Lesion Composition and Quantitative Imaging Analysis on Breast Cancer Diagnosis

Study Overview
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Brief Summary
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The objective is to better identify suspicious breast lesions that need to be biopsied for malignancy in women currently recommended for biopsy. The long-term goal is to reduce unnecessary biopsies and increase biopsy yield. To do this, the investigators have developed an innovative way to use FDA-approved breast imaging protocols to acquire multispectral images to measure the composition of suspicious breast lesions. The central hypothesis is that breast tissue composition in combination with analysis of morphological and textural tissue characteristics on digital breast tomosynthesis (DBT) imaging will yield significantly higher breast cancer specificity than conventional interpretation of DBT alone.

Detailed Description
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Women with dense breast have not been shown to benefit by increased cancer detection of volumetric digital breast tomosynthesis (DBT) but may benefit by lower recall rates. DBT screening biopsy rates are similar to 2D digital mammography; higher for first screening exams, lower thereafter with adjustment for age and breast density. In the U.S., 71% of biopsies do not result in a breast cancer diagnosis among women ages 40-79 who undergo breast cancer screening. To address the high rate of unnecessary biopsies, an innovative way to use FDA-approved breast imaging protocols has been developed to acquire multispectral images to measure the lipid/water/protein (L/W/P) composition of suspicious breast lesions. Malignant breast tissue has unique L/W/P composition fractions when compared to normal or benign breast tissue. This proposal aims to increase biopsy yield (BI-RADS-PPV3) through combining L/W/P biological biomarkers with quantitative morphological and textural image analysis. This combination of composition and physical descriptions of suspicious breast lesions is called q3CB. The benefits of adding q3CB to the current DBT screening/diagnostic imaging paradigm, that may already include computer aided detection, is not known. This study is designed to compare the expected biopsy yield with and without q3CB in a clinical reader study and explore how q3CB may be combine with existing technologies. The central hypothesis is that biological L/W/P fractions in breast tissue in combination with analysis of morphological and textural tissue characteristics will yield significantly higher breast cancer specificity than conventional interpretation of DBT alone. The objective is to better identify suspicious breast lesions that need to be biopsied for malignancy in women currently recommended for biopsy. The long-term goal is to reduce unnecessary biopsies and increase biopsy yield. The investigators rationale for the proposed research is that biological L/W/P descriptions of breast lesions will lead to more specific biopsy decisions and a better understanding of cancer types. Specifically, the project aims are 1) develop q3CB lesion signatures for distinguishing breast cancer lesions from benign lesions, using 600 prospectively-acquired DBT exams of women recommended to undergo biopsy; 2) conduct a clinical reader study to compare radiologists' performance on standard-of-care FFDM or DBT without and with the inclusion of q3CB signatures; 3) Investigate the utility of q3CB lesion signatures in a screening paradigm to improve sensitivity and specificity on CADe-identified suspicious lesions in the tasks of assessing malignancy as well as in associating with their association with cancer subtypes; Exploratory) explore the added sensitivity and specificity of dual-energy DBT in phantom studies that explore lesion size, composition, and breast density. The innovation of this study is the full characterization of lipid/water/protein lesion composition with DBT and how it complements existing computer aided diagnostic programs paired with clinical radiologists providing evidence ready for clinical translation of this unique and emerging technology.

Official Title
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Lesion Composition and Quantitative Imaging Analysis on Breast Cancer Diagnosis

Conditions
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Breast Cancer

Intervention / Treatment
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* Diagnostic Test: q3CB


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Had a recent diagnostic mammogram with a BI-RADS diagnostic score 4 or 5 assigned by a radiologist (BIRADS are standardized mammography assessment categories: 4 is for Suspicious abnormality, 5 is for Highly suggestive of malignancy. Have not had biopsy Exclusion Criteria: Pregnant or breast feeding History of breast cancer or a mastectomy (removal of the breast) with Systemic Therapy (ex. Chemotherapy, hormones and hormone inhibitors, etc.).

Ages Eligible for Study
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Minimum Age: 20 Years
Maximum Age: 85 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Diagnostic Test: q3CB|The q3CB/ncCEM/DBT acquisition protocol consists of a combination of DBT volume reconstructions and projection dual-energy mammograms acquired with a clinical contrast enhanced mammography (CEM) protocol, without contrast administration agent.|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Quantify biological composition of lesions | Quantify the biological composition (lipid/water/protein) of suspicious lesions. | Baseline | 
| Quantify morphology of lesions | Quantify morphology/texture (radiomics) of suspicious lesions. | Baseline | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Comparison of radiologists' image interpretations with and without q3CB signatures | Difference in AUC between the 1st read and 2nd read image interpretations. In the 1st read, they will be provided with the FFDM/DBT images and in the 2nd read, they will also be provided with the ncCEM q3CB composition and radiomics signature (likelihood of malignancy). | Baseline | 
| Sensitivity and Specificity of readers' responses for the BI-RADs assessment categories | Sensitivity and specificity values will be calculated: a BI-RADS assessment of 4a or higher (i.e., 4a, 4b, 4c, and 5) defined a positive call for cancer diagnosis and, conversely, a BI-RADS assessment of 3 or lower (i.e., 3, 2, and 1) defined a negative call for cancer diagnosis. | Baseline |