Computed diffusion-weighted imaging with a low-apparent diffusion coefficient-pixel cut-off technique for breast cancer detection.
Br J Radiol
; 96(1151): 20220951, 2023 Nov.
Article
en En
| MEDLINE
| ID: mdl-37393536
ABSTRACT
OBJECTIVE:
This study aimed to compare the image quality and diagnostic performance of computed diffusion-weighted imaging (DWI) with low-apparent diffusion coefficient (ADC)-pixel cut-off technique (cDWI cut-off) and actual measured DWI (mDWI).METHODS:
Eighty-seven consecutive patients with malignant breast lesions and 72 with negative breast lesions who underwent breast MRI were retrospectively evaluated. Computed DWI with high b-values of 800, 1200, and 1500 s/mm2 and ADC cut-off thresholds of none, 0, 0.3, and 0.6 (×10-3 mm2/s) were generated from DWI with two b-values (0 and 800 s/mm2). To identify the optimal conditions, two radiologists evaluated the fat suppression and lesion reduction failure using a cut-off technique. The contrast between breast cancer and glandular tissue was evaluated using region of interest analysis. Three other board-certified radiologists independently assessed the optimised cDWI cut-off and mDWI data sets. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.RESULTS:
When an ADC cut-off threshold of 0.3 or 0.6 (× 10-3 mm2/s) was applied, fat suppression improved significantly (p < .05). The contrast of the cDWI cut-off with a b-value of 1200 or 1500 s/mm2 was better than the mDWI (p < .01). The ROC area under the curve for breast cancer detection was 0.837 for the mDWI and 0.909 for the cDWI cut-off (p < .01).CONCLUSION:
The cDWI cut-off provided better diagnostic performance than mDWI for breast cancer detection. ADVANCES IN KNOWLEDGE Using the low-ADC-pixel cut-off technique, computed DWI can improve diagnostic performance by increasing contrast and eliminating un-suppressed fat signals.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Mama
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Br J Radiol
Año:
2023
Tipo del documento:
Article
País de afiliación:
Japón