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Lee M, Nguyen B, Jung J, Razzak E, Oluyemi ET, McDonald ES, Miles RC, Sadigh G, Carlos RC. Assessing the Correlation between Allostatic Load and False-Positive Image-Guided Breast Biopsies. J Womens Health (Larchmt) 2024. [PMID: 38973695 DOI: 10.1089/jwh.2024.0039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2024] Open
Abstract
Background: Allostatic load (AL) is the accumulation of physiological dysregulation attributed to repeated activation of the stress response over a lifetime. We assessed the utility of AL as a prognostic measure for high-risk benign breast biopsy pathology results. Method: Eligible patients were women 18 years or older, with a false-positive outpatient breast biopsy between January and December 2022 at a tertiary academic health center. AL was calculated using 12 variables representing four physiological systems: cardiovascular (pulse rate, systolic and diastolic blood pressures, total cholesterol, high-density lipoprotein, and low-density lipoprotein); metabolic (body mass index, albumin, and hemoglobin A1C); renal (creatinine and estimated glomerular filtration rate); and immune (white blood cell count). Multivariable logistic regression was used to assess the association between AL before biopsy and breast biopsy outcomes controlling for patients' sociodemographics. Results: In total, 170 women were included (mean age, 54.1 ± 12.9 years): 89.4% had benign and 10.6% had high-risk pathologies (radial scar/complex sclerosing lesion, atypical ductal or lobular hyperplasia, flat epithelial atypia, intraductal papilloma, or lobular carcinoma in-situ). A total of 56.5% were White, 24.7% Asian, and 17.1% other races. A total of 32.5% identified as Hispanic. The mean breast cancer risk score using the Tyrer-Cuzick model was 11.9 ± 7.0. In multivariable analysis, with every one unit increase in AL, the probability of high-risk pathology increased by 37% (odds ratio, 1.37; 95% confidence interval, 1.03, 1.81; p = 0.03). No significant association was seen between high-risk pathology and age, ethnicity, breast cancer risk, or area deprivation index. Conclusion: Our findings support that increased AL, a biological marker of stress, is associated with high-risk pathology among patients with false-positive breast biopsy results.
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Affiliation(s)
- Maxwell Lee
- Department of Radiological Sciences, University of California, Irvine, CA, USA
| | - Britney Nguyen
- Department of Radiological Sciences, University of California, Irvine, CA, USA
| | - Jinho Jung
- Department of Radiological Sciences, University of California, Irvine, CA, USA
| | - Eisa Razzak
- Loyola University Stritch School of Medicine, Chicago, Illinois, USA
| | - Eniola T Oluyemi
- Department of Radiology, John Hopkins University, Baltimore, MD, USA
| | | | - Randy C Miles
- Department of Radiology, Denver Health, Denver, CO, USA
| | - Gelareh Sadigh
- Department of Radiological Sciences, University of California, Irvine, CA, USA
| | - Ruth C Carlos
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
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Horvat JV. High-Risk Lesion Management. Semin Ultrasound CT MR 2023; 44:46-55. [PMID: 36792273 DOI: 10.1053/j.sult.2022.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
High-risk lesions or lesions of uncertain malignant potential are frequent findings on image-guided needle biopsy of the breast and comprise a number of distinct entities. These lesions are known for having risk of underlying malignancy and are usually associated with an increased lifetime risk for breast cancer. Surgical excision was traditionally recommended for all high-risk lesions but recent studies have demonstrated that vacuum-assisted excision or surveillance may be adequate for some lesions. While management of high-risk lesion varies among institutions, this chapter describes the management recommendations based on recent literature of the most frequent types of lesions.
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Affiliation(s)
- Joao V Horvat
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY.
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Nicosia L, Latronico A, Addante F, De Santis R, Bozzini AC, Montesano M, Frassoni S, Bagnardi V, Mazzarol G, Pala O, Lazzeroni M, Lissidini G, Mastropasqua MG, Cassano E. Atypical Ductal Hyperplasia after Vacuum-Assisted Breast Biopsy: Can We Reduce the Upgrade to Breast Cancer to an Acceptable Rate? Diagnostics (Basel) 2021; 11:diagnostics11061120. [PMID: 34205428 PMCID: PMC8259513 DOI: 10.3390/diagnostics11061120] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 12/02/2022] Open
Abstract
(1) Background: to evaluate which factors can reduce the upgrade rate of atypical ductal hyperplasia (ADH) to in situ or invasive carcinoma in patients who underwent vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. (2) Methods: 2955 VABBs were reviewed; 141 patients with a diagnosis of ADH were selected for subsequent surgical excision. The association between patients’ characteristics and the upgrade rate to breast cancer was evaluated in both univariate and multivariate analyses. (3) Results: the upgrade rates to ductal carcinoma in situ (DCIS) and invasive carcinoma (IC) were, respectively, 29.1% and 7.8%. The pooled upgrade rate to DCIS or IC was statistically lower at univariate analysis, considering the following parameters: complete removal of the lesion (p-value < 0.001); BIRADS ≤ 4a (p-value < 0.001); size of the lesion ≤15 mm (p-value: 0.002); age of the patients <50 years (p-value: 0.035). (4) Conclusions: the overall upgrade rate of ADH to DCIS or IC is high and, as already known, surgery should be recommended. However, ADH cases should always be discussed in multidisciplinary meetings: some parameters appear to be related to a lower upgrade rate. Patients presenting these parameters could be strictly followed up to avoid overtreatment.
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Affiliation(s)
- Luca Nicosia
- Department of Breast Radiology, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy; (L.N.); (A.L.); (A.C.B.); (M.M.); (E.C.)
| | - Antuono Latronico
- Department of Breast Radiology, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy; (L.N.); (A.L.); (A.C.B.); (M.M.); (E.C.)
| | - Francesca Addante
- Department of Emergency and Organ Transplantation, Section of Anatomic Pathology, School of Medicine, University “Aldo Moro”, 70124 Bari, Italy;
| | - Rossella De Santis
- Postgraduate School in Radiology, University of Milan, 20122 Milan, Italy;
| | - Anna Carla Bozzini
- Department of Breast Radiology, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy; (L.N.); (A.L.); (A.C.B.); (M.M.); (E.C.)
| | - Marta Montesano
- Department of Breast Radiology, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy; (L.N.); (A.L.); (A.C.B.); (M.M.); (E.C.)
| | - Samuele Frassoni
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy; (S.F.); (V.B.)
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy; (S.F.); (V.B.)
| | - Giovanni Mazzarol
- Division of Pathology and Laboratory Medicine, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy; (G.M.); (O.P.)
| | - Oriana Pala
- Division of Pathology and Laboratory Medicine, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy; (G.M.); (O.P.)
| | - Matteo Lazzeroni
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy;
| | - Germana Lissidini
- Division of Breast Surgery, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy;
| | - Mauro Giuseppe Mastropasqua
- Department of Emergency and Organ Transplantation, Section of Anatomic Pathology, School of Medicine, University “Aldo Moro”, 70124 Bari, Italy;
- Correspondence: ; Tel.: +39-0805594414
| | - Enrico Cassano
- Department of Breast Radiology, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy; (L.N.); (A.L.); (A.C.B.); (M.M.); (E.C.)
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4
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Zheng C, Jia HY, Liu LY, Wang Q, Jiang HC, Teng LS, Geng CZ, Jin F, Tang LL, Zhang JG, Wang X, Wang S, Alejandro FE, Wang F, Yu LX, Zhou F, Xiang YJ, Huang SY, Fu QY, Zhang Q, Gao DZ, Ma ZB, Li L, Fan ZM, Yu ZG. Molecular fingerprint of precancerous lesions in breast atypical hyperplasia. J Int Med Res 2021; 48:300060520931616. [PMID: 32589079 PMCID: PMC7325464 DOI: 10.1177/0300060520931616] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE To identify atypical hyperplasia (AH) of the breast by shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS), and to explore the molecular fingerprinting characteristics of breast AH. METHODS Breast hyperplasia was studied in 11 hospitals across China from January 2015 to December 2016. All patients completed questionnaires on women's health. The differences between patients with and without breast AH were compared. AH breast lesions were detected by Raman spectroscopy followed by the SHINERS technique. RESULTS There were no significant differences in clinical features and risk-related factors between patients with breast AH (n = 37) and the control group (n = 2576). Fifteen cases of breast AH lesions were detected by Raman spectroscopy. The main different Raman peaks in patients with AH appeared at 880, 1001, 1086, 1156, 1260, and 1610 cm-1, attributed to the different vibrational modes of nucleic acids, β-carotene, and proteins. Shell-isolated nanoparticles had different enhancement effects on the nucleic acid, protein, and lipid components in AH. CONCLUSION Raman spectroscopy can detect characteristic molecular changes in breast AH lesions, and may thus be useful for the non-invasive early diagnosis and for investigating the mechanism of tumorigenesis in patients with breast AH.
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Affiliation(s)
- Chao Zheng
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Hong Ying Jia
- Center of Evidence-based Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Li Yuan Liu
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qi Wang
- Breast Disease Center, Guangdong Maternal and Child Health Care Hospital, Guangzhou, Guangdong, China
| | - Hong Chuan Jiang
- Department of General Surgery, Beijing Chaoyang Hospital, Beijing, China
| | - Li Song Teng
- Department of Oncology Surgery, The First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China
| | - Cui Zhi Geng
- Breast Center, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Feng Jin
- Department of Breast Surgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Li Li Tang
- Department of Breast Surgery, Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jian Guo Zhang
- Department of General Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Xiang Wang
- Department of Breast Surgery, Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Shu Wang
- Breast Disease Center, Peking University People's Hospital, Beijing, China
| | | | - Fei Wang
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Li Xiang Yu
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Fei Zhou
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yu Juan Xiang
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Shu Ya Huang
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qin Ye Fu
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qiang Zhang
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - De Zong Gao
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Zhong Bing Ma
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Liang Li
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Zhi Min Fan
- Department of Breast Surgery, the First Hospital of Jilin University, Changchun, Jilin, China
| | - Zhi Gang Yu
- Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
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Polat DS, Schopp JG, Arjmandi F, Porembka J, Sarode V, Farr D, Xi Y, Dogan BE. Performance of a clinical and imaging-based multivariate model as decision support tool to help save unnecessary surgeries for high-risk breast lesions. Breast Cancer Res Treat 2020; 185:479-494. [PMID: 33010022 DOI: 10.1007/s10549-020-05947-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 09/21/2020] [Indexed: 11/26/2022]
Abstract
PURPOSE To investigate the performance of an imaging and biopsy parameters-based multivariate model in decreasing unnecessary surgeries for high-risk breast lesions. METHODS In an IRB-approved study, we retrospectively reviewed all high-risk lesions (HRL) identified at imaging-guided biopsy in our institution between July 1, 2014-July 1, 2017. Lesions were categorized high-risk-I (HR-I = atypical ductal hyperplasia, atypical lobular hyperplasia, lobular carcinoma in situ and atypical papillary lesion) and II (HR-II = Flat epithelial atypia, radial scar, benign papilloma). Patient risk factors, lesion features, detection and biopsy modality, excision and cancer upgrade rates were collected. Reference standard for upgrade was either excision or at least 2-year imaging follow-up. Multiple logistic regression analysis was performed to develop a multivariate model using HRL type, lesion and biopsy needle size for surgical cancer upgrade with performance assessed using ROC analysis. RESULTS Of 699 HRL in 652 patients, 525(75%) had reference standard available, and 48/525(9.1%) showed cancer at surgical excision. Excision (84.5% vs 51.1%) and upgrade (17.6%vs1.8%) rates were higher in HR-I compared to HR-II (p < 0.01). In HR-I, small needle size < 12G vs ≥ 12G [32.1% vs 13.2%, p < 0.01] and less cores [< 6 vs ≥ 6, 28.6%vs13.7%, p = 0.01] were significantly associated with higher cancer upgrades. Our multivariate model had an AUC = 0.87, saving 28.1% of benign surgeries with 100% sensitivity, based on HRL subtype, lesion size(mm, continuous), needle size (< 12G vs ≥ 12G) and biopsy modality (US vs MRI vs stereotactic) CONCLUSION: Our multivariate model using lesion size, needle size and patient age had a high diagnostic performance in decreasing unnecessary surgeries and shows promise as a decision support tool.
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Affiliation(s)
- Dogan S Polat
- Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Jennifer G Schopp
- Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Firouzeh Arjmandi
- Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jessica Porembka
- Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Venetia Sarode
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Deborah Farr
- Department of Surgery, Surgical Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yin Xi
- Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Basak E Dogan
- Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
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6
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Abstract
Pathologists are adopting whole slide images (WSIs) for diagnosis, thanks to recent FDA approval of WSI systems as class II medical devices. In response to new market forces and recent technology advances outside of pathology, a new field of computational pathology has emerged that applies artificial intelligence (AI) and machine learning algorithms to WSIs. Computational pathology has great potential for augmenting pathologists' accuracy and efficiency, but there are important concerns regarding trust of AI due to the opaque, black-box nature of most AI algorithms. In addition, there is a lack of consensus on how pathologists should incorporate computational pathology systems into their workflow. To address these concerns, building computational pathology systems with explainable AI (xAI) mechanisms is a powerful and transparent alternative to black-box AI models. xAI can reveal underlying causes for its decisions; this is intended to promote safety and reliability of AI for critical tasks such as pathology diagnosis. This article outlines xAI enabled applications in anatomic pathology workflow that improves efficiency and accuracy of the practice. In addition, we describe HistoMapr-Breast, an initial xAI enabled software application for breast core biopsies. HistoMapr-Breast automatically previews breast core WSIs and recognizes the regions of interest to rapidly present the key diagnostic areas in an interactive and explainable manner. We anticipate xAI will ultimately serve pathologists as an interactive computational guide for computer-assisted primary diagnosis.
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Shaffer K. Can Machine Learning Be Used to Generate a Model to Improve Management of High-Risk Breast Lesions? Radiology 2018; 286:819-821. [PMID: 29461953 DOI: 10.1148/radiol.2017172648] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Kitt Shaffer
- From the Department of Radiology, Boston Medical Center, 1 Boston Medical Center Pl, Newton Pavilion, Room 2503, Boston, MA 02118
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Thomassin-Piana J, Jalaguier-Coudray A, Cohen M, Houvenaeghel G, Charafe-Jauffret E, Paciencia-Gros M, Dauplat MM, Thomassin-Naggara I. Lésions histologiques mammaires à risque : classification actuelle et prise en charge. IMAGERIE DE LA FEMME 2017. [DOI: 10.1016/j.femme.2017.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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