Literature DB >> 29649823

Diagnostic Accuracy of Low and Ultra-Low Dose CT for Identification of Urinary Tract Stones: A Systematic Review.

Flora Rodger, Giles Roditi, Omar M Aboumarzouk.   

Abstract

BACKGROUND: Non-contrast computed tomography of the kidneys, ureters, and bladder (CT KUB) is the investigation of choice for renal colic; however, radiation exposure can be a concern. AIMS: The study aimed to investigate the diagnostic accuracy of low dose (LD) and ultra-low dose (ULD) CT of the urinary tract for detection of urinary tract stones in patients with renal colic.
METHODS: A Cochrane style systematic review of the literature from 1995 to 2017 was carried out. Literature search and data extraction were conducted by 2 reviewers. Specificity and sensitivity values were calculated for LD (<3.5 mean radiation dose [mSv]) and ULD (<1.9 mSv) CT separately.
RESULTS: A total of 12 studies were included following screening. A total of 1,529 patients were included in the review (475 in the LD group and 1,054 in the ULD group). Using standard dose CT KUB as the reference standard, the sensitivity of LD CT KUB ranged from 90 to 98% and specificity from 88 to 100%. The sensitivity of ULD CT KUB ranged from 72 to 99% and the specificity ranged from 86 to 100%. The diagnostic accuracy for LD CT was 94.3% and for ULD CT was 95.5%.
CONCLUSIONS: LD and ULD CT KUB provide effective methods of identifying urinary tract stones. High diagnostic accuracy, sensitivity, and specificity are maintained despite significant radiation dose reduction in comparison to standard dose CT.
© 2018 S. Karger AG, Basel.

Entities:  

Keywords:  Computed tomography; Non-contrasted computed tomography scan of the kidney, ureter, and bladder; Radiation safety; Renal colic; Stones; Urolithiasis

Mesh:

Year:  2018        PMID: 29649823     DOI: 10.1159/000488062

Source DB:  PubMed          Journal:  Urol Int        ISSN: 0042-1138            Impact factor:   2.089


  12 in total

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2.  Detection of urinary tract calculi on CT images reconstructed with deep learning algorithms.

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Review 3.  Indications for abdominal imaging: When and what to choose?

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Journal:  J Ultrason       Date:  2020-03-31

4.  Image quality and pathology assessment in CT Urography: when is the low-dose series sufficient?

Authors:  Bharti Kataria; Jonas Nilsson Althén; Örjan Smedby; Anders Persson; Hannibal Sökjer; Michael Sandborg
Journal:  BMC Med Imaging       Date:  2019-08-09       Impact factor: 1.930

5.  Diagnostic Accuracy of Doppler Twinkling Artifact for Identifying Urinary Tract Calculi.

Authors:  Hatem Adel; Amjad Sattar; Anila Rahim; Anum Aftab; Syed Omair Adil
Journal:  Cureus       Date:  2019-09-13

6.  Effect of obesity on ability to lower exposure for detection of low-attenuation liver lesions.

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Journal:  J Appl Clin Med Phys       Date:  2020-12-28       Impact factor: 2.102

7.  Role of Multi-Detector Computed Tomography Indices in Predicting Extracorporeal Shockwave Lithotripsy Outcome in Patients With Nephrolithiasis.

Authors:  Aashish Singh; Anil K Sakalecha
Journal:  Cureus       Date:  2022-03-01

Review 8.  Dynamic Contrast Enhanced-MR CEST Urography: An Emerging Tool in the Diagnosis and Management of Upper Urinary Tract Obstruction.

Authors:  Shaowei Bo; Farzad Sedaghat; KowsalyaDevi Pavuluri; Steven P Rowe; Andrew Cohen; Max Kates; Michael T McMahon
Journal:  Tomography       Date:  2021-03-02

Review 9.  What are the clinical effects of the different emergency department imaging options for suspected renal colic? A scoping review.

Authors:  Erik Doty; Stephen DiGiacomo; Bridget Gunn; Lauren Westafer; Elizabeth Schoenfeld
Journal:  J Am Coll Emerg Physicians Open       Date:  2021-06-16

10.  Computer-aided diagnosis with a convolutional neural network algorithm for automated detection of urinary tract stones on plain X-ray.

Authors:  Masaki Kobayashi; Junichiro Ishioka; Yoh Matsuoka; Yuichi Fukuda; Yusuke Kohno; Keizo Kawano; Shinji Morimoto; Rie Muta; Motohiro Fujiwara; Naoko Kawamura; Tetsuo Okuno; Soichiro Yoshida; Minato Yokoyama; Rumi Suda; Ryota Saiki; Kenji Suzuki; Itsuo Kumazawa; Yasuhisa Fujii
Journal:  BMC Urol       Date:  2021-08-05       Impact factor: 2.264

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