scholarly journals 82: Abdominal computed tomography (CT) scan in the evaluation of refractory puerperal fever: Impact on management

2018 ◽  
Vol 218 (1) ◽  
pp. S59
Author(s):  
Michal Fishel Bartal ◽  
Baha Sibai ◽  
Tali Ben-Mayor Bashi ◽  
Ayelet Dangot ◽  
Irit Eisen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ct Scan ◽  
Puerperal Fever ◽  
Abdominal Computed Tomography

Abdominal computed tomography (CT) scan in the evaluation of refractory puerperal fever: impact on management

2018 ◽  
Vol 33 (4) ◽  
pp. 577-582 ◽  
Author(s):  
Michal Fishel Bartal ◽  
Baha M. Sibai ◽  
Tali Ben-Mayor Bashi ◽  
Ayelet Dangot ◽  
Irit Schushan Eisen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ct Scan ◽  
Puerperal Fever ◽  
Abdominal Computed Tomography

scholarly journals Polyserositis: An Extremely Rare Life-Threatening Manifestation of Pheochromocytoma

2020 ◽  
Vol 2020 ◽  
pp. 1-3
Author(s):  
Maryam Heidarpour ◽  
Mohammad Ali Haghighatpanah ◽  
Hassan Rezvanian ◽  
Motahare Yadegarfar ◽  
Amir Mohammad Mozafari ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ct Scan ◽  
Cardiac Tamponade ◽  
Adrenal Mass ◽  
Vital Signs ◽  
Abdominal Computed Tomography ◽  
Life Threatening

The pericardium is an uncommon site for manifestation of pheochromocytoma. Herein, the case of a 57-year-old man with cardiac tamponade is presented. Pericardiocentesis was performed, and the vital signs were stabilized afterwards. An abdominal computed tomography (CT) scan illustrated a nonhomogeneous right adrenal mass suspicious of pheochromocytoma, planned for right adrenalectomy. He recovered well after surgery, and his subsequent follow-ups did not reveal any complications.

Tu1294 Can Abdominal Computed Tomography (CT) Scan Predict Fibrosis in Chronic Pancreatitis (CP)? A Radio-Pathologic Analysis

2014 ◽  
Vol 146 (5) ◽  
pp. S-805
Author(s):  
Amitasha Sinha ◽  
Sumera Ali ◽  
Michael Cruise ◽  
Karen Matsukuma ◽  
Siva P. Raman ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Chronic Pancreatitis ◽  
Ct Scan ◽  
Abdominal Computed Tomography ◽  
Pathologic Analysis

Preoperative Abdominal Computed Tomography at Rest and During Valsalva’s Maneuver to Evaluate Incisional Hernias

2019 ◽  
Vol 26 (5) ◽  
pp. 519-527 ◽  
Author(s):  
Gabriele Bellio ◽  
Tommaso Cipolat Mis ◽  
Roberto Del Giudice ◽  
Gabriele Munegato
Keyword(s):  
Computed Tomography ◽  
Ct Scan ◽  
Cohort Analysis ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Abdominal Ct ◽  
Incisional Hernias ◽  
Abdominal Computed Tomography ◽  
Abdominal Ct Scan ◽  
Valsalva’S Maneuver

Background. Incisional hernias (IHs) can develop in up to 15% of patients who underwent an abdominal surgical procedure. Abdominal computed tomography (CT) is the best examination to evaluate these patients before surgical repair. The aim of this study is to assess the usefulness of the abdominal CT scan during Valsalva’s maneuver in patients who are candidates for surgery. Methods. A retrospective cohort analysis conducted on prospectively recorded data was performed on 26 consecutive patients affected by IHs who underwent a preoperative abdominal CT scan both at rest and during Valsalva’s maneuver between January 1, 2015, and December 31, 2016. Results. Five patients (19%) had IH classified as M1-M2, 10 (39%) as M3, and 11 (42%) as M4-M5. Both the median IH orifice area (IHOA) and the median volume of the IH increased during straining ( P = .001 and P < .001, respectively). The percentage of the difference in volume ratios increased as the localization of the IH moved caudally. At the binary logistic regression analysis M3 IH, body mass index >28, IHOA > 156 cm2 at rest, and IHOA > 138 cm2 during Valsalva’s maneuver were risk factors for posterior component separation. Conclusions. The preoperative CT scan both at rest and during Valsalva’s maneuver seemed useful to estimate the risk of difficult IH repairs. Moreover, it could allow surgeons to decide if the patient should be addressed to more specialized centers.

Requesting physicians’ knowledge of X-radiation exposure from computed tomography scan examinations: A case study of two Nigerian tertiary hospitals

2020 ◽  
Vol 3 ◽  
pp. 36-39
Author(s):  
Samson O. Paulinus ◽  
Benjamin E. Udoh ◽  
Bassey E. Archibong ◽  
Akpama E. Egong ◽  
Akwa E. Erim ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ionizing Radiation ◽  
Ct Scan ◽  
Radiation Exposure ◽  
Work Experience ◽  
Radiation Risk ◽  
Radiological Protection ◽  
X Ray ◽  
Tertiary Hospitals ◽  
Medical Exposure

Objective: Physicians who often request for computed tomography (CT) scan examinations are expected to have sound knowledge of radiation exposure (risks) to patients in line with the basic radiation protection principles according to the International Commission on Radiological Protection (ICRP), the Protection of Persons Undergoing Medical Exposure or Treatment (POPUMET), and the Ionizing Radiation (Medical Exposure) Regulations (IR(ME)R). The aim is to assess the level of requesting physicians’ knowledge of ionizing radiation from CT scan examinations in two Nigerian tertiary hospitals. Materials and Methods: An 18-item-based questionnaire was distributed to 141 practicing medical doctors, excluding radiologists with work experience from 0 to >16 years in two major teaching hospitals in Nigeria with a return rate of 69%, using a voluntary sampling technique. Results: The results showed that 25% of the respondents identified CT thorax, abdomen, and pelvis examination as having the highest radiation risk, while 22% said that it was a conventional chest X-ray. Furthermore, 14% concluded that CT head had the highest risk while 9% gave their answer to be conventional abdominal X-ray. In addition, 17% inferred that magnetic resonance imaging had the highest radiation risk while 11% had no idea. Furthermore, 25.5% of the respondents have had training on ionizing radiation from CT scan examinations while 74.5% had no training. Majority (90%) of the respondents were not aware of the ICRP guidelines for requesting investigations with very little (<3%) or no knowledge (0%) on the POPUMET and the IR(ME)R respectively. Conclusion: There is low level of knowledge of ionizing radiation from CT scan examinations among requesting physicians in the study locations.

scholarly journals Predicting the Presence of an Accessory Hepatic Vein Using Abdominal Computed Tomography

2017 ◽  
Vol 35 (1) ◽  
pp. 21-25 ◽  
Author(s):  
Hyung Soo Kim ◽  
Chang Hee Lee ◽  
Seong Hyun Kim ◽  
Jeong Woo Kim ◽  
Cheol Min Park ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Hepatic Vein ◽  
Abdominal Computed Tomography ◽  
Accessory Hepatic Vein

scholarly journals A rare case of right-sided varicocele in right renal tumor in the absence of venous thrombosis and IVC compression

2020 ◽  
Vol 26 (1) ◽  
Author(s):  
Priyabrata Adhikari ◽  
Siddalingeshwar I. Neeli ◽  
Shyam Mohan
Keyword(s):  
Computed Tomography ◽  
Ct Scan ◽  
Renal Vein ◽  
Renal Tumor ◽  
Vena Cava ◽  
Signs And Symptoms ◽  
Spermatic Vein ◽  
Careful Study ◽  
Rare Presentation ◽  
Grade 3

Abstract Background The presence of unilateral right-sided varicocele hints at a serious retroperitoneal disease such as renal cell neoplasm. Such tumors are usually associated with a thrombus in renal vein or spermatic vein. We report a rare presentation of right-sided renal tumor causing right-sided varicocele in the absence of thrombus in renal vein and spermatic vein but due to an anomalous vein draining from the tumor into the spermatic vein as demonstrated by computed tomography angiogram. Case presentation A 54-yr-old hypertensive male presented with unilateral grade 3 right-sided varicocele and no other signs and symptoms. Ultrasound examination of his abdomen showed the presence of a mass lesion in the lower pole of right kidney. Computed tomography confirmed the presence of right renal mass, absence of thrombus in right renal vein or inferior vena cava. The angiographic phase of CT scan showed an anomalous vein from the tumor draining into the pampiniform plexus causing varicocele. Conclusion The presence of right-sided varicocele should raise a suspicion hidden serious pathological retroperitoneal condition, renal malignancy in particular, and should prompt the treating physician to carry out imaging studies of the retroperitoneum and careful study of the angiographic phase of the CT scan can ascertain the pathogenesis of the varicocele.

scholarly journals Deep learning for end-to-end kidney cancer diagnosis on multi-phase abdominal computed tomography

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Kwang-Hyun Uhm ◽  
Seung-Won Jung ◽  
Moon Hyung Choi ◽  
Hong-Kyu Shin ◽  
Jae-Ik Yoo ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Kidney Cancer ◽  
Renal Tumor ◽  
Renal Tumors ◽  
Abdominal Computed Tomography ◽  
Wide Range ◽  
End To End ◽  
Multi Phase ◽  
Histologic Subtypes

AbstractIn 2020, it is estimated that 73,750 kidney cancer cases were diagnosed, and 14,830 people died from cancer in the United States. Preoperative multi-phase abdominal computed tomography (CT) is often used for detecting lesions and classifying histologic subtypes of renal tumor to avoid unnecessary biopsy or surgery. However, there exists inter-observer variability due to subtle differences in the imaging features of tumor subtypes, which makes decisions on treatment challenging. While deep learning has been recently applied to the automated diagnosis of renal tumor, classification of a wide range of subtype classes has not been sufficiently studied yet. In this paper, we propose an end-to-end deep learning model for the differential diagnosis of five major histologic subtypes of renal tumors including both benign and malignant tumors on multi-phase CT. Our model is a unified framework to simultaneously identify lesions and classify subtypes for the diagnosis without manual intervention. We trained and tested the model using CT data from 308 patients who underwent nephrectomy for renal tumors. The model achieved an area under the curve (AUC) of 0.889, and outperformed radiologists for most subtypes. We further validated the model on an independent dataset of 184 patients from The Cancer Imaging Archive (TCIA). The AUC for this dataset was 0.855, and the model performed comparably to the radiologists. These results indicate that our model can achieve similar or better diagnostic performance than radiologists in differentiating a wide range of renal tumors on multi-phase CT.

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