Prostate cancer aggressive prediction: preponderant diagnostic performances of intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) beyond ADC at 3.0 T scanner with gleason score at final pathology.
Purpose: To explore the preponderant diagnostic performances of IVIM and DKI in predicting the Gleason score (GS) of prostate cancer. Methods: Diffusion-weighted imaging data were postprocessed using monoexponential, lVIM and DK models to quantitate the apparent diffusion coefficient (ADC), molecula...
| Publicado en: | Abdominal Radiology Vol. 44; no. 10; pp. 3441 - 3453 |
|---|---|
| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Oct2019
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=138590113&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 138590113 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Oct2019 vid: 44 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 138590113 144187684 10.1007/s00261-019-02075-3 138590113 ppf: 3441 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prostate cancer aggressive prediction: preponderant diagnostic performances of intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) beyond ADC at 3.0 T scanner with gleason score at final pathology. aug: au: Shan, Yingchan Chen, Xiaoshan Liu, Kai Zeng, Mengsu Zhou, Jianjun affil: Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, 180 Fenglin Road, 200032, Shanghai, People's Republic of China sug: ab: Purpose: To explore the preponderant diagnostic performances of IVIM and DKI in predicting the Gleason score (GS) of prostate cancer. Methods: Diffusion-weighted imaging data were postprocessed using monoexponential, lVIM and DK models to quantitate the apparent diffusion coefficient (ADC), molecular diffusion coefficient (D), perfusion-related diffusion coefficient (Dstar), perfusion fraction (F), apparent diffusion for Gaussian distribution (Dapp), and apparent kurtosis coefficient (Kapp). Spearman's rank correlation coefficient was used to explore the relationship between those parameters and the GS, Kruskal–Wallis test, and Mann–Whitney U test were performed to compare the above parameters between the different groups, and a receiver-operating characteristic (ROC) curve was used to analyze the differential diagnosis ability. The interpretation of the results is in view of histopathologic tumor tissue composition. Results: The area under the ROC curves (AUCs) of ADC, F, D, Dapp, and Kapp in differentiating GS ≤ 3 + 4 and GS > 3 + 4 PCa were 0.744 (95% CI 0.581–0.868), 0.726 (95% CI 0.563–0.855), 0.732 (95% CI 0.569–0.860), and 0.752 (95% CI 0.590–0.875), 0.766 (95% CI 0.606–0.885), respectively, and those in differentiating GS ≤ 7 and GS > 7 PCa were 0.755 (95% CI 0.594–0.877), 0.734 (95% CI 0.571–0.861), 0.724 (95% CI0.560–0.853), and 0.716 (95% CI 0.552–0.847), 0.828 (95% CI 0.676–0.929), respectively. All the P values were less than 0.05. There was no significant difference in the AUC for the detection of different GS groups by using those parameters. Conclusion: Both the IVIM and DKI models are beneficial to predict GS of PCa and indirectly predict its aggressiveness, and they have a comparable diagnostic performance with each other as well as ADC. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|