Literature DB >> 33201788

Mean Apparent Diffusion Coefficient Is a Sufficient Conventional Diffusion-weighted MRI Metric to Improve Breast MRI Diagnostic Performance: Results from the ECOG-ACRIN Cancer Research Group A6702 Diffusion Imaging Trial.

Elizabeth S McDonald1, Justin Romanoff1, Habib Rahbar1, Averi E Kitsch1, Sara M Harvey1, Jennifer G Whisenant1, Thomas E Yankeelov1, Linda Moy1, Wendy B DeMartini1, Basak E Dogan1, Wei T Yang1, Lilian C Wang1, Bonnie N Joe1, Lisa J Wilmes1, Nola M Hylton1, Karen Y Oh1, Luminita A Tudorica1, Colleen H Neal1, Dariya I Malyarenko1, Christopher E Comstock1, Mitchell D Schnall1, Thomas L Chenevert1, Savannah C Partridge1.   

Abstract

Background The Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 multicenter trial helped confirm the potential of diffusion-weighted MRI for improving differential diagnosis of suspicious breast abnormalities and reducing unnecessary biopsies. A prespecified secondary objective was to explore the relative value of different approaches for quantitative assessment of lesions at diffusion-weighted MRI. Purpose To determine whether alternate calculations of apparent diffusion coefficient (ADC) can help further improve diagnostic performance versus mean ADC values alone for analysis of suspicious breast lesions at MRI. Materials and Methods This prospective trial (ClinicalTrials.gov identifier: NCT02022579) enrolled consecutive women (from March 2014 to April 2015) with a Breast Imaging Reporting and Data System category of 3, 4, or 5 at breast MRI. All study participants underwent standardized diffusion-weighted MRI (b = 0, 100, 600, and 800 sec/mm2). Centralized ADC measures were performed, including manually drawn whole-lesion and hotspot regions of interest, histogram metrics, normalized ADC, and variable b-value combinations. Diagnostic performance was estimated by using the area under the receiver operating characteristic curve (AUC). Reduction in biopsy rate (maintaining 100% sensitivity) was estimated according to thresholds for each ADC metric. Results Among 107 enrolled women, 81 lesions with outcomes (28 malignant and 53 benign) in 67 women (median age, 49 years; interquartile range, 41-60 years) were analyzed. Among ADC metrics tested, none improved diagnostic performance versus standard mean ADC (AUC, 0.59-0.79 vs AUC, 0.75; P = .02-.84), and maximum ADC had worse performance (AUC, 0.52; P < .001). The 25th-percentile ADC metric provided the best performance (AUC, 0.79; 95% CI: 0.70, 0.88), and a threshold using median ADC provided the greatest reduction in biopsy rate of 23.9% (95% CI: 14.8, 32.9; 16 of 67 BI-RADS category 4 and 5 lesions). Nonzero minimum b value (100, 600, and 800 sec/mm2) did not improve the AUC (0.74; P = .28), and several combinations of two b values (0 and 600, 100 and 600, 0 and 800, and 100 and 800 sec/mm2; AUC, 0.73-0.76) provided results similar to those seen with calculations of four b values (AUC, 0.75; P = .17-.87). Conclusion Mean apparent diffusion coefficient calculated with a two-b-value acquisition is a simple and sufficient diffusion-weighted MRI metric to augment diagnostic performance of breast MRI compared with more complex approaches to apparent diffusion coefficient measurement. © RSNA, 2020 Online supplemental material is available for this article.

Entities:  

Mesh:

Year:  2020        PMID: 33201788      PMCID: PMC7771995          DOI: 10.1148/radiol.2020202465

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  31 in total

1.  Breast MRI: State of the Art.

Authors:  Ritse M Mann; Nariya Cho; Linda Moy
Journal:  Radiology       Date:  2019-07-30       Impact factor: 11.105

2.  Assessment of breast lesions with diffusion-weighted MRI: comparing the use of different b values.

Authors:  Fernanda Philadelpho Arantes Pereira; Gabriela Martins; Eduardo Figueiredo; Marisa Nassar Aidar Domingues; Romeu Cortes Domingues; Lea Mirian Barbosa da Fonseca; Emerson Leandro Gasparetto
Journal:  AJR Am J Roentgenol       Date:  2009-10       Impact factor: 3.959

Review 3.  Effect of b value and pre-admission of contrast on diagnostic accuracy of 1.5-T breast DWI: a systematic review and meta-analysis.

Authors:  Monique D Dorrius; Hildebrand Dijkstra; Matthijs Oudkerk; Paul E Sijens
Journal:  Eur Radiol       Date:  2014-08-09       Impact factor: 5.315

4.  Supplemental MRI Screening for Women with Extremely Dense Breast Tissue.

Authors:  Marije F Bakker; Stéphanie V de Lange; Ruud M Pijnappel; Ritse M Mann; Petra H M Peeters; Evelyn M Monninkhof; Marleen J Emaus; Claudette E Loo; Robertus H C Bisschops; Marc B I Lobbes; Matthijn D F de Jong; Katya M Duvivier; Jeroen Veltman; Nico Karssemeijer; Harry J de Koning; Paul J van Diest; Willem P T M Mali; Maurice A A J van den Bosch; Wouter B Veldhuis; Carla H van Gils
Journal:  N Engl J Med       Date:  2019-11-28       Impact factor: 91.245

5.  ADC mapping of benign and malignant breast tumors.

Authors:  Reiko Woodhams; Keiji Matsunaga; Shinichi Kan; Hirofumi Hata; Masanori Ozaki; Keiichi Iwabuchi; Masaru Kuranami; Masahiko Watanabe; Kazushige Hayakawa
Journal:  Magn Reson Med Sci       Date:  2005       Impact factor: 2.471

6.  Diffusion-Weighted Breast Magnetic Resonance Imaging: A Semiautomated Voxel Selection Technique Improves Interreader Reproducibility of Apparent Diffusion Coefficient Measurements.

Authors:  Habib Rahbar; Brenda F Kurland; Matthew L Olson; Averi E Kitsch; John R Scheel; Xiaoyu Chai; Joshua Usoro; Constance D Lehman; Savannah C Partridge
Journal:  J Comput Assist Tomogr       Date:  2016 May-Jun       Impact factor: 1.826

7.  Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging.

Authors:  Yong Guo; You-Quan Cai; Zu-Long Cai; Yuan-Gui Gao; Ning-Yu An; Lin Ma; Srikanth Mahankali; Jia-Hong Gao
Journal:  J Magn Reson Imaging       Date:  2002-08       Impact factor: 4.813

8.  The role of diffusion-weighted imaging and the apparent diffusion coefficient (ADC) values for breast tumors.

Authors:  Mi Jung Park; Eun Suk Cha; Bong Joo Kang; Yon Kwon Ihn; Jun Hyun Baik
Journal:  Korean J Radiol       Date:  2007 Sep-Oct       Impact factor: 3.500

9.  Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions.

Authors:  Xin Chen; Wen-ling Li; Yi-li Zhang; Qian Wu; You-min Guo; Zhi-lan Bai
Journal:  BMC Cancer       Date:  2010-12-29       Impact factor: 4.430

10.  Estimation of diffusion, perfusion and fractional volumes using a multi-compartment relaxation-compensated intravoxel incoherent motion (IVIM) signal model.

Authors:  Anna Rydhög; Ofer Pasternak; Freddy Ståhlberg; André Ahlgren; Linda Knutsson; Ronnie Wirestam
Journal:  Eur J Radiol Open       Date:  2019-05-24
View more
  10 in total

Review 1.  Challenges in ensuring the generalizability of image quantitation methods for MRI.

Authors:  Kathryn E Keenan; Jana G Delfino; Kalina V Jordanova; Megan E Poorman; Prathyush Chirra; Akshay S Chaudhari; Bettina Baessler; Jessica Winfield; Satish E Viswanath; Nandita M deSouza
Journal:  Med Phys       Date:  2021-09-29       Impact factor: 4.506

2.  Factors Affecting Image Quality and Lesion Evaluability in Breast Diffusion-weighted MRI: Observations from the ECOG-ACRIN Cancer Research Group Multisite Trial (A6702).

Authors:  Jennifer G Whisenant; Justin Romanoff; Habib Rahbar; Averi E Kitsch; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak E Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Lisa J Wilmes; Nola M Hylton; Karen Y Oh; Luminita A Tudorica; Colleen H Neal; Dariya I Malyarenko; Elizabeth S McDonald; Christopher E Comstock; Thomas E Yankeelov; Thomas L Chenevert; Savannah C Partridge
Journal:  J Breast Imaging       Date:  2020-12-24

3.  Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial.

Authors:  Savannah C Partridge; Jon Steingrimsson; David C Newitt; Jessica E Gibbs; Helga S Marques; Patrick J Bolan; Michael A Boss; Thomas L Chenevert; Mark A Rosen; Nola M Hylton
Journal:  Tomography       Date:  2022-03-04

4.  Breast Lesion Classification with Multiparametric Breast MRI Using Radiomics and Machine Learning: A Comparison with Radiologists' Performance.

Authors:  Isaac Daimiel Naranjo; Peter Gibbs; Jeffrey S Reiner; Roberto Lo Gullo; Sunitha B Thakur; Maxine S Jochelson; Nikita Thakur; Pascal A T Baltzer; Thomas H Helbich; Katja Pinker
Journal:  Cancers (Basel)       Date:  2022-03-29       Impact factor: 6.575

5.  Implementation of Whole-Body MRI (MY-RADS) within the OPTIMUM/MUKnine multi-centre clinical trial for patients with myeloma.

Authors:  Mihaela Rata; Matthew Blackledge; Erica Scurr; Jessica Winfield; Dow-Mu Koh; Alina Dragan; Antonio Candito; Alexander King; Winston Rennie; Suchi Gaba; Priya Suresh; Paul Malcolm; Amy Davis; Anjumara Nilak; Aarti Shah; Sanjay Gandhi; Mauro Albrizio; Arnold Drury; Sadie Roberts; Matthew Jenner; Sarah Brown; Martin Kaiser; Christina Messiou
Journal:  Insights Imaging       Date:  2022-07-28

6.  Tri-Compartmental Restriction Spectrum Imaging Breast Model Distinguishes Malignant Lesions from Benign Lesions and Healthy Tissue on Diffusion-Weighted Imaging.

Authors:  Alexandra H Besser; Lauren K Fang; Michelle W Tong; Maren M Sjaastad Andreassen; Haydee Ojeda-Fournier; Christopher C Conlin; Stéphane Loubrie; Tyler M Seibert; Michael E Hahn; Joshua M Kuperman; Anne M Wallace; Anders M Dale; Ana E Rodríguez-Soto; Rebecca A Rakow-Penner
Journal:  Cancers (Basel)       Date:  2022-06-30       Impact factor: 6.575

7.  Correlations between dynamic-enhanced magnetic resonance imaging quantitative parameters and postoperative recurrence or metastasis and clinicopathological features in breast cancer patients-a retrospective cohort study.

Authors:  Xuelian Chen; Qian Gao; Zhijuan Wu; Hongyan Wang; Jianliang Wang
Journal:  Gland Surg       Date:  2022-08

8.  Image quality and whole-lesion histogram and texture analysis of diffusion-weighted imaging of breast MRI based on advanced ZOOMit and simultaneous multislice readout-segmented echo-planar imaging.

Authors:  Kun Sun; Hong Zhu; Bingqing Xia; Xinyue Li; Weimin Chai; Caixia Fu; Benkert Thomas; Wei Liu; Robert Grimm; Weiland Elisabeth; Fuhua Yan
Journal:  Front Oncol       Date:  2022-08-12       Impact factor: 5.738

9.  Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding.

Authors:  Alan Penn; Milica Medved; Hiroyuki Abe; Vandana Dialani; Gregory S Karczmar; David Brousseau
Journal:  BMC Med Imaging       Date:  2022-09-29       Impact factor: 2.795

10.  Differentiating benign from malignant gallbladder wall thickening in non-contrast MRI imaging: Preliminary study of a combined diagnostic indicator.

Authors:  Wen-Wen He; Jian-Guo Zhu; Dmytro Pylypenko; Fei Liu; Mei Wang; Yue-Fei Wu; Jun Tian; Hai-Ge Li
Journal:  Medicine (Baltimore)       Date:  2022-10-07       Impact factor: 1.817

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.