TY - JOUR
T1 - Advanced diffusion-weighted imaging modeling for prostate cancer characterization
T2 - Correlation with quantitative histopathologic tumor tissue composition - A hypothesis-generating study
AU - Hectors, Stefanie J.
AU - Semaan, Sahar
AU - Song, Christopher
AU - Lewis, Sara
AU - Haines, George K.
AU - Tewari, Ashutosh
AU - Rastinehad, Ardeshir R.
AU - Taouli, Bachir
N1 - Publisher Copyright:
© RSNA, 2017.
PY - 2018/3
Y1 - 2018/3
N2 - Purpose: To correlate quantitative diffusion-weighted imaging (DWI) parameters derived from conventional monoexponential DWI, stretched exponential DWI, diffusion kurtosis imaging (DKI), and diffusion-tensor imaging (DTI) with quantitative histopathologic tumor tissue composition in prostate cancer in a preliminary hypothesis-generating study. Materials and This retrospective institutional review board-approved study included Methods: 24 patients with prostate cancer (mean age, 63 years) who underwent magnetic resonance (MR) imaging, including high-b-value DWI and DTI at 3.0 T, before prostatectomy. The following parameters were calculated in index tumors and nontumoral peripheral zone (PZ): apparent diffusion coefficient (ADC) obtained with monoexponential fit (ADCME), ADC obtained with stretched exponential modeling (ADCSE), anomalous exponent (a) obtained at stretched exponential DWI, ADC obtained with DKI modeling (ADCDKI), kurtosis with DKI, ADC obtained with DTI (ADCDTI), and fractional anisotropy (FA) at DTI. Parameters in prostate cancer and PZ were compared by using paired Student t tests. Pearson correlations between tumor DWI and quantitative histologic parameters (nuclear, cytoplasmic, cellular, stromal, luminal fractions) were determined. Results: All DWI parameters were significantly different between prostate cancer and PZ (P , .012). ADCME, ADCSE, and ADCDKI all showed significant negative correlation with cytoplasmic and cellular fractions (r = 20.546 to 20.435; P , .034) and positive correlation with stromal fractions (r = 0.619-0.669; P , .001). ADCDTI and FA showed correlation only with stromal fraction (r = 0.512 and 20.413, respectively; P , .045). a did not correlate with histologic parameters, whereas kurtosis showed significant correlations with histopathologic parameters (r = 0.487, 0.485, 20.422 for cytoplasmic, cellular, and stromal fractions, respectively; P , .040). Conclusion: Advanced DWI methods showed significant correlations with histopathologic tissue composition in prostate cancer. These findings should be validated in a larger study.
AB - Purpose: To correlate quantitative diffusion-weighted imaging (DWI) parameters derived from conventional monoexponential DWI, stretched exponential DWI, diffusion kurtosis imaging (DKI), and diffusion-tensor imaging (DTI) with quantitative histopathologic tumor tissue composition in prostate cancer in a preliminary hypothesis-generating study. Materials and This retrospective institutional review board-approved study included Methods: 24 patients with prostate cancer (mean age, 63 years) who underwent magnetic resonance (MR) imaging, including high-b-value DWI and DTI at 3.0 T, before prostatectomy. The following parameters were calculated in index tumors and nontumoral peripheral zone (PZ): apparent diffusion coefficient (ADC) obtained with monoexponential fit (ADCME), ADC obtained with stretched exponential modeling (ADCSE), anomalous exponent (a) obtained at stretched exponential DWI, ADC obtained with DKI modeling (ADCDKI), kurtosis with DKI, ADC obtained with DTI (ADCDTI), and fractional anisotropy (FA) at DTI. Parameters in prostate cancer and PZ were compared by using paired Student t tests. Pearson correlations between tumor DWI and quantitative histologic parameters (nuclear, cytoplasmic, cellular, stromal, luminal fractions) were determined. Results: All DWI parameters were significantly different between prostate cancer and PZ (P , .012). ADCME, ADCSE, and ADCDKI all showed significant negative correlation with cytoplasmic and cellular fractions (r = 20.546 to 20.435; P , .034) and positive correlation with stromal fractions (r = 0.619-0.669; P , .001). ADCDTI and FA showed correlation only with stromal fraction (r = 0.512 and 20.413, respectively; P , .045). a did not correlate with histologic parameters, whereas kurtosis showed significant correlations with histopathologic parameters (r = 0.487, 0.485, 20.422 for cytoplasmic, cellular, and stromal fractions, respectively; P , .040). Conclusion: Advanced DWI methods showed significant correlations with histopathologic tissue composition in prostate cancer. These findings should be validated in a larger study.
UR - http://www.scopus.com/inward/record.url?scp=85042462791&partnerID=8YFLogxK
U2 - 10.1148/radiol.2017170904
DO - 10.1148/radiol.2017170904
M3 - Article
C2 - 29117481
AN - SCOPUS:85042462791
SN - 0033-8419
VL - 286
SP - 918
EP - 928
JO - Radiology
JF - Radiology
IS - 3
ER -