Evaluation of fitting models for prostate tissue characterization using extended-range b-factor diffusion-weighted imaging.
Evaluation of fitting models for prostate tissue characterization using extended-range b-factor diffusion-weighted imaging.
复制标题
使用扩展范围B因子扩散加权成像评估前列腺组织表征的拟合模型。
DOI：
10.1002/mrm.26831
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发表时间：
2018-04
影响因子：
3.3
通讯作者：
Maier SE
中科院分区：
文献类型：
--
作者：
Langkilde F;Kobus T;Fedorov A;Dunne R;Tempany C;Mulkern RV;Maier SE
To compare the fitting and tissue discrimination performance of biexponential, kurtosis, stretched exponential, and gamma distribution models for high b-factor diffusion-weighted images in prostate cancer. Diffusion-weighted images with 15 b-factors ranging from b = 0 to 3500 s/mm2 were obtained in 62 prostate cancer patients. Pixel-wise signal decay fits for each model were evaluated with the Akaike Information Criterion (AIC). Parameter values for each model were determined within normal prostate and the index lesion. Their potential to differentiate normal from cancerous tissue was investigated through receiver operating characteristic analysis and comparison with Gleason score. The biexponential slow diffusion fraction fslow, the apparent kurtosis diffusion coefficient ADCK, and the excess kurtosis factor K differ significantly among normal peripheral zone (PZ), normal transition zone (TZ), tumor PZ, and tumor TZ. Biexponential and gamma distribution models result in the lowest AIC, indicating a superior fit. Maximum areas under the curve (AUCs) of all models ranged from 0.93 to 0.96 for the PZ and from 0.95 to 0.97 for the TZ. Similar AUCs also result from the apparent diffusion coefficient (ADC) of a monoexponential fit to a b-factor sub-range up to 1250 s/mm2. For kurtosis and stretched exponential models, single parameters yield the highest AUCs, whereas for the biexponential and gamma distribution models, linear combinations of parameters produce the highest AUCs. Parameters with high AUC show a trend in differentiating low from high Gleason score, whereas parameters with low AUC show no such ability. All models, including a monoexponential fit to a lower-b sub-range, achieve similar AUCs for discrimination of normal and cancer tissue. The biexponential model, which is favored statistically, also appears to provide insight into disease-related microstructural changes.
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影响因子：
2.5
作者：
Quentin, Michael;Blondin, Dirk;Wittsack, Hans-Joerg
通讯作者：
Wittsack, Hans-Joerg
影响因子：
4.4
作者：
Liu, Xiaohang;Zhou, Liangping;Zhang, Yong
通讯作者：
Zhang, Yong
影响因子：
19.7
作者：
Rosenkrantz, Andrew B.;Sigmund, Eric E.;Jensen, Jens H.
通讯作者：
Jensen, Jens H.
前列腺癌的多参数MRI：最新技术的最新信息及其在检测和定位前列腺癌方面的表现。
DOI：
10.1002/jmri.23860
发表时间：
2013-05
期刊：
Journal of magnetic resonance imaging : JMRI
影响因子：
--
作者：
Hegde JV;Mulkern RV;Panych LP;Fennessy FM;Fedorov A;Maier SE;Tempany CM
通讯作者：
Tempany CM
影响因子：
2.9
作者：
Riches, S. F.;Hawtin, K.;de Souza, N. M.
通讯作者：
de Souza, N. M.