OBJECTIVES: To investigate the tissue characteristics of cervical cancer based on the intravoxel incoherent motion (IVIM) model and to assess the IVIM parameters in tissue differentiation in the female pelvis. METHODS: Sixteen treatment-naïve cervical cancer and 17 age-matched healthy subjects were prospectively recruited for diffusion-weighted (b = 0-1,000 s/mm(2)) and standard pelvic MRI. Bi-exponential analysis was performed to derive the perfusion parameters f (perfusion fraction) and D* (pseudodiffusion coefficient) as well as the diffusion parameter D (true molecular diffusion coefficient) in cervical cancer (n = 16), normal cervix (n = 17), myometrium (n = 33) and leiomyoma (n = 14). Apparent diffusion coefficient (ADC) was calculated. Kruskal-Wallis test and receiver operating characteristics (ROC) curves were used. RESULTS: Cervical cancer had the lowest f (14.9 ± 2.6%) and was significantly different from normal cervix and leiomyoma (p < 0.05). The D (0.86 ± 0.16 x 10(-3) mm2/s) was lowest in cervical cancer and was significantly different from normal cervix and myometrium (p < 0.05) but not leiomyoma. No difference was observed in D*. D was consistently lower than ADC in all tissues. ROC curves indicated that f < 16.38%, D < 1.04 × 10(-3) mm(2)/s and ADC < 1.13 × 10(-3) mm(2)/s could differentiate cervical cancer from non-malignant tissues (AUC 0.773-0.908). CONCLUSIONS: Cervical cancer has low perfusion and diffusion IVIM characteristics with promising potential for tissue differentiation. KEY POINTS: • Diffusion-weighted MRI is increasingly applied in evaluation of cervical cancer. • Cervical cancer has distinctive perfusion and diffusion characteristics. • Intravoxel incoherent motion characteristics can differentiate cervical cancer from non-malignant uterine tissues.
OBJECTIVES: To investigate the tissue characteristics of cervical cancer based on the intravoxel incoherent motion (IVIM) model and to assess the IVIM parameters in tissue differentiation in the female pelvis. METHODS: Sixteen treatment-naïve cervical cancer and 17 age-matched healthy subjects were prospectively recruited for diffusion-weighted (b = 0-1,000 s/mm(2)) and standard pelvic MRI. Bi-exponential analysis was performed to derive the perfusion parameters f (perfusion fraction) and D* (pseudodiffusion coefficient) as well as the diffusion parameter D (true molecular diffusion coefficient) in cervical cancer (n = 16), normal cervix (n = 17), myometrium (n = 33) and leiomyoma (n = 14). Apparent diffusion coefficient (ADC) was calculated. Kruskal-Wallis test and receiver operating characteristics (ROC) curves were used. RESULTS:Cervical cancer had the lowest f (14.9 ± 2.6%) and was significantly different from normal cervix and leiomyoma (p < 0.05). The D (0.86 ± 0.16 x 10(-3) mm2/s) was lowest in cervical cancer and was significantly different from normal cervix and myometrium (p < 0.05) but not leiomyoma. No difference was observed in D*. D was consistently lower than ADC in all tissues. ROC curves indicated that f < 16.38%, D < 1.04 × 10(-3) mm(2)/s and ADC < 1.13 × 10(-3) mm(2)/s could differentiate cervical cancer from non-malignant tissues (AUC 0.773-0.908). CONCLUSIONS:Cervical cancer has low perfusion and diffusion IVIM characteristics with promising potential for tissue differentiation. KEY POINTS: • Diffusion-weighted MRI is increasingly applied in evaluation of cervical cancer. • Cervical cancer has distinctive perfusion and diffusion characteristics. • Intravoxel incoherent motion characteristics can differentiate cervical cancer from non-malignant uterine tissues.
Authors: Vincent Lai; Xiao Li; Victor Ho Fun Lee; Ka On Lam; Daniel Yee Tak Fong; Bingsheng Huang; Queenie Chan; Pek Lan Khong Journal: Eur Radiol Date: 2013-08-29 Impact factor: 5.315
Authors: Hersh Chandarana; Stella K Kang; Samson Wong; Henry Rusinek; Jeff L Zhang; Shigeki Arizono; William C Huang; Jonathan Melamed; James S Babb; Edgar F Suan; Vivian S Lee; Eric E Sigmund Journal: Invest Radiol Date: 2012-12 Impact factor: 6.016
Authors: Katja Pinker; Piotr Andrzejewski; Pascal Baltzer; Stephan H Polanec; Alina Sturdza; Dietmar Georg; Thomas H Helbich; Georgios Karanikas; Christoph Grimm; Stephan Polterauer; Richard Poetter; Wolfgang Wadsak; Markus Mitterhauser; Petra Georg Journal: PLoS One Date: 2016-05-11 Impact factor: 3.240