MRI for the Detection of Small Bowel Ischemic Injury in Arterial Acute Mesenteric Ischemia: Preclinical Study in a Porcine Model.

BACKGROUND: MRI is the reference for the diagnosis of arterial cerebral ischemia, but its role in acute mesenteric ischemia (AMI) is poorly known. PURPOSE: To assess MRI detection of early ischemic bowel lesions in a porcine model of arterial AMI. STUDY TYPE: Prospective/cohort. ANIMAL MODEL: Porcine model of arterial AMI obtained by embolization of the superior mesenteric artery (seven pigs). FIELD STRENGTH/SEQUENCE: A 5-T. T1 gradient-echo-weighted-imaging (WI), half-Fourier-acquisition-single-shot-turbo-spin-echo, T2 turbo-spin-echo, true-fast-imaging-with-steady-precession (True-FISP), diffusion-weighted-echo-planar (DWI). ASSESSMENT: T1-WI, T2-WI, and DWI were performed before and continuously after embolization for 6 hours. The signal intensity (SI) of the ischemic bowel was assessed visually and quantitatively on all sequences. The apparent diffusion coefficient (ADC) was assessed. STATISTICAL TESTS: Paired Student's t-test or Mann-Whitney U-test, significance at P < 0.05. RESULTS: One pig died from non-AMI-related causes. The remaining pigs underwent a median 5 h53 (range 1 h24-6 h01) of ischemia. Visually, the ischemic bowel showed signal hyperintensity on DWI-b800 after a median 85 (57-276) minutes compared to the nonischemic bowel. DWI-b800 SI significantly increased after 2 hours (+19%) and the ADC significant decrease within the first hour (-31%). The ischemic bowel was hyperintense on precontrast T1-WI after a median 87 (70-171) minutes with no significant quantitative changes over time (P = 0.46-0.93). The ischemic bowel was hyperintense on T2-WI in three pigs with a significant SI increase on True-FISP after 1 and 2 hours. DATA CONCLUSION: Changes in SI and ADC can be seen early after the onset of arterial AMI with DWI. The value of T2-WI appears to be limited. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Paradigm shift: should preoperative 3D reconstruction models become mandatory before hepatectomy for hepatocellular carcinoma (HCC)? Results of a multicenter prospective trial.

BACKGROUND: A preoperative surgical strategy before hepatectomy for hepatocellular carcinoma is fundamental to minimize postoperative morbidity and mortality and to reach the best oncologic outcomes. Preoperative 3D reconstruction models may help to better choose the type of procedure to perform and possibly change the initially established plan based on conventional 2D imaging. METHODS: A non-randomized multicenter prospective trial with 136 patients presenting with a resectable hepatocellular carcinoma who underwent open or minimally invasive liver resection. Measurement was based on the modification rate analysis between conventional 2D imaging (named "Plan A") and 3D model analysis ("Plan B"), and from Plan B to the final procedure performed (named "Plan C"). RESULTS: The modification rate from Plan B to Plan C (18%) was less frequent than the modification from Plan A to Plan B (35%) (OR = 0.32 [0.15; 0.64]). Concerning secondary objectives, resection margins were underestimated in Plan B as compared to Plan C (-3.10 mm [-5.04; -1.15]). CONCLUSION: Preoperative 3D imaging is associated with a better prediction of the performed surgical procedure for liver resections in HCC, as compared to classical 2D imaging.

Robotically assisted augmented reality system for identification of targeted lymph nodes in laparoscopic gynecological surgery: a first step toward the identification of sentinel node : Augmented reality in gynecological surgery.

BACKGROUND: To prove feasibility of multimodal and temporal fusion of laparoscopic images with preoperative computed tomography scans for a real-time in vivo-targeted lymph node (TLN) detection during minimally invasive pelvic lymphadenectomy and to validate and enable such guidance for safe and accurate sentinel lymph node dissection, including anatomical landmarks in an experimental model. METHODS: A measurement campaign determined the most accurate tracking system (UR5-Cobot versus NDI Polaris). The subsequent interventions on two pigs consisted of an identification of artificial TLN and anatomical landmarks without and with augmented reality (AR) assistance. The AR overlay on target structures was quantitatively evaluated. The clinical relevance of our system was assessed via a questionnaire completed by experienced and trainee surgeons. RESULTS: An AR-based robotic assistance system that performed real-time multimodal and temporal fusion of laparoscopic images with preoperative medical images was developed and tested. It enabled the detection of TLN and their surrounding anatomical structures during pelvic lymphadenectomy. Accuracy of the CT overlay was > 90%, with overflow rates < 6%. When comparing AR to direct vision, we found that scores were significatively higher in AR for all target structures. AR aided both experienced surgeons and trainees, whether it was for TLN, ureter, or vessel identification. CONCLUSION: This computer-assisted system was reliable, safe, and accurate, and the present achievements represent a first step toward a clinical study.

Diffuse Versus Localized Caroli Disease: A Comparative MRCP Study.

OBJECTIVE. The purpose of this multicenter retrospective study was to assess the MRCP features of Caroli disease (CD). MATERIALS AND METHODS. Sixty-six patients were identified from 2000 to 2019. The inclusion criteria were diagnosis of diffuse or localized CD mentioned in an imaging report, presence of intrahepatic bile duct (IHBD) dilatation, and having undergone an MRCP examination. The exclusion criteria included presence of obstructive proximal biliary stricture and having undergone hepatobiliary surgery other than cholecystectomy. Histopathology records were available for 53 of the 66 (80%) patients. Diffuse and localized diseases were compared by chi-square and t tests and Kaplan-Meier model. RESULTS. Forty-five patients had diffuse bilobar CD ((five pediatric patients [three girls and two boys] with a mean [± SD] age of 8 ± 5 years [range, 1-15 years] and 40 adult patients [26 men and 14 women] with a mean age of 35 ± 11 years [range, 20-62 years]) and 21 patients had localized disease (12 men and 9 women; mean age, 54 ± 14 years). Congenital hepatic fibrosis was found only in patients with diffuse CD (35/45 [78%]), as was a "central dot" sign (15/35 [43%]). IHBD dilatation with both saccular and fusiform features was found in 43 (96%) and the peripheral "funnel-shaped" sign in 41 (91%) of the 45 patients with diffuse CD but in none of the patients with localized disease (p < .001). Intrahepatic biliary calculi were found in all patients with localized disease but in only 16 of the 45 (36%) patients with diffuse CD (p < .001). Left liver atrophy was found in 18 of the 21 (86%) patients with localized disease and in none of the patients with diffuse CD (p < .001). The overall survival rate among patients with diffuse CD was significantly lower than that among patients with localized disease (p = .03). CONCLUSION. Diffuse IHBD dilatation with both saccular and fusiform features associated with the peripheral funnel-shaped sign can be used for the diagnosis of CD on MRCP. Localized IHBD dilatation seems to be mainly related to primary intrahepatic lithiasis.

Precision image-guided colonic surgery: proof of concept for enhanced preoperative and intraoperative vascular imaging.

BACKGROUND: Colorectal surgery has benefited from advances in precision medicine such as total mesorectal resection, and recently, mesocolon resection, fluorescent perfusion imaging, and fluorescent node mapping. However, these advances fail to address the variable quality of mesocolon dissection and the directed extent of vascular dissection (including high ligation) or pre-resection anastomotic perfusion mapping, thereby impacting anastomotic leaks. We propose a new paradigm of precision image-directed colorectal surgery involving 3D preoperative resection modeling and intraoperative fluoroscopic and fluorescence vascular imaging which better defines optimal dissection planes and vascular vs. anatomy-based resection lines according to our hypothesis. METHODS: Six pigs had preoperative CT with vascular 3D reconstruction allowing for the preoperative planning of vascular-based dissection. Laparoscopic surgery was performed in a hybrid operating room (OR). Superselective arterial catheterization was performed in branches of the superior mesenteric artery (SMA) or the inferior mesenteric artery (IMA). Intraoperative boluses of 0.1 mg/kg or a continuous infusion of indocyanine green (ICG) (0.01 mg/mL) were administered to guide fluorescent-based sigmoid and ileocecal resections. Fluorescence was assessed using proprietary software at several regions of interest (ROI) in the right and left colon. RESULTS: The approach was feasible and safe. Selective catheterization took an average of 43 min. Both bolus and continuous perfusion clearly marked pre-identified vessels (arteries/veins) and the target colon segment, facilitating precise resections based on the visible vascular anatomy. Quantitative software analysis indicated the optimal resection margin for each ROI. CONCLUSION: Intra-arterial fluorescent mapping allows visualization of major vascular structures and segmental colonic perfusion. This may help to prevent any inadvertent injury to major vascular structures and to precisely determine perfusion-based resection planes and margins. This could enable tailoring of the amount of colon resected, ensure good anastomotic perfusion, and improve oncological outcomes.

COVID-19 Efforts at the Institute of Image Guided Surgery (IHU-Strasbourg): 2020.

We submit a summary of some of the activities of the IHU-Strasbourg during the initial period of the COVID-19 pandemic. These were presented as part of the coronnavation effort coordinated by Dr Adrian Park. Three initiatives are presented as follows: Protect-Est App, healthcare worker stress, and converted diving mask for ventilation. Two of the 3 projects are still ongoing, and one (Predoict-Est) has been adopted nationally.

Early evaluation using a radiomic signature of unresectable hepatic metastases to predict outcome in patients with colorectal cancer treated with FOLFIRI and bevacizumab.

PURPOSE: The objective of this study was to build and validate a radiomic signature to predict early a poor outcome using baseline and 2-month evaluation CT and to compare it to the RECIST1·1 and morphological criteria defined by changes in homogeneity and borders. METHODS: This study is an ancillary study from the PRODIGE-9 multicentre prospective study for which 491 patients with metastatic colorectal cancer (mCRC) treated by 5-fluorouracil, leucovorin and irinotecan (FOLFIRI) and bevacizumab had been analysed. In 230 patients, computed texture analysis was performed on the dominant liver lesion (DLL) at baseline and 2 months after chemotherapy. RECIST1·1 evaluation was performed at 6 months. A radiomic signature (Survival PrEdiction in patients treated by FOLFIRI and bevacizumab for mCRC using contrast-enhanced CT TextuRe Analysis (SPECTRA) Score) combining the significant predictive features was built using multivariable Cox analysis in 120 patients, then locked, and validated in 110 patients. Overall survival (OS) was estimated with the Kaplan-Meier method and compared between groups with the logrank test. An external validation was performed in another cohort of 40 patients from the PRODIGE 20 Trial. RESULTS: In the training cohort, the significant predictive features for OS were: decrease in sum of the target liver lesions (STL), (adjusted hasard-ratio(aHR)=13·7, p=1·93×10-7), decrease in kurtosis (ssf=4) (aHR=1·08, p=0·001) and high baseline density of DLL, (aHR=0·98, p<0·001). Patients with a SPECTRA Score >0·02 had a lower OS in the training cohort (p<0·0001), in the validation cohort (p<0·0008) and in the external validation cohort (p=0·0027). SPECTRA Score at 2 months had the same prognostic value as RECIST at 6 months, while non-response according to RECIST1·1 at 2 months was not associated with a lower OS in the validation cohort (p=0·238). Morphological response was not associated with OS (p=0·41). CONCLUSION: A radiomic signature (combining decrease in STL, density and computed texture analysis of the DLL) at baseline and 2-month CT was able to predict OS, and identify good responders better than RECIST1.1 criteria in patients with mCRC treated by FOLFIRI and bevacizumab as a first-line treatment. This tool should now be validated by further prospective studies. TRIAL REGISTRATION: Clinicaltrial.gov identifier of the PRODIGE 9 study: NCT00952029.Clinicaltrial.gov identifier of the PRODIGE 20 study: NCT01900717.

Simple Magnetic Resonance Scores Associate With Outcomes of Patients With Primary Sclerosing Cholangitis.

BACKGROUND & AIMS: Primary sclerosing cholangitis (PSC) has a variable, often progressive, course. Magnetic resonance cholangiography (MRC) is used in the diagnosis of PSC. Magnetic resonance risk scoring systems, called Anali without and with gadolinium, are used to predict disease progression, determined by radiologic factors. We aimed to assess the prognostic value of Anali scores in patients with PSC and validate our findings in a separate cohort. METHODS: We performed a retrospective study of patients with large-duct PSC (internal cohort, 119 patients in France; external cohort, 119 patients in Canada, Italy, and the United Kingdom). All the first-available MRC results were reviewed by 2 radiologists and the Anali scores were calculated as follows: Anali without gadolinium = (1× dilatation of intrahepatic bile ducts) + (2× dysmorphy) + (1× portal hypertension); Anali with gadolinium = (1× dysmorphy) + (1× parenchymal enhancement heterogeneity). The primary end point was survival without liver transplantation or cirrhosis decompensation. The prognostic value of Anali scores was assessed by Cox regression modeling. RESULTS: During a total of 549 patient-years for the internal cohort and 497 patient-years for the external cohort, we recorded 2 and 8 liver transplantations, 4 and 3 liver-related deaths, and 26 and 25 cirrhosis decompensations, respectively. In the univariate analysis, factors associated with survival without liver transplantation or cirrhosis decompensation in the internal cohort were as follows: serum levels of bilirubin, aspartate aminotransferase, alanine aminotransferase, γ-glutamyl transferase, alkaline phosphatase, albumin, and Anali scores. Anali scores without and with gadolinium identified patients' survival without liver transplantation or cirrhosis decompensation with a c-statistic of 0.89 (95% CI, 0.84-0.95) and 0.75 (95% CI, 0.64-0.87), respectively. Independent prognostic factors identified by multivariate analysis were Anali scores and bilirubinemia. The prognostic value of Anali scores was confirmed in the external cohort. CONCLUSIONS: In internal and external cohorts, we found that Anali scores, determined from MRC, were associated with outcomes of patients with PSC. These scores might be used as prognostic factors.

Predictors of Mortality from Spontaneous Soft-Tissue Hematomas in a Large Multicenter Cohort Who Underwent Percutaneous Transarterial Embolization.

Purpose To evaluate the safety and efficacy of percutaneous transarterial embolization (PTAE) for the treatment of spontaneous soft-tissue hematomas (SSTHs) and identify variables predictive of short-term outcome. Materials and Methods Between 2011 and 2017, the outcome was retrospectively analyzed for 112 patients (mean age ± standard deviation, 72 years ± 14; range, 28-92 years), including 65 women (mean age, 73 years ± 12.7; range, 39-92 years) and 47 men (mean age, 70 years ± 14.9; range, 28-91 years), with SSTH treated with PTAE. Thirty-day mortality, technical and clinical success, simplified acute physiology score (SAPS) II, anticoagulation, embolic agent, hematoma volume and location, serum hemoglobin level, hemodynamic instability, and presence of active bleeding at CT and/or angiography were recorded. Clinical success was defined as cessation of bleeding as determined by hemodynamic stability and/or serum hemoglobin level stabilization after PTAE. Univariable and multivariable analyses were performed by using a Cox model to identify variables associated with time to death. Results Mortality rate was 26.8% (30 of 112 patients), angiographic success rate was 95.5% (107 of 112 patients), and clinical success rate was 83% (93 of 112 patients). For surviving patients, mean SAPS II was 19.6 ± 7.1 (range, 13-31) and mean hematoma volume was 862 cm3 ± 618 (range, 238-1887 cm3). For deceased patients, mean SAPS II was 42 ± 13.2 (range, 18-63) and mean hematoma volume was 1419 cm3 ± 788 (range, 251-3492 cm3). SAPS II (P < .001), hematoma volume (P = .01), and retroperitoneal location (P = .01) were independently associated with fatal outcome. Conclusion Percutaneous transarterial embolization is effective for the emergency treatment of spontaneous soft-tissue hematomas. Simplified acute physiology score II, hematoma volume, and retroperitoneal location are predictors of short-term outcome. © RSNA, 2019 Online supplemental material is available for this article.

Artificial intelligence in radiology: who's afraid of the big bad wolf?

This Editorial comment refers to the article "Medical students' attitude towards artificial intelligence: a multicenter survey," Pinto Dos Santos D, et al Eur Radiol 2018. KEY POINTS: • Medical students are not well informed of the potential consequences of AI in radiology. • The fundamental principles of AI-as well as its application in medicine-must be taught in medical schools. • The radiologist specialty must actively reflect on how to validate, approve, and integrate AI algorithms into our clinical practices.

Image-based biomarkers for solid tumor quantification.

The last few decades have witnessed tremendous technological developments in image-based biomarkers for tumor quantification and characterization. Initially limited to manual one- and two-dimensional size measurements, image biomarkers have evolved to harness developments not only in image acquisition technology but also in image processing and analysis algorithms. At the same time, clinical validation remains a major challenge for the vast majority of these novel techniques, and there is still a major gap between the latest technological developments and image biomarkers used in everyday clinical practice. Currently, the imaging biomarker field is attracting increasing attention not only because of the tremendous interest in cutting-edge therapeutic developments and personalized medicine but also because of the recent progress in the application of artificial intelligence (AI) algorithms to large-scale datasets. Thus, the goal of the present article is to review the current state of the art for image biomarkers and their use for characterization and predictive quantification of solid tumors. Beginning with an overview of validated imaging biomarkers in current clinical practice, we proceed to a review of AI-based methods for tumor characterization, such as radiomics-based approaches and deep learning.Key Points• Recent years have seen tremendous technological developments in image-based biomarkers for tumor quantification and characterization.• Image-based biomarkers can be used on an ongoing basis, in a non-invasive (or mildly invasive) way, to monitor the development and progression of the disease or its response to therapy.• We review the current state of the art for image biomarkers, as well as the recent developments in artificial intelligence (AI) algorithms for image processing and analysis.

Demystification of AI-driven medical image interpretation: past, present and future.

The recent explosion of 'big data' has ushered in a new era of artificial intelligence (AI) algorithms in every sphere of technological activity, including medicine, and in particular radiology. However, the recent success of AI in certain flagship applications has, to some extent, masked decades-long advances in computational technology development for medical image analysis. In this article, we provide an overview of the history of AI methods for radiological image analysis in order to provide a context for the latest developments. We review the functioning, strengths and limitations of more classical methods as well as of the more recent deep learning techniques. We discuss the unique characteristics of medical data and medical science that set medicine apart from other technological domains in order to highlight not only the potential of AI in radiology but also the very real and often overlooked constraints that may limit the applicability of certain AI methods. Finally, we provide a comprehensive perspective on the potential impact of AI on radiology and on how to evaluate it not only from a technical point of view but also from a clinical one, so that patients can ultimately benefit from it. KEY POINTS: • Artificial intelligence (AI) research in medical imaging has a long history • The functioning, strengths and limitations of more classical AI methods is reviewed, together with that of more recent deep learning methods. • A perspective is provided on the potential impact of AI on radiology and on its evaluation from both technical and clinical points of view.

Value of Shear Wave Elastography for the Differentiation of Benign and Malignant Microcalcifications of the Breast.

OBJECTIVE. The objective of our study was to evaluate whether shear wave elastography (SWE) can differentiate benign from malignant microcalcifications of the breast when detected on ultrasound (US). SUBJECTS AND METHODS. Between February 9, and June 23, 2016, 74 patients with mammographically detected suspicious microcalcifications underwent breast US. When microcalcifications were identified on US, stiffness was assessed using SWE. Biopsy was subsequently performed under US guidance using a 10-gauge vacuum-assisted needle. Qualitative and quantitative elastography results were compared between benign and malignant calcifications as well as between pure ductal carcinoma in situ and lesions with invasive components using the Mann-Whitney U test. ROC curves were created to assess the performance of SWE in detecting malignancy and invasive components. RESULTS. Twenty-nine groups of microcalcifications in 29 patients were identified on US. At pathology, 16 groups were benign and 13 were malignant. Stiffness of malignant calcifications was significantly higher than that of the benign ones (p = 0.0004). The AUC, sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of SWE for the diagnosis of malignancy were 0.89, 69%, 100%, 80%, 100%, and 86%, respectively, and for detection of an invasive component were 0.93, 75%, 100%, 75%, 100%, and 85%. CONCLUSION. SWE has the potential to differentiate benign from malignant micro-calcifications of the breast when detected on US with high specificity.

Features from Computerized Texture Analysis of Breast Cancers at Pretreatment MR Imaging Are Associated with Response to Neoadjuvant Chemotherapy.

Purpose To evaluate whether features from texture analysis of breast cancers were associated with pathologic complete response (pCR) after neoadjuvant chemotherapy and to explore the association between texture features and tumor subtypes at pretreatment magnetic resonance (MR) imaging. Materials and Methods Institutional review board approval was obtained. This retrospective study included 85 patients with 85 breast cancers who underwent breast MR imaging before neoadjuvant chemotherapy between April 10, 2008, and March 12, 2015. Two-dimensional texture analysis was performed by using software at T2-weighted MR imaging and contrast material-enhanced T1-weighted MR imaging. Quantitative parameters were compared between patients with pCR and those with non-pCR and between patients with triple-negative breast cancer and those with non-triple-negative cancer. Multiple logistic regression analysis was used to determine independent parameters. Results Eighteen tumors (22%) were triple-negative breast cancers. pCR was achieved in 30 of the 85 tumors (35%). At univariate analysis, mean pixel intensity with spatial scaling factor (SSF) of 2 and 4 on T2-weighted images and kurtosis on contrast-enhanced T1-weighted images showed a significant difference between triple-negative breast cancer and non-triple-negative breast cancer (P = .009, .003, and .001, respectively). Kurtosis (SSF, 2) on T2-weighted images showed a significant difference between pCR and non-pCR (P = .015). At multiple logistic regression, kurtosis on T2-weighted images was independently associated with pCR in non-triple-negative breast cancer (P = .033). A multivariate model incorporating T2-weighted and contrast-enhanced T1-weighted kurtosis showed good performance for the identification of triple-negative breast cancer (area under the receiver operating characteristic curve, 0.834). Conclusion At pretreatment MR imaging, kurtosis appears to be associated with pCR to neoadjuvant chemotherapy in non-triple-negative breast cancer and may be a promising biomarker for the identification of triple-negative breast cancer. © RSNA, 2017.

Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology.

Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the last 5 years, AI techniques known as deep learning have delivered rapidly improving performance in image recognition, caption generation, and speech recognition. Radiology, in particular, is a prime candidate for early adoption of these techniques. It is anticipated that the implementation of AI in radiology over the next decade will significantly improve the quality, value, and depth of radiology's contribution to patient care and population health, and will revolutionize radiologists' workflows. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI working group with the mandate to discuss and deliberate on practice, policy, and patient care issues related to the introduction and implementation of AI in imaging. This white paper provides recommendations for the CAR derived from deliberations between members of the AI working group. This white paper on AI in radiology will inform CAR members and policymakers on key terminology, educational needs of members, research and development, partnerships, potential clinical applications, implementation, structure and governance, role of radiologists, and potential impact of AI on radiology in Canada.

Endometrial Carcinoma: MR Imaging-based Texture Model for Preoperative Risk Stratification-A Preliminary Analysis.

Purpose To evaluate the associations among mathematical modeling with the use of magnetic resonance (MR) imaging-based texture features and deep myometrial invasion (DMI), lymphovascular space invasion (LVSI), and histologic high-grade endometrial carcinoma. Materials and Methods Institutional review board approval was obtained for this retrospective study. This study included 137 women with endometrial carcinomas measuring greater than 1 cm in maximal diameter who underwent 1.5-T MR imaging before hysterectomy between January 2011 and December 2015. Texture analysis was performed with commercial research software with manual delineation of a region of interest around the tumor on MR images (T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced images and apparent diffusion coefficient maps). Areas under the receiver operating characteristic curve and diagnostic performance of random forest models determined by using a subset of the most relevant texture features were estimated and compared with those of independent and blinded visual assessments by three subspecialty radiologists. Results A total of 180 texture features were extracted and ultimately limited to 11 features for DMI, 12 for LVSI, and 16 for high-grade tumor for random forest modeling. With random forest models, areas under the receiver operating characteristic curve, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were estimated at 0.84, 79.3%, 82.3%, 81.0%, 76.7%, and 84.4% for DMI; 0.80, 80.9%, 72.5%, 76.6%, 74.3%, and 79.4% for LVSI; and 0.83, 81.0%, 76.8%, 78.1%, 60.7%, and 90.1% for high-grade tumor, respectively. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of visual assessment for DMI were 84.5%, 82.3%, 83.2%, 77.7%, and 87.8% (reader 3). Conclusion The mathematical models that incorporated MR imaging-based texture features were associated with the presence of DMI, LVSI, and high-grade tumor and achieved equivalent accuracy to that of subspecialty radiologists for assessment of DMI in endometrial cancers larger than 1 cm. However, these preliminary results must be interpreted with caution until they are validated with an independent data set, because the small sample size relative to the number of features extracted may have resulted in overfitting of the models. © RSNA, 2017 Online supplemental material is available for this article.

Portal Vein Embolization in the Setting of Staged Hepatectomy with Preservation of Segment IV ± I Only for Bilobar Colorectal Liver Metastases: Safety, Efficacy, and Clinical Outcomes.

PURPOSE: To assess frequency of adverse events, efficacy, and clinical outcomes of percutaneous portal vein embolization (PVE) in patients with bilobar colorectal liver metastases undergoing staged hepatectomy with preservation of segment IV ± I only. MATERIALS AND METHODS: Retrospective analysis was performed of 40 consecutive patients who underwent right PVE after successful left lobectomy between 2005 and 2013. Rates of adverse events, future liver remnant (FLR) > 30% compared with baseline liver volume, clinical success (completion of staged hepatectomy with clearance of liver metastases), and overall survival were analyzed. RESULTS: PVE was performed using polyvinyl alcohol particles (n = 7; 17.5%), particles plus coils (n = 23; 57.5%), and N-butyl cyanoacrylate glue plus ethiodized oil (n = 10; 25%). Technical success was 100%. After PVE, 20% (n = 8) of patients exhibited portal venous thrombosis, ranging from isolated intrahepatic portal branch thrombosis to massive thrombosis of the main portal vein (n = 3) and responsible for periportal cavernoma and portal hypertension in 5 patients. Of patients, 23 (57.5%) had FLR ≥ 30%, and 21 (52.5%) had clinical success. Six patients had significant stenosis or occlusion of the left portal vein or biliary system after original left lobectomy, which was independently associated with FLR < 30% (R2 = 0.24). Clinical success was the only independent variable associated with survival (R2 = 0.25). CONCLUSIONS: PVE for staged hepatectomy with preservation of segment IV ± I only is technically feasible, leading to adequate hypertrophy and clinical success rates in these patients with poor oncologic prognosis. Portal venous thrombosis is greater after the procedure than in the setting of standard PVE.

Accuracy and generalizability of using automated methods for identifying adverse events from electronic health record data: a validation study protocol.

BACKGROUND: Adverse events (AEs) in acute care hospitals are frequent and associated with significant morbidity, mortality, and costs. Measuring AEs is necessary for quality improvement and benchmarking purposes, but current detection methods lack in accuracy, efficiency, and generalizability. The growing availability of electronic health records (EHR) and the development of natural language processing techniques for encoding narrative data offer an opportunity to develop potentially better methods. The purpose of this study is to determine the accuracy and generalizability of using automated methods for detecting three high-incidence and high-impact AEs from EHR data: a) hospital-acquired pneumonia, b) ventilator-associated event and, c) central line-associated bloodstream infection. METHODS: This validation study will be conducted among medical, surgical and ICU patients admitted between 2013 and 2016 to the Centre hospitalier universitaire de Sherbrooke (CHUS) and the McGill University Health Centre (MUHC), which has both French and English sites. A random 60% sample of CHUS patients will be used for model development purposes (cohort 1, development set). Using a random sample of these patients, a reference standard assessment of their medical chart will be performed. Multivariate logistic regression and the area under the curve (AUC) will be employed to iteratively develop and optimize three automated AE detection models (i.e., one per AE of interest) using EHR data from the CHUS. These models will then be validated on a random sample of the remaining 40% of CHUS patients (cohort 1, internal validation set) using chart review to assess accuracy. The most accurate models developed and validated at the CHUS will then be applied to EHR data from a random sample of patients admitted to the MUHC French site (cohort 2) and English site (cohort 3)-a critical requirement given the use of narrative data -, and accuracy will be assessed using chart review. Generalizability will be determined by comparing AUCs from cohorts 2 and 3 to those from cohort 1. DISCUSSION: This study will likely produce more accurate and efficient measures of AEs. These measures could be used to assess the incidence rates of AEs, evaluate the success of preventive interventions, or benchmark performance across hospitals.

Hepatic artery complications following liver transplantation. Does preoperative chemoembolization impact the postoperative course?

BACKGROUND: Transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) may cause damage to the hepatic artery (HA) and impact the postoperative course of the liver transplantation (LT). We aim to describe the relationship between preoperative TACE and the occurrence of histological and radiological hepatic artery complications (HAC). METHODS: All cirrhotic patients with HCC undergoing LT between January 2009 and October 2012 were included and divided in two groups: TACE (group 1) and No TACE (group 2). HA histological complications were reviewed and compared. RESULTS: Sixty-seven patients were reviewed, 32 in group 1 and 35 in group 2. Both groups were similar in gender, age, cirrhosis origin, and American Society of Anesthesiology (ASA) score. After a mean follow-up of 17 months, 10 radiological HAC occurred: seven in group 1 and three in group 2 (p = 0.02). There was one thrombosis in each group: six non-thrombotic complications in group 1 and two in group 2. Histological screening showed 12 HA injuries in group 1 (three HA wall edemas, five fibrosis, one edema + fibrosis, one hemorragic necrosis + thrombosis, two thrombosis) and three in group 2 (two HA wall edemas, one fibrosis) (p = 0.01). All these injuries were found at the proper HA and at the right/left HA bifurcation level. CONCLUSIONS: Despite the limits of our study, we found a higher incidence of radiological and histological injury in patients underwent TACE.