Intravoxel incoherent motion MR imaging of early cervical carcinoma: correlation between imaging parameters and tumor-stroma ratio

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Background The identification of hypoxia inducible factor (HIF‐1α) expression is helpful for the quantitative assessment of tumor hypoxia. The application of multimodal imaging techniques may play a part in the assessment of HIF‐1α expression of cervical carcinoma. Purpose To investigate the correlations between multiple imaging parameters and HIF‐1α expression of early cervical carcinoma and to determine whether tumor hypoxia can be predicted using multisequence imaging parameters. Study Type Prospective observational. Population One hundred patients with early cervical carcinoma. Field Strength/Sequences 3.0 T MRI including intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI) and dynamic contrast‐enhanced (DCE) perfusion MRI sequences. Assessment DCE‐MRI and IVIM DWI were performed for all patients. The imaging parameters included volume transfer constant (Ktrans), rate constant (Kep), extravascular extracellular volume fraction (Ve), D, D*, and f. Statistical Tests The comparisons of imaging parameters between two independent groups were performed using the Mann–Whitney U‐test. Multiple linear regression analysis was performed to determine the correlation between multiple imaging parameters and HIF‐1α expression. The diagnostic ability of DCE‐MRI, IVIM DWI, and the combination of two techniques for discriminating high‐expression and low‐expression groups were analyzed. Results The high‐expression group had a lower Ktrans or Kep value than the low‐expression group (P = 0.03; 0.02), while the high‐expression group had a higher Ve value than the low‐expression group (P = 0.03). The high‐expression group had a higher D or f value than the low‐expression group (P = 0.02; 0.02). Ktrans, Kep, D, Ve, and f values were independently correlated with HIF‐1α expression. The sensitivity or accuracy of a combined method was higher than that of DCE‐MRI or IVIM DWI individually (P = 0.03, 0.02; 0.04, 0.03). Data Conclusion The combination of DCE‐MRI and IVIM DWI can improve the diagnostic ability of discriminating different HIF‐1α expression levels for early cervical tumors. Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:918–929.

Section: Discussioncontrasting

confidence: 57%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…In the IVIM model, the relationship between signal variation and b factors was calculated from the following equation:

italicSb / S 0 = ((), 1 - f) * \exp ((), - italicbD) + f^{*} \exp ((), - {bD}^{*})

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Intravoxel Incoherent Motion Combined With Dynamic Contrast‐Enhanced Perfusion MRI of Early Cervical Carcinoma: Correlations Between Multimodal Parameters and HIF‐1α Expression

et al. 2019

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Whole‐tumor histogram analysis of monoexponential and advanced diffusion‐weighted imaging for sinonasal malignant tumors: Correlations with histopathologic features

Xiao

Tang

Zhang

et al. 2019

Background: The histopathological basis of monoexponential diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) in the characterization of sinonasal malignant tumors is still unclear. Purpose: To explore the correlations of histogram metrics from monoexponential DWI, IVIM, and DKI with histopathologic features in sinonasal malignant tumors. Study Type: Retrospective. Subjects: In all, 76 patients with sinonasal malignant tumors. Field Strength/Sequence: Fourteen different b values (b = 0, and 2500 sec/mm 2 ) were used to perform different DWI models at 3.0T. Assessment: The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), diffusion kurtosis (K), and diffusion coefficient (Dk) maps. Histopathologic features, including nuclear, cytoplasmic, cellular, stromal fractions, and the nuclear-to-cytoplasmic (N/C) ratio, were measured. Statistical Tests: Spearman correlations and stepwise multiple linear regression analyses were performed to determine the correlations between histogram metrics and histopathologic features. Results: ADC, Dk, and f histogram metrics showed significant correlations with investigated histopathologic features; D and K histogram metrics were significantly correlated with cellular, stromal, and nuclear fractions (all P < 0.05). Significant correlations between the 75th percentile of D and cytoplasmic fraction and between the kurtosis of K and the N/C ratio were observed (P < 0.05). The skewness of Dk, K, and the 75th percentile of D were independently associated with cellular and nuclear fractions; the skewness of Dk and K were independently associated with stromal fraction (P < 0.05). Data Conclusion: Monoexponential and advanced DWI histogram parameters were significantly correlated with histopathologic features in sinonasal malignancies. Level of Evidence: 3 Technical Efficacy: Stage 2

DWI and IVIM Imaging in a Murine Model of Rhabdomyosarcoma: Correlations with Quantitative Histopathologic Features

Fang

Yang

Chen

et al. 2021

Background High cellularity and abnormal interstitial structures are some of the unfavorable factors that affect the treatment outcomes and survival of rhabdomyosarcoma (RMS) patients. Purpose To explore the correlation between diffusion‐weighted imaging (DWI) and intravoxel incoherent motion (IVIM) with quantitative histopathologic features in a murine model of RMS. Study Type Prospective. Animal Model Murine model of RMS (31 female BALB/c nude mice). Field Strength/Sequence 3.0 T; fast spin‐echo (FSE) T1‐weighted imaging, fast relaxation fast spin‐echo (FRFSE) T2‐weighted imaging, DWI PROPELLER FSE imaging sequence, and IVIM echo planar imaging sequence; 10 different b‐values (0, 50, 100, 150, 200, 400, 600, 800, 1000, and 1200 s/mm2). Assessment Magnetic resonance imaging (MRI) was performed after 30–45 days of implantation. The following MRI parameters were calculated: apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo‐diffusion coefficient (D*), and perfusion fraction (f). Histopathologic features, which contained nuclear, cytoplasmic, and stromal fractions, and the nuclear‐to‐cytoplasmic ratio within the tumor were measured using image‐based segmentation. Statistical Tests Pearson's correlation, multiple linear regression analysis, and receiver operating characteristic curve analysis were performed. A P < 0.05 was considered statistically significant. Results The ADC value showed moderate negative correlation with nuclear fraction (r = −0.540), and moderate positive correlation with stroma fraction (r = 0.474). The D value showed moderate negative correlation with nuclear fraction (r = −0.491), and moderate positive correlation with stroma fraction (r = 0.421). The f value showed a moderate negative correlation with stroma fraction (r = −0.423). The D value showed the best diagnostic ability. The optimal cut‐off D value of 0.460 was associated with 77.8% sensitivity and 68.2% specificity (area under the curve, 0.747). Data Conclusion The ADC, D, and f values obtained from DWI and IVIM images showed moderate correlation with the quantitative histopathologic features in a murine model of RMS. Level of Evidence 1 Technical Efficacy Stage 3