OBJECTIVE: In breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0 T. METHODS: 152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000 s mm(-2). ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types. RESULTS: Considering the cut-off values 1.46 and 1.49 × 10(3)mm(2) s(-1), the pairs 50, 1000 and 200, 800 s mm(-2) showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000 s mm(-2) with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86 ± 0.46, 1.77 ± 0.37 and 1.15 ± 0.46 × 10(-3) mm(2) s(-1) for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCall (ADC calculated from the full set of b - values) [difference = 0.0075 × 10(-3) mm(2) s(-1); confidence interval 95%: (-0.0036; 0.0186); p = 0.18]. CONCLUSION: The diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000 s mm(-2). ADVANCES IN KNOWLEDGE: The best b-value pair for lesion discrimination and characterization through ADC quantification was 50, 1000 s mm(-2).
OBJECTIVE: In breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0 T. METHODS: 152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000 s mm(-2). ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types. RESULTS: Considering the cut-off values 1.46 and 1.49 × 10(3)mm(2) s(-1), the pairs 50, 1000 and 200, 800 s mm(-2) showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000 s mm(-2) with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86 ± 0.46, 1.77 ± 0.37 and 1.15 ± 0.46 × 10(-3) mm(2) s(-1) for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCall (ADC calculated from the full set of b - values) [difference = 0.0075 × 10(-3) mm(2) s(-1); confidence interval 95%: (-0.0036; 0.0186); p = 0.18]. CONCLUSION: The diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000 s mm(-2). ADVANCES IN KNOWLEDGE: The best b-value pair for lesion discrimination and characterization through ADC quantification was 50, 1000 s mm(-2).
Authors: Francesco Sardanelli; Gian M Giuseppetti; Pietro Panizza; Massimo Bazzocchi; Alfonso Fausto; Giovanni Simonetti; Vincenzo Lattanzio; Alessandro Del Maschio Journal: AJR Am J Roentgenol Date: 2004-10 Impact factor: 3.959
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Authors: Savannah C Partridge; Wendy B DeMartini; Brenda F Kurland; Peter R Eby; Steven W White; Constance D Lehman Journal: AJR Am J Roentgenol Date: 2009-12 Impact factor: 3.959
Authors: Manuela Durando; Lucas Gennaro; Gene Y Cho; Dilip D Giri; Merlin M Gnanasigamani; Sujata Patil; Elizabeth J Sutton; Joseph O Deasy; Elizabeth A Morris; Sunitha B Thakur Journal: Eur J Radiol Date: 2016-06-28 Impact factor: 3.528
Authors: Corrado Tagliati; Paola Piccinni; Paola Ercolani; Elisabetta Marconi; Barbara Franca Simonetti; Gian Marco Giuseppetti; Andrea Giovagnoni Journal: Pol J Radiol Date: 2021-04-30