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

BACKGROUND: Thresholding apparent diffusion coefficient (ADC) maps obtained from Diffusion-Weighted-Imaging (DWI) has been proposed for identifying benign lesions that can safely avoid biopsy. The presence of malignancies with high ADC values leads to high thresholds, limiting numbers of avoidable b...

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Autores principales: Penn, Alan, Medved, Milica, Abe, Hiroyuki, Dialani, Vandana, Karczmar, Gregory S., Brousseau, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524062/
https://www.ncbi.nlm.nih.gov/pubmed/36175878
http://dx.doi.org/10.1186/s12880-022-00897-0
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author Penn, Alan
Medved, Milica
Abe, Hiroyuki
Dialani, Vandana
Karczmar, Gregory S.
Brousseau, David
author_facet Penn, Alan
Medved, Milica
Abe, Hiroyuki
Dialani, Vandana
Karczmar, Gregory S.
Brousseau, David
author_sort Penn, Alan
collection PubMed
description BACKGROUND: Thresholding apparent diffusion coefficient (ADC) maps obtained from Diffusion-Weighted-Imaging (DWI) has been proposed for identifying benign lesions that can safely avoid biopsy. The presence of malignancies with high ADC values leads to high thresholds, limiting numbers of avoidable biopsies. PURPOSE: We evaluate two previously reported methods for identifying avoidable biopsies: using case-set dependent ADC thresholds that assure 100% sensitivity and using negative likelihood ratio (LR-) with a fixed ADC threshold of 1.50 × 10(–3) mm(2)/s. We evaluated improvements in efficacy obtained by excluding non-mass lesions and lesions with anisotropic intra-lesion morphologic characteristics. STUDY TYPE: Prospective. POPULATION: 55 adult females with dense breasts with 69 BI-RADS 4 or 5 lesions (38 malignant, 31 benign) identified on ultrasound and mammography and imaged with MRI prior to biopsy. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T. DWI. ASSESSMENT: Analysis of DWI, including directional images was done on an ROI basis. ROIs were drawn on DWI images acquired prior to biopsy, referencing all available images including DCE, and mean ADC was measured. Anisotropy was quantified via variation in ADC values in the lesion core across directional DWI images. STATISTICAL TESTS: Improvement in specificity at 100% sensitivity was evaluated with exact McNemar test with 1-sided p-value < 0.05 indicating statistical significance. RESULTS: Using ADC thresholding that assures 100% sensitivity, non-mass and directional variance filtering improved the percent of avoidable biopsies to 42% from baseline of 10% achieved with ADC thresholding alone. Using LR-, filtering improved outcome to 0.06 from baseline 0.25 with ADC thresholding alone. ADC thresholding showed a lower percentage of avoidable biopsies in our cohort than reported in prior studies. When ADC thresholding was supplemented with filtering, the percentage of avoidable biopsies exceeded those of prior studies. DATA CONCLUSION: Supplementing ADC thresholding with filters excluding non-mass lesions and lesions with anisotropic characteristics on DWI can result in an increased number of avoidable biopsies.
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spelling pubmed-95240622022-10-01 Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding Penn, Alan Medved, Milica Abe, Hiroyuki Dialani, Vandana Karczmar, Gregory S. Brousseau, David BMC Med Imaging Research BACKGROUND: Thresholding apparent diffusion coefficient (ADC) maps obtained from Diffusion-Weighted-Imaging (DWI) has been proposed for identifying benign lesions that can safely avoid biopsy. The presence of malignancies with high ADC values leads to high thresholds, limiting numbers of avoidable biopsies. PURPOSE: We evaluate two previously reported methods for identifying avoidable biopsies: using case-set dependent ADC thresholds that assure 100% sensitivity and using negative likelihood ratio (LR-) with a fixed ADC threshold of 1.50 × 10(–3) mm(2)/s. We evaluated improvements in efficacy obtained by excluding non-mass lesions and lesions with anisotropic intra-lesion morphologic characteristics. STUDY TYPE: Prospective. POPULATION: 55 adult females with dense breasts with 69 BI-RADS 4 or 5 lesions (38 malignant, 31 benign) identified on ultrasound and mammography and imaged with MRI prior to biopsy. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T. DWI. ASSESSMENT: Analysis of DWI, including directional images was done on an ROI basis. ROIs were drawn on DWI images acquired prior to biopsy, referencing all available images including DCE, and mean ADC was measured. Anisotropy was quantified via variation in ADC values in the lesion core across directional DWI images. STATISTICAL TESTS: Improvement in specificity at 100% sensitivity was evaluated with exact McNemar test with 1-sided p-value < 0.05 indicating statistical significance. RESULTS: Using ADC thresholding that assures 100% sensitivity, non-mass and directional variance filtering improved the percent of avoidable biopsies to 42% from baseline of 10% achieved with ADC thresholding alone. Using LR-, filtering improved outcome to 0.06 from baseline 0.25 with ADC thresholding alone. ADC thresholding showed a lower percentage of avoidable biopsies in our cohort than reported in prior studies. When ADC thresholding was supplemented with filtering, the percentage of avoidable biopsies exceeded those of prior studies. DATA CONCLUSION: Supplementing ADC thresholding with filters excluding non-mass lesions and lesions with anisotropic characteristics on DWI can result in an increased number of avoidable biopsies. BioMed Central 2022-09-29 /pmc/articles/PMC9524062/ /pubmed/36175878 http://dx.doi.org/10.1186/s12880-022-00897-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Penn, Alan
Medved, Milica
Abe, Hiroyuki
Dialani, Vandana
Karczmar, Gregory S.
Brousseau, David
Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding
title Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding
title_full Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding
title_fullStr Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding
title_full_unstemmed Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding
title_short Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding
title_sort safely reducing unnecessary benign breast biopsies by applying non-mass and dwi directional variance filters to adc thresholding
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524062/
https://www.ncbi.nlm.nih.gov/pubmed/36175878
http://dx.doi.org/10.1186/s12880-022-00897-0
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