequate pectoralis muscle, and excessive exaggeration on the CC view. The percentages of unmet positioning criteria out of the total potential unmet positioning criteria at health system 1 and health system 2 were 8.4% (163 759/1 949 922) and 7.3% (219 785/3 030 129), respectively. Conclusion Artificial intelligence identified a similar distribution of unmet MPQ criteria in 2 health systems’ daily work. Knowledge of current commonly unmet MPQ criteria can facilitate the improvement of mammography quality through tailored education strategies.

The goal of this study was to determine how radiologists’ rating of image quality when using 0.5T Magnetic Resonance Imaging (MRI) compares to Computed Tomography (CT) for visualization of pathology and evaluation of specific anatomic regions within the paranasal sinuses. 42 patients with clinical CT scans opted to have a 0.5T MRI scan for this study. Scans were completed from June 2021 to June 2022 with an average of 65.2 days from CT to MRI. A neuroradiologist and neuroradiology fellow evaluated the images to answer several questions and provide a confidence score for each based on image quality. Responses between the CT and MRI scans were compared for intramodality and intermodality agreement. The Likert scores demonstrate that MRI performed well in assessing mucosal thickening. Performance was not adequate for anatomical questions for presurgical planning. 0.5T MRI is able to produce high quality imaging of the sinuses. This could be used as a radiation free test to correlate mucosal thickening with patient’s symptoms. However, a CT would be needed to screen for ostiomeatal obstruction and anatomical visualization of critical variants for presurgical planning.

Background18F-FDG-PET/CT is a valuable tool in the staging and surveillance of cutaneous melanoma; however, recent studies prompt debate on the clinical significance of imaging patients below the lesser trochanter. This study explored two research questions. In patients with a known primary cutaneous melanoma within the standard field of view (SFOV, between the orbits and lesser trochanter), what is the prevalence of metastasis to sites solely within the lower extremities? and, In patients with a known primary cutaneous melanoma within the SFOV what demographic and clinical factors are associated with sole metastasis to the lower extremities?MethodsA retrospective, multi-centered, observational study of consecutive case reports was conducted. Subjects included 619 patients who underwent extended field of view (EFOV) 18F-FDG-PET/CT (from vertex to toes) for staging and/or follow-up of cutaneous melanoma. Data was collected at three primary healthcare centers in Canada (Nova Scotia, Alberta, and British Columbia). Inclusion criteria were patients >18 years of age, confirmed primary cutaneous melanoma, and a known location of the primary within the SFOV. Patients with primary cutaneous melanoma lesions in lower extremities and previous other cancers were excluded. To determine the prevalence of lesions located below the lesser trochanter, the proportion of such lesions were computed, and 95% confidence intervals ensured a precise estimation of the proportion.Results2512 patient charts were reviewed with 619 meeting the inclusion criteria, 298 of these were females. Six percent had metastases in both the lower extremities and sites within the SFOV. The number of subjects who had no metastasis within their SFOV was 361 (58.3%). The number of subjects who presented with confirmed metastasis in the lower extremities without concurrent metastasis in the SFOV region was one (0.58%). Despite a large initial study sample, the number of patients with metastasis in the lower extremities was insufficient to allow correlation of factors associated with risk of spread to the lower extremities.ConclusionLower extremity 18F-FDG-PET/CT provided additional, relevant clinical data in a sole patient. This finding supports prior research suggesting the prevalence is rare. Future studies should seek to define demographic and clinical factors that predict such rare occurrences, where follow up would be warranted. This study highlights feasibility challenges associated with such investigation.

Image Quality Metrics (IQMs) have allowed for objective analysis of MR images in order to optimize protocols or reconstruction algorithms, for example. However, the performance of IQMs depends on the diagnostic task. Therefore, the aim of this study was to explore how well leading IQMs correlate with, or predict, neuroradiologists’ diagnostic confidence in acute and chronic stroke diagnostic tasks. We observed that, although the IQMs in question calculated for T2 FLAIR images could be used to predict neuroradiologists’ diagnostic confidence scores for the chronic stroke diagnostic task, they did not correlate with diagnostic confidence scores for acute stroke.

Artificial intelligence (AI) software in radiology is becoming increasingly prevalent and performance is improving rapidly with new applications for given use cases being developed continuously, oftentimes with development and validation occurring in parallel. Several guidelines have provided reporting standards for publications of AI-based research in medicine and radiology. Yet, there is an unmet need for recommendations on the assessment of AI software before adoption and after commercialization. As the radiology AI ecosystem continues to grow and mature, a formalization of system assessment and evaluation is paramount to ensure patient safety, relevance and support to clinical workflows, and optimal allocation of limited AI development and validation resources before broader implementation into clinical practice. To fulfil these needs, we provide a glossary for AI software types, use cases and roles within the clinical workflow; list healthcare needs, key performance indicators and required information about software prior to assessment; and lay out examples of software performance metrics per software category. This conceptual framework is intended to streamline communication with the AI software industry and provide healthcare decision makers and radiologists with tools to assess the potential use of these software. The proposed software evaluation framework lays the foundation for a radiologist-led prospective validation network of radiology AI software. Learning Points: The rapid expansion of AI applications in radiology requires standardization of AI software specification, classification, and evaluation. The Canadian Association of Radiologists' AI Tech & Apps Working Group Proposes an AI Specification document format and supports the implementation of a clinical expert evaluation process for Radiology AI software.

OBJECTIVES:To evaluate the interobserver agreement between radiologists using the Ultrasound Liver Reporting And Data System (US LI-RADS) visualization score and assess association between visualization score and cause of liver disease, sex, and body mass index (BMI).METHODS:This retrospective, single institution, cross-sectional study evaluated 237 consecutive hepatocellular carcinoma surveillance US examinations between March 4, 2017 and September 4, 2017. Five abdominal radiologists independently assigned a US LI-RADS visualization score (A, no or minimal limitations; B, moderate limitations; C, severe limitations). Interobserver agreement was assessed with a weighted Kappa statistic. Association between US visualization score (A vs B or C) and cause of liver disease, sex, and BMI (< or ≥ 25 kg/m2) was evaluated using univariate and multivariate analyses.RESULTS:The average weighted Kappa statistic for all raters was 0.51. A score of either B or C was assigned by the majority of radiologists in 148/237 cases and was significantly associated with cause of liver disease (P = 0.014) and elevated BMI (P < 0.001). Subjects with viral liver disease were 3.32 times (95% CI: 1.44-8.38) more likely to have a score of A than those with non-alcoholic steatohepatitis (P = 0.007). The adjusted odds ratio of visualization score A was 0.249 (95% CI: 0.13-0.48) among those whose BMI was ≥25 kg/m2 vs. BMI < 25 kg/m2.CONCLUSION:Interobserver agreement between radiologists using US LI-RADS score was moderate. The majority of US examinations were scored as having moderate or severe limitations, and this was significantly associated with non-alcoholic steatohepatitis and increased BMI.

OBJECTIVES:To determine the sensitivity of ultrasound (US) in detecting pancreatic ductal adenocarcinoma in our region, to identify factors associated with US test result, and assess the impact on the diagnostic interval and survival.METHODS:Patients diagnosed between January 1, 2014 and December 31, 2015 in Nova Scotia, Canada were identified by a cancer registry. US performed prior to diagnosis were retrospectively graded as true positive (TP), indeterminate or false negative (FN). Amongst US results, differences in age, weight and tumor size were assessed [one-way analysis of variance (ANOVA)]. Associations between result and sex, tumor location (proximal/distal), clinical suspicion of malignancy, and visualization of the pancreas, tumor, secondary signs and liver metastases were assessed (Chi-square). Mean follow-up imaging, diagnostic, and survival intervals were assessed (one-way ANOVA).RESULTS:One hundred thirteen US of 107 patients (54 women; mean 70 ± 13 years) were graded as follows: 48/113 (42.5%) TPs; 42/113 (37.2%) indeterminates; and 23/113 (20.4%) FNs. Sensitivity was 48/71(67.6%). There was no difference in age, weight or tumor size amongst US result (P > 0.5). FNs had proportionally more men (P = 0.011) and lacked clinical suspicion of malignancy (P = 0.0006); TPs had proportionally more proximal tumors (P = 0.017). US result was associated with visualization of the pancreas, tumor, secondary signs and liver metastases (P < 0.005). FNs had longer mean follow-up imaging (P < 0.0001) and diagnostic (P = 0.0007) intervals, and worse mean survival (P = 0.034).CONCLUSIONS:In our region, the sensitivity of US in detecting pancreatic ductal adenocarcinoma is 67.6%. A false negative US is associated with delayed diagnostic work-up and worse mean survival.

Purpose: To identify factors associated with false or indeterminate US result for suspected appendicitis, and assess whether multi-categorical reporting of US yields more precise estimates regarding the probability of appendicitis. Methods: 562 US examinations for suspected appendicitis between May 2013-April 2015 were categorized as true (77/562 true positives or true negatives) or false/indeterminate (485/562 false negatives, false positives or indeterminates) based on results from a prior study. Of 541 examinations with images available retrospectively, a category of A-E was assigned as follows: non-visualized appendix with secondary findings (A) absent or (B) present; appendix visualized and considered (C) negative, (D) equivocal, or (E) positive for appendicitis. The following factors were recorded: age; sex; scan time (daytime vs. off-hours); resident/fellow involvement; abdominal subspecialty radiologist; radiologist experience (>5 years or not); and tenderness on interrogation. Associations between factors and US result were assessed (t-tests, Fisher's exact test and multivariate logistic regression). Results: The true group had proportionally more males (18/77 (23.4%) vs. 66/485 (13.6%), p = 0.04) and patients with sonographic tenderness (43/77 (55.8%) vs. 132/353 (27.3%), p < 0.0001). There was no significant difference or association with other factors. On multivariate logistic regression, false/indeterminate results were 1.9 times (95% CIs 1.0-3.5) more likely among females and 3.8 times more likely in the absence of tenderness (95% CIs 2.3-6.4). The proportion of patients with appendicitis in categories A-E was 34/410 (8.3%), 24/44 (54.5%), 0/18 (0%), 0/3 (0%) and 61/66 (92.4%), respectively. Conclusions: Females and absence of tenderness were associated with a false/indeterminate US. Categorical reporting provides more granular estimates of the post-test probability of appendicitis.

PURPOSE:We performed an exploratory analysis of electroencephalography (EEG) and neuroimaging data from a cohort of 51 patients with first seizure (FS) and new-onset epilepsy (NOE) to identify variables, or combinations of variables, that might discriminate between clinical trajectories over a one-year period and yield potential biomarkers of epileptogenesis. METHODS:Patients underwent EEG, hippocampal and whole brain structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS) within six weeks of the index seizure, and repeat neuroimaging one year later. We classified patients with FS as having had a single seizure (FS-SS) or having converted to epilepsy (FS-CON) after one year and performed logistic regression to identify combinations of variables that might discriminate between FS-SS and FS-CON, and between FS-SS and the combined group FS-CON + NOE. We performed paired t-tests to assess changes in quantitative variables over time. RESULTS:Several combinations of variables derived from hippocampal structural MRI, DTI, and MRS provided excellent discrimination between FS-SS and FS-CON in our sample, with areas under the receiver operating curve (AUROC) ranging from 0.924 to 1. They also provided excellent discrimination between FS-SS and the combined group FS-CON + NOE in our sample, with AUROC ranging from 0.902 to 1. After one year, hippocampal fractional anisotropy (FA) increased bilaterally, hippocampal radial diffusivity (RD) decreased on the side with the larger initial measurement, and whole brain axial diffusivity (AD) increased in patients with FS-SS; hippocampal volume decreased on the side with the larger initial measurement, hippocampal FA increased bilaterally, hippocampal RD decreased bilaterally and whole brain AD, FA and mean diffusivity increased in the combined group FS-CON + NOE (corrected threshold for significance, q = 0.017). CONCLUSION:We propose a prospective, multicenter study to develop and test models for the prediction of seizure recurrence in patients after a first seizure, based on hippocampal neuroimaging. Further longitudinal neuroimaging studies in patients with a first seizure and new-onset epilepsy may provide clues to the microstructural changes occurring at the earliest stages of epilepsy and yield biomarkers of epileptogenesis.

To develop a breast cancer risk model to identify women at mammographic screening who are at higher risk of breast cancer within the general screening population. This retrospective nested case-control study used data from a population-based breast screening program (2009–2015). All women aged 40–75 diagnosed with screen-detected or interval breast cancer (n = 1882) were frequency-matched 3:1 on age and screen-year with women without screen-detected breast cancer (n = 5888). Image-derived risk factors from the screening mammogram (percent mammographic density [PMD], breast volume, age) were combined with core biopsy history, first-degree family history, and other clinical risk factors in risk models. Model performance was assessed using the area under the receiver operating characteristic curve (AUC). Classifiers assigning women to low- versus high-risk deciles were derived from risk models. Agreement between classifiers was assessed using a weighted kappa. The AUC was 0.597 for a risk model including only image-derived risk factors. The successive addition of core biopsy and family history significantly improved performance (AUC = 0.660, p < 0.001 and AUC = 0.664, p = 0.04, respectively). Adding the three remaining risk factors did not further improve performance (AUC = 0.665, p = 0.45). There was almost perfect agreement (kappa = 0.97) between risk assessments based on a classifier derived from image-derived risk factors, core biopsy, and family history compared with those derived from a model including all available risk factors. Women in the general screening population can be risk-stratified at time of screen using a simple model based on age, PMD, breast volume, and biopsy and family history. • A breast cancer risk model based on three image-derived risk factors as well as core biopsy and first-degree family history can provide current risk estimates at time of screen. • Risk estimates generated from a combination of image-derived risk factors, core biopsy history, and first-degree family history may be more valid than risk estimates that rely on extensive self-reported risk factors. • A simple breast cancer risk model can avoid extensive clinical risk factor data collection.

OBJECTIVE. The objective of our study was to determine the accuracy of ultrasound (US) and CT in diagnosing appendicitis at our institution while taking into account the number of indeterminate examinations in accordance with the Standards for Reporting Diagnostic Accuracy (STARD) guidelines. MATERIALS AND METHODS. We retrospectively evaluated 790 patients who underwent US, CT, or both for evaluation of suspected appendicitis between May 1, 2013, and April 30, 2015. Patient characteristics and US and CT examination results were recorded. The reference standard was histopathology or 3 months of medical record follow-up if surgery was not performed; 3 × 2 tables were generated, and sensitivity, specificity, overall test yield, and accuracy were calculated according to STARD guidelines. For surgical cases, time to surgery (one-way ANOVA) was compared among patients who underwent US alone, CT alone, or both US and CT. RESULTS. A total of 473 of 562 US examinations had indeterminate findings (overall test yield, 15.8%); sensitivity and specificity in the 89 diagnostic examinations were 98.5% and 54.2%, respectively. Thirteen of 522 CT examinations were indeterminate (overall test yield, 97.5%); sensitivity and specificity in the remaining 509 CT examinations were 98.9% and 97.2%, respectively. Taking indeterminate studies into account, the accuracy was 13.7% for US and 95.6% for CT. The negative appendectomy rates were 17.7% (11/62) for US and 3.3% (9/276) for CT (p = 0.0002). Time to surgery was longer for patients who underwent US and CT (mean ± SD, 17.7 ± 8.9 hours) than US alone (12.9 ± 6.4 hours; p = 0.002) but was not longer for patients who underwent CT alone (16.3 ± 8.4 hours; p = 0.45). CONCLUSION. At our institution, a large proportion of US examinations are indeterminate for appendicitis. CT is the preferred first-line imaging test for evaluating appendicitis in nonobstetric adult patients.

e12556 Background: Little is known about the association between mammographic breast density and the subtypes of breast cancer including HER2-positive breast cancers (HER2-BrCa). The objective of this study was to assess the strength of association between breast density and HER2-BrCa in a population-based screening program. Methods: This is a population-based case-control breast cancer study of women aged 40 to 75 who underwent digital breast screening from 2009 to 2015 in Nova Scotia, Canada. Cases included women diagnosed with HER2-BrCa at screen or before their next screen (interval); controls included women without screen-detected cancer matched to cases by age and year of screen. Measures of mammographic breast density (percent density, BI-RADS-4th and -5th edition) were obtained from automated software (densitasai) and linked with clinical risk factor data (age, parity, total breast volume, post-menopausal status, hormone replacement therapy, family history and history of core biopsy). The association between breast density and cancer risk was assessed by calculating the odds ratios [OR] with 95% confidence intervals using multivariable logistic regression. Results: A total of 209 cases (median age, 58.8 years) and 6812 controls (median age, 59.4 years) were included. The risk of HER2-BrCa increased with increasing levels of percent breast density. High breast density according to BIRADS-4th and -5th editions was significantly associated with HER2-BrCa: BIRADS -4th 3/4 vs 1: OR 2.50 (1.68 - 3.68); BIRADS-5th C/D vs A: OR 2.58 (1.71 - 4.01). The association between higher breast density and increased risk of HER2-BrCa remained after adjustment for clinical factors. Conclusions: The risk of HER2-BrCa was associated with progressively higher mammographic breast density, although to a lesser extent than breast cancer in general. Accurate risk models including breast density may support the development of more breast-screening protocols that can lead to more strategic use of healthcare resources.

To determine the proportion of diagnostic computed tomography colonography (CTC) Reporting and Data System (C-RADS) categories in a non-screening population, and which patient factors are associated with a positive CTC (C2–4), a non-diagnostic CTC (C0), and potentially relevant extracolonic findings (ECF, E3–4). Diagnostic CTCs performed at a single academic center from 2017 to 2018 were retrospectively reviewed. For each examination, the indications, age, sex, admission status, and C-RADS categories were recorded. Multivariate logistic regression was performed of patient demographic factors and clinical indications, with adjusted odds ratios (OR) and 95% confidence intervals. 1373 CTCs were included. The mean age was 66.4 ± 13 years (range 24–97). There were 782 women and 75 inpatients. The number of CTCs reported as C0–C4 were 194/1373 (14.1%), 970/1373 (70.6%), 77/1373 (5.6%), 86/1373 (6.3%), and 46/1373 (3.4%), respectively, and 134/1373 (9.8%), 960/1373 (69.9%), 173/1373 (12.6%), and 106/1373 (7.7%) CTCs were reported as E1–4, respectively. Factors that demonstrated the strongest associations were as follows: with C2–4, age groups 50–79 (OR 2.8, 95% confidence interval 1.4–6.1), 80–89 (6.2, 2.9–14.5) and ≥ 90 (7.6, 2.0–29.1), and inpatients (3.4, 1.8–6.4); with C0, age groups 50–79 (5.9, 2.2–24.4), 80–89 (9.8, 3.4–41.8), and ≥ 90 (22.5, 5.8–113.0), incomplete colonoscopy (3.2, 2.0–5.1) and melena or gastrointestinal bleeding (4.1, 1.8–9.4); and with E3–4, age groups 50–79 (1.6, 1.0–2.9), 80–89 (2.0, 1.1–3.9), and ≥ 90 (3.2, 1.2–8.8), and inpatients (2.3, 1.3–3.9). Older age is increasingly associated with a positive test, a non-diagnostic test and potentially relevant ECF. Inpatients are also associated with positive tests and E3–4 findings. Symptoms are not strongly associated with a positive CTC.

Rationale and Objectives: To compare the magnitude and interpatient variability in normalized mean hepatic enhancement (MHE) indices when dosing contrast media (CM) according to total body weight (TBW) and lean body weight (LBW). Materials and Methods: This ethics-approved stratified randomized controlled study allocated 280 outpatients for abdominal Computed Tomography (CT) between February-November 2018 to TBW- or LBW-dosing using computer-generated tables. CTs were acquired in portal venous phase after fixed 35-second injection of Iohexol 350. Patients with missing precontrast image, incorrect dose, or chronic kidney, liver or heart disease were excluded. The number of included patients and CM doses were: TBW arm, 51 women and 60 men, 1.22 mL/kg; LBW arm, 59 women, 1.66 mL/kg LBW, and 59 men, 1.52 mL/kg LBW. Liver attenuations were obtained from regions of interest. Values and standard deviations in MHE indices normalized to iodine dose (MHE/I) and iodine dose per kg TBW (aMHE = MHE/[I/ TBW]) were compared (unpaired t tests and F-tests). Results: Cohorts were similar in age, sex, TBW, and LBW. TBW groups received more CM than LBW groups: men, 106.5 +/- 20 versus 98.4 +/- 11 mL, p = 0.007; women, 93.7 +/- 20 versus 77.5 +/- 11 mL, p < 0.0001. TBW and LBW groups showed no significant difference in MHE/I (women, 1.75 +/- 0.5 versus 1.86 +/- 0.6 HU/g, p = 0.31; men, 1.53 +/- 0.4 versus 1.52 +/- 0.4 HU/g, p = 0.90) or aMHE (women, 0.03 +/- 0.01 versus 0.03 +/- 0.01 HU/g/kg, p = 0.25; men, 0.02 +/- 0.01 versus 0.02 +/- 0.01 HU/g/kg, p = 0.52). Variances in MHE/I and aMHE were not significantly different for all groups (p > 0.05). Conclusion: TBW- and LBW-based CM dosing yield a similar magnitude and interpatient variability in normalized MHE indices at routine abdominal CT.

Background/objective The association between maternal pre-pregnancy obesity and adverse child health outcomes is well described, but there are few data on the relationship with offspring health service use. We examined the influence of maternal pre-pregnancy obesity on offspring health care utilization and costs over the first 18 years of life. Methods This was a population-based retrospective cohort study of children ( n = 35,090) born between 1989 and 1993 and their mothers, who were identified using the Nova Scotia Atlee Perinatal Database and linked to provincial administrative health data from birth through 2014. The primary outcome was health care utilization as determined by the number and cost of physician visits, hospital admissions and days, and high utilizer status (>95th percentile of physician visits). The secondary outcome was health care utilization by ICD chapter. Maternal pre-pregnancy weight was categorized as normal weight, overweight, or obese. Multivariable-adjusted regression models were used to examine the association between maternal weight status and offspring health care use. Results Children of mothers with pre-pregnancy obesity had more physician visits (10%), hospital admissions (16%), and hospital days (10%) than children from mothers of normal weight over the first 18 years of life. Offspring of mothers with obesity had C$356 higher physician costs and C$1415 hospital costs over 18 years than offspring of normal weight mothers. Children of mothers with obesity were 1.74 times more likely to be a high utilizer of health care and had higher rates of physician visits and hospital stays for nervous system and sense organ disorders, respiratory disorders, and gastrointestinal disorders compared to children of normal weight mothers. Conclusion Our findings suggest that maternal pre-pregnancy overweight and obesity are associated with slightly higher offspring health care utilization and costs in the first 18 years of life.

INTRODUCTIONPreoperative prediction of benign vs. malignant small renal masses (SRMs) remains a challenge. This study: 1) validates our previously published classification tree (CT) with an external cohort; 2) creates a new CT with the combined cohort; and 3) evaluates the RENAL and PADUA scoring systems for prediction of malignancy.METHODSThis study includes a total of 818 patients with renal masses; 395 underwent surgical resection and 423 underwent biopsy. A CT to predict benign disease was developed using patient and tumour characteristics from the 709 eligible participants. Our CT is based on four parameters: tumour volume, symptoms, gender, and symptomatology. CART modelling was also used to determine if RENAL and PADUA scoring could predict malignancy.RESULTSWhen externally validated with the surgical cohort, the predictive accuracy of the old CT dropped. However, by combining the cohorts and creating a new CT, the predictive accuracy increased from 74% to 87% (95% confidence interval 0.84-0.89). RENAL and PADUA score alone were not predictive of malignancy. One limitation was the lack of available histological data from the biopsy series.CONCLUSIONSThe validated old CT and new combined-cohort CT have a predictive value greater than currently published nomograms and single-biopsy cohorts. Overall, RENAL and PADUA scores were not able to predict malignancy.

Objective The objective of this study was to assess the accuracy of gadoxetic acid hepatic enhancement indices in predicting posthepatectomy liver failure (PHLF) and other major complications (OMCs). Methods Sixty-five patients underwent prehepatectomy gadoxetic acid-enhanced magnetic resonance imaging. Enhancement indices were calculated by obtaining regions of interest on magnetic resonance images and segmented volumes of the liver and spleen. Multivariate regression analysis was performed to predict PHLF and OMC as a function of the indices, and areas under the receiver operator characteristic (AUROC) curves were calculated. Results Areas under the receiver operator characteristic values varied from 0.412 to 0.681 and 0.462 to 0.738 in predicting PHLF and OMC, respectively. The most accurate indices in predicting PHLF were the region of interest-based, fat-normalized relative liver enhancement and liver enhancement index (AUROC, 0.681). The most accurate index in predicting OMC was the volumetric least-squares regression slope of a pharmacokinetic model (K-hep_V, AUROC, 0.738). Conclusions Indices of gadoxetic acid liver enhancement demonstrate variable performance in predicting PHLF and OMC.