Welcome to brand new Ask the Fish. Post your questions in different boards to get in touch with CTisus team & Dr. Elliot K. Fishman!
Our old Ask the Fish forum can be still viewed as an archive at https://ctisus.com/redesign-askfish/index.html.
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Recent Posts

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Facebook Live / GI Bleeding
« Last post by Lilly Kauffman on January 08, 2019, 03:21:10 pm »
Our Facebook Live video on GI Bleeding: https://www.facebook.com/ctisus/videos/543596602787786/

Post your thoughts here!
Biliary Tract Cancer at CT: A Radiomics-based Model to Predict Lymph Node Metastasis and Survival Outcomes.

Radiology. 2019 Jan;290(1):90-98. doi: 10.1148/radiol.2018181408. Epub 2018 Oct 16.
Ji GW1, Zhang YD1, Zhang H1, Zhu FP1, Wang K1, Xia YX1, Zhang YD1, Jiang WJ1, Li XC1, Wang XH1.


Purpose To evaluate a radiomics model for predicting lymph node (LN) metastasis in biliary tract cancers (BTCs) and to determine its prognostic value for disease-specific and recurrence-free survival. Materials and Methods For this retrospective study, a radiomics model was developed on the basis of a primary cohort of 177 patients with BTC who underwent resection and LN dissection between June 2010 and December 2016. Radiomic features were extracted from portal venous CT scans. A radiomics signature was built on the basis of reproducible features by using the least absolute shrinkage and selection operator method. Multivariable logistic regression model was adopted to establish a radiomics nomogram. Nomogram performance was determined by its discrimination, calibration, and clinical usefulness. The model was internally validated in 70 consecutive patients with BTC between January 2017 and February 2018. Results The radiomics signature, composed of three LN-status-related features, was associated with LN metastasis in primary and validation cohorts (P < .001). The radiomics nomogram that incorporated radiomics signature and CT-reported LN status showed good calibration and discrimination in primary cohort (area under the curve, 0.81) and validation cohort (area under the curve, 0.80). Patients at high risk of LN metastasis portended lower disease-specific and recurrence-free survival than did those at low risk after surgery (both P < .001). High-risk LN metastasis was an independent preoperative predictor of disease-specific survival (hazard ratio, 3.37; P < .001) and recurrence-free survival (hazard ratio, 1.98; P = .003). Conclusion A radiomics model derived from portal phase CT of the liver has good performance for predicting lymph node metastasis in biliary tract cancer and may help to improve clinical decision making. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Laghi and Voena in this issue.

DOI: https://doi.org/10.1148/radiol.2018181408


What are your thoughts?  Comments?
Understanding and interpreting CT angiography in peripheral vascular disease

M.L. Bera

Peripheral vascular disease (PVD) is most common in elderly age group with majority of them being asymptomatic or undiagnosed. Good patient outcome depends on prompt diagnosis and early intervention while emergencies are reversible. The choice between different imaging techniques depends on local protocols, availability of local expertise/services, and needs of the local population.

DOI: https://doi.org/10.1016/j.jicc.2015.10.017


What are your comments?  Thoughts?
The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program.

J Am Coll Radiol. 2018 Dec;15(12):1753-1757. doi: 10.1016/j.jacr.2017.12.021. Epub 2018 Feb 21.
Collado-Mesa F1, Alvarez E2, Arheart K3.


PURPOSE: Advances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey was conducted among trainees and attending radiologists at a single residency program.

METHODS: An anonymous questionnaire was distributed. Comparisons of categorical data between groups (trainees and attending radiologists) were made using Pearson χ2 analysis or an exact analysis when required. Comparisons were made using the Wilcoxon rank sum test when the data were not normally distributed. An α level of 0.05 was used.

RESULTS: The overall response rate was 66% (69 of 104). Thirty-six percent of participants (n = 25) reported not having read a scientific medical article on the topic of artificial intelligence during the past 12 months. Twenty-nine percent of respondents (n = 12) reported using artificial intelligence tools during their daily work. Trainees were more likely to express doubts on whether they would have pursued diagnostic radiology as a career had they known of the potential impact artificial intelligence is predicted to have on the specialty (P = .0254) and were also more likely to plan to learn about the topic (P = .0401).

CONCLUSIONS: Radiologists lack exposure to current scientific medical articles on artificial intelligence. Trainees are concerned by the implications artificial intelligence may have on their jobs and desire to learn about the topic. There is a need to develop educational resources to help radiologists assume an active role in guiding and facilitating the development and implementation of artificial intelligence tools in diagnostic radiology.

DOI: https://doi.org/10.1016/j.jacr.2017.12.021


What are your thoughts?  Comments?
The Impact of a 1-Day Multidisciplinary Prostate Cancer Clinic on Patients' Choice of Treatment.

J Am Coll Radiol. 2018 Dec;15(12):1745-1748. doi: 10.1016/j.jacr.2018.06.023. Epub 2018 Aug 3.
Cushman TR1, Mashni J2, Roberts T3, Kumar R4.

Prostate cancer is the most common solid malignancy in men in the United States, affecting an estimated 240,000 men each year [1]. Fortunately, it is typically a slow-progressing cancer, and only approximately 14% of men with prostate cancer will die from the disease [2]. There is no clear evidence demonstrating improved survival from definitive treatment in patients with low-risk prostate cancer, which has led to controversy in how to best manage this group [2]. The National Comprehensive Cancer Network treatment recommendations for low-risk prostate cancer with a life expectancy of 10 or more years include active surveillance (prostate-specific antigen monitoring, yearly digital rectal examination, and biopsy), external-beam radiation therapy, brachytherapy, or even radical prostatectomy [3]. For intermediate- and high-risk patients, treatment recommendations are similarly diverse, and also include androgen deprivation therapy.

DOI: https://doi.org/10.1016/j.jacr.2018.06.023


What are your thoughts & comments?
we like water and IV contrast for r/o appendicitis. remember only about 25% of patients actually will have appendicitis and the other causes of the patients symptoms can be detected on the single exam!
CTisus iOS Apps / CTisus L-Spine Pathology
« Last post by Lilly Kauffman on January 02, 2019, 12:24:17 pm »
Our newest iPad app: https://itunes.apple.com/us/app/ctisus-l-spine-pathology/id1436496488?mt=8

Please leave comments, reviews, feedback, etc here!
CME / ORLANDO, FL: 35th Annual Computed Body Tomography 2019....
« Last post by Lilly Kauffman on January 02, 2019, 12:13:44 pm »
35th Annual Computed Body Tomography 2019: The Cutting Edge

Walt Disney World Swan Resort, Orlando, FL
February 7-10, 2019

Elliot K. Fishman, MD, FACR
Activity Director
Professor of Radiology and Radiological Science, Oncology, Surgery and Urology
Director, Diagnostic Imaging and Body CT

Linda Chu, MD
Assistant Professor of Radiology and Radiological Science

Jan Fritz, MD
Associate Professor of Radiology and Radiological Science

Karen M. Horton, MD
Professor and Chair
Professor of Radiology and Radiological Science

Stefan Zimmerman, MD
Associate Professor of Radiology and Radiological Science

Info: https://hopkinscme.cloud-cme.com/default.aspx?P=5&EID=15354

Facebook Event: https://www.facebook.com/events/2287889211234965/
Diagnostic performance of CT for pediatric patients with suspected appendicitis in various clinical settings: a systematic review and meta-analysis.

Emerg Radiol. 2018 Jul 12. doi: 10.1007/s10140-018-1624-9. [Epub ahead of print]

Kim DW1, Yoon HM2, Lee JY3, Kim JH4, Jung AY5, Lee JS5, Cho YA5.


OBJECTIVE: To assess the diagnostic performance of CT for pediatric patients with suspected appendicitis in various clinical settings and the proportion of acute appendicitis on final diagnosis among equivocal CT findings.

METHODS: MEDLINE and EMBASE databases were searched until October 21, 2017, for studies investigating diagnostic performance of CT for acute appendicitis in pediatric patients confirmed by histopathologic findings and/or clinical follow-up. Pooled estimates of sensitivity and specificity were calculated using a hierarchical logistic regression modeling. The proportion of true appendicitis among patients with inconclusive CT results was obtained using fixed and random effects meta-analyses.

RESULTS: Twenty-two articles with 3396 patients were included. The pooled sensitivity and specificity were 95% (95% CI, 93-97%) and 94% (95% CI, 90-96%), respectively, and the area under the hierarchical summary receiver operating characteristic (HSROC) curve was 0.98 (95% CI, 0.96-0.99). Subgroup analyses revealed a comparable diagnostic performance in the low-dose CT group (sensitivity, 97%; specificity, 96%) and the unenhanced group (sensitivity, 95%; specificity, 95%). Other subgroups (publication year, study design, enrolled population, true appendicitis proportion, CT channel number, and slice thickness) also showed good diagnostic performance. Six studies reporting the true appendicitis proportion among patients with equivocal CT findings had pooled proportion of 17% (95% CI, 9-29%).

CONCLUSIONS: CT showed good performance for suspected appendicitis in pediatric patients under various clinical settings, including in cases with dose reduction or absence of IV contrast. The prevalence of true appendicitis among patients with equivocal appendicitis results on CTs was not low; therefore, clinical attention should not be disregarded in this population.

DOI: https://doi.org/10.1007/s10140-018-1624-9


What are your thoughts?  Comments?
Lectures & Quizzes / Re: January 2019 Quiz
« Last post by Elliot K. Fishman, MD on January 02, 2019, 10:31:45 am »
got all 10 correct.
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