AI Article Synopsis

  • This study analyzed DWI/ADC and DCE-MRI parameters in breast MRIs to differentiate between benign and malignant lesions, aiming to identify predictors of malignancy and develop a predictive model.* -
  • It evaluated 121 patients with 151 breast lesions, finding significant differences in lesion size, age, and specific MRI parameters like TIC and ADC values between the malignant and benign groups.* -
  • The results identified ADCmean and TIC as strong independent predictors of malignancy, with a predictive model achieving high sensitivity (94.2%) for cancer detection.*

Article Abstract

Objectives: To analyze DWI/ADC and DCE-MRI kinetic parameters on breast MRI between benign and malignant lesions, to obtain independent predictors of malignancy, and to build a possible future predictive model.

Methods: 121 patients (151 breast lesions) were evaluated by 3.0T breast MRI. Based on their post-operative histopathology, we divided them into two groups, benign and malignant. We processed their DCE-MRI images to obtain size of lesions and several kinetic parameters like Time Intensity Curve (TIC), Time To Peak (TTP), Area Under Curve (AUC), Maximum Enhancement, Wash-In (WI), and Wash-Out (WO). We also processed their DWI/ADC maps to obtain their Signal Intensity (SI) ADC values. These parameters were compared between the two groups.

Results: The age of the patients was higher in the malignant group as compared to the benign group (mean=55.9 years and 47.3 years, respectively, P<0.001). Malignant lesions were of greater size than benign ones (mean 2.55 cm and 1.82 cm, respectively, P<0.01). On DCE-MRI, parameters such as TIC, AUC, WI, and WO were statistically significantly different (all P values <0.05). On DWI/ADC, malignant lesions had statistically significant lower ADC values than benign lesions (mean of 1.02x0.001 and 1.72x0.001 mm2/s, respectively, P<0.001). We obtained a cutoff ADC value of 1.18x0.001 mm2/s to differentiate between benign and malignant lesions. Our predictive model results showed ADCmean and TIC as independent predictors of malignancy with an excellent combined model of fit (P=0.000).

Conclusion: Kinetic DCE-MRI and DWI parameters are significantly different between benign and malignant breast lesions. ADCmean and TIC are reliable independent predictors of malignancy in our prediction model, with excellent goodness of fit to predict cancer with a sensitivity of 94.2%.

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