Assessment of tumor morphology on diffusion-weighted (DWI) breast MRI: Diagnostic value of reduced field of view DWI.
OBJECTIVE
To compare the diagnostic value of conventional, bilateral diffusion-weighted imaging (DWI) and high-resolution targeted DWI of known breast lesions.


METHODS
Twenty-one consecutive patients with known breast cancer or suspicious breast lesions were scanned with the conventional bilateral DWI technique, a high-resolution, reduced field of view (rFOV) DWI technique, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) (3.0 T). We compared bilateral DWI and rFOV DWI quantitatively by measuring the lesions' apparent diffusion coefficient (ADC) values. For qualitative comparison, three dedicated breast radiologists scored image quality and performed lesion interpretation.


RESULTS
In a phantom, ADC values were in good agreement with the reference values. Twenty-one patients (30 lesions: 14 invasive carcinomas, 10 benign lesions [of which 5 cysts], 3 high-risk, and 3 in situ carcinomas) were included. Cysts and high-risk lesions were excluded from the quantitative analysis. Quantitatively, both bilateral and rFOV DWI measured lower ADC values in invasive tumors than other lesions. In vivo, rFOV DWI gave lower ADC values than bilateral DWI (1.11 × 10(-3) mm(2) /s vs. 1.24 × 10(-3) mm(2) /s, P = 0.002). Regions of interest (ROIs) were comparable in size between the two techniques (2.90 vs. 2.13 cm(2) , P = 0.721). Qualitatively, all three radiologists scored sharpness of rFOV DWI images as significantly higher than bilateral DWI (P ≤ 0.002). Receiver operating characteristic (ROC) curve analysis showed a higher area under the curve (AUC) in BI-RADS classification for rFOV DWI compared to bilateral DWI (0.71 to 0.93 vs. 0.61 to 0.76, respectively).


CONCLUSIONS
Tumor morphology can be assessed in more detail with high-resolution DWI (rFOV) than with standard bilateral DWI by providing significantly sharper images.
Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Maarten W
MW
Barentsz
Department of Radiology, Stanford University, Stanford, California, USA.
Valentina
V
Taviani
Department of Radiology, Seoul National University Hospital, Seoul, Korea.
Jung M
JM
Chang
Department of Radiology, Stanford University, Stanford, California, USA.
Debra M
DM
Ikeda
Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Hospital, Kyoto, Japan.
Kanae K
KK
Miyake
Global Applied Science Laboratory, GE Healthcare, Menlo Park, California, USA.
Suchandrima
S
Banerjee
Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Maurice A A J
MA
van den Bosch
Department of Radiology, Stanford University, Stanford, California, USA.
Brian A
BA
Hargreaves
Department of Radiology, Stanford University, Stanford, California, USA.
Bruce L
BL
Daniel
D000328:Adult; D000368:Aged; D000465:Algorithms; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000473:pathology*; D048429:Cell Size; D038524:Diffusion Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
breast cancer; diffusion-weighted imaging; magnetic resonance imaging; tumor morphology