1. Characterizing Breast Lesions Using Quantitative Parametric 3D Subharmonic Imaging: A Multicenter Study
- Author
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Sridharan, Anush, Eisenbrey, John R, Stanczak, Maria, Machado, Priscilla, Merton, Daniel A, Wilkes, Annina, Sevrukov, Alexander, Ojeda-Fournier, Haydee, Mattrey, Robert F, Wallace, Kirk, and Forsberg, Flemming
- Subjects
screening and diagnosis ,Clinical Sciences ,Doppler ,Contrast Media ,Breast Neoplasms ,Ultrasound contrast agents ,Imaging ,Detection ,Nuclear Medicine & Medical Imaging ,Breast cancer ,Diagnosis ,Differential ,Three-Dimensional ,Breast Cancer ,Humans ,Biomedical Imaging ,Female ,Subharmonic imaging ,Contrast-enhanced ultrasound ,Ultrasonography ,Cancer ,4.2 Evaluation of markers and technologies - Abstract
Rationale and objectivesBreast cancer is the leading type of cancer among women. Visualization and characterization of breast lesions based on vascularity kinetics was evaluated using three-dimensional (3D) contrast-enhanced ultrasound imaging in a clinical study.Materials and methodsBreast lesions (n = 219) were imaged using power Doppler imaging (PDI), 3D contrast-enhanced harmonic imaging (HI), and 3D contrast-enhanced subharmonic imaging (SHI) with a modified Logiq 9 ultrasound scanner using a 4D10L transducer. Quantitative metrics of vascularity derived from 3D parametric volumes (based on contrast perfusion; PER and area under the curve; AUC) were generated by off-line processing of contrast wash-in and wash-out. Diagnostic accuracy of these quantitative vascular parameters was assessed with biopsy results as the reference standard.ResultsVascularity was observed with PDI in 93 lesions (69 benign and 24 malignant), 3D HI in 8 lesions (5 benign and 3 malignant), and 3D SHI in 83 lesions (58 benign and 25 malignant). Diagnostic accuracy for vascular heterogeneity, PER, and AUC ranged from 0.52 to 0.75, while the best logistical regression model (vascular heterogeneity ratio, central PER, and central AUC) reached 0.90.Conclusion3D SHI successfully detects contrast agent flow in breast lesions and characterization of these lesions based on quantitative measures of vascular heterogeneity and 3D parametric volumes is promising.
- Published
- 2020