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Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis.

ABSTRACT: BACKGROUND:Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC). METHODS AND FINDINGS:In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ? 800 s/mm2 were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I2 = 95). CONCLUSIONS:None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.

SUBMITTER: Wielema M

PROVIDER: S-EPMC7202642 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis.

Wielema M M Dorrius M D MD Pijnappel R M RM De Bock G H GH Baltzer P A T PAT Oudkerk M M Sijens P E PE

PloS one 20200506 5

<h4>Background</h4>Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from maligna ...[more]

PMID: 32374781

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Project description:To evaluate the incremental value of diffusion-weighted (DW) imaging and apparent diffusion coefficient (ADC) mapping in relation to conventional breast magnetic resonance (MR) imaging in the characterization of benign versus malignant breast lesions at 3.0 T.This retrospective HIPAA-compliant study was approved by the institutional review board, with the requirement for informed patient consent waived. Of 550 consecutive patients who underwent bilateral breast MR imaging over a 10-month period, 93 women with 101 lesions met the following study inclusion criteria: They had undergone three-dimensional (3D) high-spatial-resolution T1-weighted contrast material-enhanced MR imaging, dynamic contrast-enhanced MR imaging, and DW imaging examinations at 3.0 T and either had received a pathologic analysis-proven diagnosis (96 lesions) or had lesion stability confirmed at more than 2 years of follow-up (five lesions). DW images were acquired with b values of 0 and 600 sec/mm(2). Regions of interest were drawn on ADC maps of breast lesions and normal glandular tissue. Morphologic features (margin, enhancement pattern), dynamic contrast-enhanced MR results (semiquantitative kinetic curve data), absolute ADCs, and glandular tissue-normalized ADCs were included in multivariate models to predict a diagnosis of benign versus malignant lesion.Forty-one (44%) of the 93 patients were premenopausal, and 52 (56%) were postmenopausal. Thirty-three (32.7%) of the 101 lesions were benign, and 68 (67.3%) were malignant. Normalized ADCs were significantly different between the benign (mean ADC, 1.1 x 10(-3) mm(2)/sec +/- 0.4 [standard deviation]) and malignant (mean ADC, 0.55 x 10(-3) mm(2)/sec +/- 0.16) lesions (P < .001). Adding normalized ADCs to the 3D T1-weighted and dynamic contrast-enhanced MR data improved the diagnostic performance of MR imaging: The area under the receiver operating characteristic curve improved from 0.89 to 0.98, and the false-positive rate decreased from 36% (nine of 25 lesions) to 24% (six of 25 lesions).DW imaging with glandular tissue-normalized ADC assessment improves the characterization of breast lesions beyond the characterization achieved with conventional 3D T1-weighted and dynamic contrast-enhanced MR imaging at 3.0 T.

Project description:The European Society of Breast Radiology (EUSOBI) established an International Breast DWI working group. The working group consists of clinical breast MRI experts, MRI physicists, and representatives from large vendors of MRI equipment, invited based upon proven expertise in breast MRI and/or in particular breast DWI, representing 25 sites from 16 countries. The aims of the working group are (a) to promote the use of breast DWI into clinical practice by issuing consensus statements and initiate collaborative research where appropriate; (b) to define necessary standards and provide practical guidance for clinical application of breast DWI; (c) to develop a standardized and translatable multisite multivendor quality assurance protocol, especially for multisite research studies; (d) to find consensus on optimal methods for image processing/analysis, visualization, and interpretation; and (e) to work collaboratively with system vendors to improve breast DWI sequences. First consensus recommendations, presented in this paper, include acquisition parameters for standard breast DWI sequences including specifications of b values, fat saturation, spatial resolution, and repetition and echo times. To describe lesions in an objective way, levels of diffusion restriction/hindrance in the breast have been defined based on the published literature on breast DWI. The use of a small ROI placed on the darkest part of the lesion on the ADC map, avoiding necrotic, noisy or non-enhancing lesion voxels is currently recommended. The working group emphasizes the need for standardization and quality assurance before ADC thresholds are applied. The working group encourages further research in advanced diffusion techniques and tailored DWI strategies for specific indications. Key Points • The working group considers breast DWI an essential part of a multiparametric breast MRI protocol and encourages its use. • Basic requirements for routine clinical application of breast DWI are provided, including recommendations on b values, fat saturation, spatial resolution, and other sequence parameters. • Diffusion levels in breast lesions are defined based on meta-analysis data and methods to obtain a reliable ADC value are detailed.

Project description: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.

Project description:Purpose To assess the repeatability of apparent diffusion coefficient (ADC) estimates in extracranial soft-tissue diffusion-weighted magnetic resonance imaging across a wide range of imaging protocols and patient populations. Materials and Methods Nine prospective patient studies and one prospective volunteer study, performed between 2006 and 2016 with research ethics committee approval and written informed consent from each subject, were included in this single-institution study. A total of 141 tumors and healthy organs were imaged twice (interval between repeated examinations, 45 minutes to 10 days, depending the on study) to assess the repeatability of median and mean ADC estimates. The Levene test was used to determine whether ADC repeatability differed between studies. The Pearson linear correlation coefficient was used to assess correlation between coefficient of variation (CoV) and the year the study started, study size, and volumes of tumors and healthy organs. The repeatability of ADC estimates from small, medium, and large tumors and healthy organs was assessed irrespective of study, and the Levene test was used to determine whether ADC repeatability differed between these groups. Results CoV aggregated across all studies was 4.1% (range for each study, 1.7%-6.5%). No correlation was observed between CoV and the year the study started or study size. CoV was weakly correlated with volume (r = -0.5, P = .1). Repeatability was significantly different between small, medium, and large tumors (P < .05), with the lowest CoV (2.6%) for large tumors. There was a significant difference in repeatability between studies-a difference that did not persist after the study with the largest tumors was excluded. Conclusion ADC is a robust imaging metric with excellent repeatability in extracranial soft tissues across a wide range of tumor sites, sizes, patient populations, and imaging protocol variations. Online supplemental material is available for this article.

Project description:PurposeTo develop a biomimetic tumor tissue phantom which more closely reflects water diffusion in biological tissue than previously used phantoms, and to evaluate the stability of the phantom and its potential as a tool for validating diffusion-weighted (DW) MRI measurements.MethodsCoaxial-electrospraying was used to generate micron-sized hollow polymer spheres, which mimic cells. The bulk structure was immersed in water, providing a DW-MRI phantom whose apparent diffusion coefficient (ADC) and microstructural properties were evaluated over a period of 10 months. Independent characterization of the phantom's microstructure was performed using scanning electron microscopy (SEM). The repeatability of the construction process was investigated by generating a second phantom, which underwent high resolution synchrotron-CT as well as SEM and MR scans.ResultsADC values were stable (coefficients of variation (CoVs) < 5%), and varied with diffusion time, with average values of 1.44 ± 0.03 µm2 /ms (Δ = 12 ms) and 1.20 ± 0.05 µm2 /ms (Δ = 45 ms). Microstructural parameters showed greater variability (CoVs up to 13%), with evidence of bias in sphere size estimates. Similar trends were observed in the second phantom.ConclusionA novel biomimetic phantom has been developed and shown to be stable over 10 months. It is envisaged that such phantoms will be used for further investigation of microstructural models relevant to characterizing tumor tissue, and may also find application in evaluating acquisition protocols and comparing DW-MRI-derived biomarkers obtained from different scanners at different sites. Magn Reson Med 80:147-158, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Dataset Information

Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis.

Publications

Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis.

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