ABSTRACT
Objective@#To assess the value of multi-parametric MRI in mammographically detected breast imaging reporting and data systems (BI-RADS) 3 to 4 exclusive microcalcifications.@*Methods@#A retrospective analysis was performed in 152 patients with mammographically detected BI-RADS 3 to 4 exclusive microcalcifications from January 2013 to December 2017. All patients underwent bilateral breast multi-parametric MRI before surgical biopsy. Microcalcifications were classified according to BI-RADS by two radiologists with more than 10 years′ experience in breast imaging. The area under the curve (AUC), sensitivity and specificity of BI-RADS 3 to 4 exclusive microcalcifications diagnosis by mammography and mammography plus MRI were calculated and compared using pathology as the gold standard.@*Results@#A total of 152 lesions (93 benign lesionsand 59 malignant lesions) were assessed in this study. The positive predictive value (PPV) of mammography for BI-RADS 3, 4A, 4B and 4C microcalcifications diagnosis were 22.2%(16/72), 5.0%(1/20), 48.5%(17/35) and 100.0%(25/25) respectively. The PPV of MRI for BI-RADS 2, 3, 4, 5 microcalcifications diagnosis were 1.6%(1/62), 7.1%(2/28), 72.2%(13/18) and 97.7%(43/44).The area under curve, sensitivity and specificity of mammography for BI-RADS 3 to 4 microcalcifications diagnosis were 0.676,72.9% and 60.2%. The area under curve, sensitivity and specificity of mammography plus MRI for BI-RADS 3 to 4 microcalcifications diagnosis were 0.982, 94.9% and 93.6%.@*Conclusions@#Multi-parametric MRI can improve the diagnostic accuracy in mammographically detected BI-RADS 3 to 4 exclusive microcalcifications, which is helpful to differentiate benign and malignant breast lesions with microcalcifications and avoid unnecessary biopsies.
ABSTRACT
Objective To assess the value of multi-parametric MRI in mammographically detected breast imaging reporting and data systems (BI-RADS) 3 to 4 exclusive microcalcifications. Methods A retrospective analysis was performed in 152 patients with mammographically detected BI-RADS 3 to 4 exclusive microcalcifications from January 2013 to December 2017. All patients underwent bilateral breast multi-parametric MRI before surgical biopsy. Microcalcifications were classified according to BI-RADS by two radiologists with more than 10 years′ experience in breast imaging. The area under the curve (AUC), sensitivity and specificity of BI-RADS 3 to 4 exclusive microcalcifications diagnosis by mammography and mammography plus MRI were calculated and compared using pathology as the gold standard. Results A total of 152 lesions (93 benign lesionsand 59 malignant lesions) were assessed in this study. The positive predictive value (PPV) of mammography for BI-RADS 3, 4A, 4B and 4C microcalcifications diagnosis were 22.2%(16/72),5.0%(1/20),48.5%(17/35) and 100.0%(25/25) respectively. The PPV of MRI for BI-RADS 2, 3, 4, 5 microcalcifications diagnosis were 1.6%(1/62),7.1%(2/28),72.2%(13/18) and 97.7%(43/44).The area under curve, sensitivity and specificity of mammography for BI-RADS 3 to 4 microcalcifications diagnosis were 0.676,72.9% and 60.2%. The area under curve, sensitivity and specificity of mammography plus MRI for BI-RADS 3 to 4 microcalcifications diagnosis were 0.982, 94.9% and 93.6%. Conclusions Multi-parametric MRI can improve the diagnostic accuracy in mammographically detected BI-RADS 3 to 4 exclusive microcalcifications, which is helpful to differentiate benign and malignant breast lesions with microcalcifications and avoid unnecessary biopsies.
ABSTRACT
Objective To design a wearable physiological monitoring system for acquiring and monitor-ing vital signs non-intrusively and concurrently.Methods All bio-sensors were embedded in an elastic shirt for detecting physiological parameters with wearable technology.A patented respiratory inductive plethysmography technology was used to measure respiratory function,two sensors were woven into the jerkin around the patient's chest and abdomen.A three-lead,single channel ECG measures heart rate,and a three-axis accelerometer records posture and activity level.An NTC thermometer embedded in the shirt measures the body temperature.Results An elastic jerkin with embedded sensors that collect and continuously monitor respiration,cardiac,temperature,posture and activity signals was fabricated.Conclusion This wearable physiological monitoring system can record multiple parameters non-intrusively and concurrently.It can act as an useful platform for further researches.