Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends.

Background: To date, there are inconsistent data about relationships between diffusion-weighted imaging (DWI) and tumor grading/microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Our purpose was to systematize the reported results regarding the role of DWI in prediction of tumor grading/MVI in HCC. Method: MEDLINE library, Scopus, and Embase data bases were screened up to December 2019. Overall, 29 studies with 2,715 tumors were included into the analysis. There were 20 studies regarding DWI and tumor grading, 8 studies about DWI and MVI, and 1 study investigated DWI, tumor grading, and MVI in HCC. Results: In 21 studies (1,799 tumors), mean apparent diffusion coefficient (ADC) values (ADCmean) were used for distinguishing HCCs. ADCmean of G1–3 lesions overlapped significantly. In 4 studies (461 lesions), minimum ADC (ADCmin) was used. ADCmin values in G1/2 lesions were over 0.80 × 10−3 mm2/s and in G3 tumors below 0.80 × 10−3 mm2/s. In 4 studies (241 tumors), true diffusion ( D ) was reported. A significant overlapping of D values between G1, G2, and G3 groups was found. ADCmean and MVI were analyzed in 9 studies (1,059 HCCs). ADCmean values of MIV+/MVI− lesions overlapped significantly. ADCmin was used in 4 studies (672 lesions). ADCmin values of MVI+ tumors were in the area under 1.00 × 10−3 mm2/s. In 3 studies (227 tumors), D was used. Also, D values of MVI+ lesions were predominantly in the area under 1.00 × 10−3 mm2/s. Conclusion: ADCmin reflects tumor grading, and ADCmin and D predict MVI in HCC. Therefore, these DWI parameters should be estimated for every HCC lesion for pretreatment tumor stratification. ADCmean cannot predict tumor grading/MVI in HCC.

/pdf/diffusion-weighted-imaging-reflects-tumor-grading-and-1u1nbt9fnj.pdf

Diffusion-Weighted Imaging Reflects Tumor Grading and Microvascular Invasion in Hepatocellular Carcinoma

Background The Liver Imaging Reporting and Data System (LI-RADS), supported by the American College of Radiology (ACR), has been developed for standardizing the acquisition, interpretation, reporting, and data collection of liver imaging examinations in patients at risk for hepatocellular carcinoma (HCC). Diffusion-weighted imaging (DWI), which is described as an ancillary imaging feature of LI-RADS, can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance imaging (MRI) for HCC. Aim To determine whether the use of DWI can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance MRI for HCC. Methods In this institutional review board-approved study, 245 observations of high risk of HCC were retrospectively acquired from 203 patients who underwent gadoxetic acid-enhanced MRI from October 2013 to April 2018. Two readers independently measured the maximum diameter and recorded the presence of each lesion and assigned scores according to LI-RADS v2017. The test was used to determine the agreement between the two readers with or without DWI. In addition, the sensitivity (SE), specificity (SP), accuracy (AC), positive predictive value (PPV), and negative predictive value (NPV) of LI-RADS were calculated. Youden index values were used to compare the diagnostic performance of LI-RADS with or without DWI. Results Almost perfect interobserver agreement was obtained for the categorization of observations with LI-RADS (kappa value: 0.813 without DWI and 0.882 with DWI). For LR-5, the diagnostic SE, SP, and AC values were 61.2%, 92.5%, and 71.4%, respectively, with or without DWI; for LR-4/5, they were 73.9%, 80%, and 75.9% without DWI and 87.9%, 80%, and 85.3% with DWI; for LR-4/5/M, they were 75.8%, 58.8%, and 70.2% without DWI and 87.9%, 58.8%, and 78.4% with DWI; for LR- 4/5/TIV, they were 75.8%, 75%, and 75.5% without DWI and 89.7%, 75%, and 84.9% with DWI. The Youden index values of the LI-RADS classification without or with DWI were as follows: LR-4/5: 0.539 vs 0.679; LR-4/5/M: 0.346 vs 0.467; and LR-4/5/TIV: 0.508 vs 0.647. Conclusion LI-RADS v2017 has been successfully applied with gadoxetate-enhanced MRI for patients at high risk for HCC. The addition of DWI significantly increases the diagnostic efficiency for HCC.

Hepatocellular carcinoma: Can LI-RADS v2017 with gadoxetic-acid enhancement magnetic resonance and diffusion-weighted imaging improve diagnostic accuracy?

Diffusion-weighted MRI with ADC mapping for response prediction and assessment of oesophageal cancer: A systematic review

The present study aimed to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). This study included 65 patients with malignant hepatic nodules (55 with HCC, 10 with ICC), and 17 control patients with normal livers. All patients underwent IVIM-DWI scans on a 3.0 T magnetic resonance imaging (MRI) scanner. The standard apparent diffusion coefficient (ADC), pure diffusion coefficient (Dslow), pseudo-diffusion coefficient (Dfast), and perfusion fraction (f) were obtained. Differences in the parameters among the groups were analysed using one-way ANOVA, with p < 0.05 indicating statistical significance. Receiver operating characteristic (ROC) curve analysis was used to compare the efficacy of each parameter in differentiating HCC from ICC. ADC, Dslow, Dfast, f significantly differed among the three groups. ADC and Dslow were significantly lower in the HCC group than in the ICC group, while Dfast was significantly higher in the HCC group than in the ICC group; f did not significantly differ between the HCC and ICC groups. When the cut-off values of ADC, Dslow, and Dfast were 1.27 × 10−3 mm2/s, 0.81 × 10−3 mm2/s, and 26.04 × 10−3 mm2/s, respectively, their diagnostic sensitivities for differentiating HCC from ICC were 98.18%, 58.18%, and 94.55%, their diagnostic specificities were 50.00%, 80.00%, and 80.00%, and their areas under the ROC curve (AUCs) were 0.687, 0.721, and 0.896, respectively. Dfast displayed the largest AUC value. IVIM-DWI can be used to differentiate HCC from ICC.

/pdf/intravoxel-incoherent-motion-diffusion-weighted-imaging-to-lrda97fvoe.pdf

Intravoxel incoherent motion diffusion-weighted imaging to differentiate hepatocellular carcinoma from intrahepatic cholangiocarcinoma.

Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for predicting histological grade of hepatocellular carcinoma: Comparison with conventional diffusion-weighted imaging

High-resolution magnetic resonance (MR) images clearly depict the normal oesophageal wall as consisting of eight layers, which correlates well with histopathological findings. In 56 (91.8%) of 61 lesions, the depth of oesophageal wall invasion determined through MR imaging was consistent with histopathological staging (r = 0.975, P < 0.001). The sensitivity, specificity and accuracy for the mucosa were 71.4%, 98.1%, and 95.1%, respectively, and the corresponding values for the submucosa were 82.4%, 95.5%, and 91.8%; for the muscularis propria, the sensitivity, specificity and accuracy were 100%, 95.7%, and 96.7%, respectively, and for the adventitia, these values were 100%, 100%, and 100%. The Cohen k values for interobserver agreement were excellent: K = 0.839, P < 0.001 (observer 1 vs. observer 2); K = 0.908, P < 0.001 (observer 1 vs. observer 3); and K = 0.885, P < 0.01 (observer 2 vs. observer 3). High-resolution ex vivo MR images obtained with a 3.0 T scanner can be used to precisely evaluate oesophageal carcinoma invasion and provide good diagnostic sensitivity, specificity and accuracy.

/pdf/oesophageal-carcinoma-comparison-of-ex-vivo-high-resolution-4cj3l2txfp.pdf

Oesophageal carcinoma: comparison of ex vivo high-resolution 3.0 T MR imaging with histopathological findings.

Background The pathological grade of esophageal carcinoma is highly determinant of patient prognosis, but it still cannot be adequately evaluated preoperatively. Compared with conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) diffusion-weighted MRI can separate true molecular diffusion and perfusion in tissues and has been shown to be useful in characterizing malignant tumors. There is no report that compared IVIM and conventional DWI in grading esophageal carcinoma. Purpose To prospectively determine the diagnostic performance of conventional DWI and IVIM models in differentiating the pathological differentiated grade of esophageal carcinoma. Study type Prospective. Population A cohort comprising 81 patients with newly diagnosed esophageal squamous cell carcinoma (ESCC) between December 2015 and August 2017 were evaluated. Field strength/sequence 3.0T, axial echo-planer imaging, fast spin echo (FSE) sequence, IVIM sequence (b = 0, 20, 50, 80, 100, 150, 200, 400, 600, 800, 1000, 1200). Assessment Apparent diffusion coefficient (ADC), true ADC (ADCslow ), pseudo ADC (ADCfast ), and perfusion fraction (f) of each tumor were calculated by two independent radiologists. Histopathologic grade was used as the reference standard. Statistical tests Games-Howell test; diagnostic accuracy; Spearman correlation; intraclass correlation coefficient; and Bland-Altman analysis. Receiver operating characteristics (ROC) curves. Results ADCslow demonstrated the highest area under curve (AUC) with a value of 0.830 (95% confidence interval [CI]: 0.730-0.904) and 0.816 (95% CI: 0.714-0.893) by two radiologists, followed by ADC with a value of 0.754 (95% CI: 0.646-0.843) and 0.761 (95% CI: 0.653-0.848). Good correlation was obtained between the histologic grade and ADCslow (r(R1) = 0.748, r(R2) = 0.720) and ADC (r(R1) = 0.576, r(R2) = 0.571). Data conclusion ADCslow and ADC had a significantly higher performance than the ADCfast and f, and ADCslow had a significantly higher performance than the ADC. Level of evidence 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:253-261.

Esophageal carcinoma: Intravoxel incoherent motion diffusion-weighted MRI parameters and histopathological correlations

Purpose
To prospectively determine the feasibility of T2-mapping magnetic resonance imaging (MRI) to quantitatively describe the signal characteristics of the normal esophageal wall and assess the depth of esophageal wall invasion by carcinoma at 3.0T.

Materials and Methods
Thirty-two patient specimens, each having foci of carcinoma, were studied using 3.0T MR. Freehand regions of interest were placed to measure the T2 value of the normal esophageal layers and were compared with the regions of carcinoma. Three independent readers reviewed the MR images to evaluate the depth of carcinoma invasion; when the three radiologists could not fully agree with each other, the final stage was determined by consensus. The Games-Howell test was used to compare the difference between the normal esophageal layers and carcinoma. Spearman correlation coefficient analysis was used to compare the stage at MRI with that at histopathological analysis. The interobserver agreement was compared with Cohen's kappa. The sensitivity, specificity, and accuracy for detecting carcinoma invasion were calculated.

Results
The T2 values between the carcinoma and normal esophageal layers were different (all P < 0.01), except for the inner circular muscle (P = 0.511). The T2 value of each layer of the normal esophageal wall was also different from that of the adjacent layer (all P < 0.01). In 29 of 32 lesions, the depth of the esophageal wall invasion determined by MR was consistent with the histopathological stage (r = 0.969, P < 0.001). The sensitivity, specificity, and accuracy were 80%, 96.3%, and 93.8%, respectively, for invasion into the mucosa; 77.8%, 95.7%, and 90.6%, respectively, for invasion into submucosa; 100%, 95.8%, and 96.9%, respectively, for invasion into muscularis propria; and 100%, 100%, and 100%, respectively, for invasion into the adventitia.

Conclusion
T2-mapping MR images obtained using a 3.0T MR scanner can be used to depict the precise histopathological layers of the esophageal wall clearly and provide excellent diagnostic accuracy for assessing esophageal carcinoma invasion.

Level of Evidence: 1

J. Magn. Reson. Imaging 2016.

Esophageal carcinoma: Ex vivo evaluation by high‐spatial‐resolution T2‐mapping MRI compared with histopathological findings at 3.0T

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Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for predicting histological grade of hepatocellular carcinoma: Comparison with conventional diffusion-weighted imaging

Oesophageal carcinoma: comparison of ex vivo high-resolution 3.0 T MR imaging with histopathological findings.

Esophageal carcinoma: Intravoxel incoherent motion diffusion-weighted MRI parameters and histopathological correlations

Esophageal carcinoma: Ex vivo evaluation by high‐spatial‐resolution T2‐mapping MRI compared with histopathological findings at 3.0T