Literature DB >> 31471207

Quantitative Improvement in Brain Tumor MRI Through Structured Reporting (BT-RADS).

James Y Zhang1, Brent D Weinberg2, Ranliang Hu2, Amit Saindane2, Mark Mullins2, Jason Allen2, Michael J Hoch3.   

Abstract

RATIONALE AND
OBJECTIVES: Determine the objective benefits of structured reporting of brain tumors through Brain tumor-RADS (BT-RADS) by analyzing discrete quantifiable metrics of the reports themselves.
MATERIALS AND METHODS: Following Institutional Review Board approval, post-treatment glioma reports were acquired from two matched 3-month time periods for pre- and postimplementation of BT-RADS. The reports were analyzed for presence of history words, such as "Avastin" and "methylguanine-DNA methyltransferase," as well as hedge words, such as "Possibly" and "Likely." The word counts of the total report and of the impression section were also assessed, as well as whether or not the report contained addenda.
RESULTS: In total, 211 pre-BT-RADS and 172 post-BT-RADS reports were analyzed. Post-BT-RADS reports demonstrated greater reporting of history words, including "Avastin" (7.6% vs. 20.9%, p < 0.001) and "methylguanine-DNA methyltransferase" (10.9% vs. 31.4%, p < 0.0001). They also demonstrated reduced usage of hedge words, including "Possibly" (3.8% vs. 0.6%, p < 0.05) and "Likely" (49.8% vs. 28.5%, p < 0.01). Furthermore, post-BT-RADS reports possessed fewer words in total report length (389 vs. 245.2, p < 0.001), as well as in the impression section (53.7 vs. 42.6, p < 0.01). Finally, fewer post-BT-RADS reports contained addenda (10% vs. 1.2%, p < 0.01).
CONCLUSION: Following implementation of BT-RADS, glioma reports demonstrated greater consistency and completeness of clinical history, less ambiguity, and more conciseness.
Copyright © 2019 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Evidence-based Medicine; Gliomas; Quality Improvement; Structured Template; Value-based Care

Year:  2019        PMID: 31471207     DOI: 10.1016/j.acra.2019.07.028

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  5 in total

Review 1.  Overview of Noninterpretive Artificial Intelligence Models for Safety, Quality, Workflow, and Education Applications in Radiology Practice.

Authors:  Yasasvi Tadavarthi; Valeria Makeeva; William Wagstaff; Henry Zhan; Anna Podlasek; Neil Bhatia; Marta Heilbrun; Elizabeth Krupinski; Nabile Safdar; Imon Banerjee; Judy Gichoya; Hari Trivedi
Journal:  Radiol Artif Intell       Date:  2022-02-02

2.  Clinical Routine and Necessary Advances in Soft Tissue Tumor Imaging Based on the ESSR Guideline: Initial Findings.

Authors:  Alexander Korthaus; Sebastian Weiss; Alexej Barg; Johannes Salamon; Carsten Schlickewei; Karl-Heinz Frosch; Matthias Priemel
Journal:  Tomography       Date:  2022-06-17

3.  Adding DSC PWI and DWI to BT-RADS can help identify postoperative recurrence in patients with high-grade gliomas.

Authors:  Yuelong Yang; Yunjun Yang; Xiaoling Wu; Yi Pan; Dong Zhou; Hongdan Zhang; Yonglu Chen; Jiayun Zhao; Zihua Mo; Biao Huang
Journal:  J Neurooncol       Date:  2020-01-04       Impact factor: 4.130

4.  [MRI reporting of gliomas : What neuro-oncology clinicians expect from radiologists].

Authors:  Torge Huckhagel; Christian Riedel
Journal:  Radiologie (Heidelb)       Date:  2022-05-25

5.  The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients.

Authors:  Karthik Ramesh; Saumya S Gurbani; Eric A Mellon; Vicki Huang; Mohammed Goryawala; Peter B Barker; Lawrence Kleinberg; Hui-Kuo G Shu; Hyunsuk Shim; Brent D Weinberg
Journal:  Tomography       Date:  2020-06
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.