Correlations between intravoxel incoherent motion (IVIM) parameters and histological findings in rectal cancer: preliminary results

Histogram analysis based on intravoxel incoherent motion diffusion-weighted imaging for determining the perineural invasion status of rectal cancer

Background

Unfortunately, the morphologic magnetic resonance imaging (MRI) is unable to determine perineural invasion (PNI) status. This study applied histogram analysis of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the assessment of PNI status of rectal cancer (RC).

Methods

The retrospective analysis enrolled 175 patients with RC confirmed by postoperative pathology in The First Affiliated Hospital of Shandong First Medical University from January 2019 to December 2021. All patients underwent preoperative rectal MRI. Whole-tumor volume histogram features from IVIM-DWI were extracted using open-source software. Univariate analysis and multivariate logistic regression analysis were used to compare the differences in histogram parameters and clinical features between the PNI-positive group and PNI-negative group. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance, while the Delong test was used to compare the area under the curve of the models.

Results

The interobserver agreement of the histogram features derived from DWI, including apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), water molecular diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC) were good to excellent. A total of eight histogram features including DWI_maximum, DWI_skewness, D_kurtosis, D_minimum, D_skewness, D*_energy, D*_skewness, and f_minimum were significantly different between the PNI-positive and PNI-negative groups in the univariate analysis (P<0.05); among the clinicoradiologic factors, percentage of rectal wall circumference invasion (PCI) was significantly different between the two groups (P<0.05). Multivariate analysis demonstrated that the values of D*_energy, D*_skewness, and f_minimum differed significantly between the PNI-positive patients and PNI-negative patients (P<0.05), with the independent risk factors being D*_skewness [odds ratio (OR) =1.157; 95% confidence interval (CI): 1.050-1.276; P=0.003] and PCI (OR =11.108, 95% CI: 1.767-69.838; P=0.0002). The area under the curve of the model combining the three histogram features and PCI to assess PNI status in RC was 0.807 (95% CI: 0.741-0.863). The results of the Delong test showed that the combined model was significantly different from each single-parameter model (P<0.05).

Conclusions

The combined model constructed on the basis of IVIM-DWI histogram features may help to assess the status of RC PNI.

Precise Prostate Cancer Assessment Using IVIM-Based Parametric Estimation of Blood Diffusion from DW-MRI

Prostate cancer is a significant health concern with high mortality rates and substantial economic impact. Early detection plays a crucial role in improving patient outcomes. This study introduces a non-invasive computer-aided diagnosis (CAD) system that leverages intravoxel incoherent motion (IVIM) parameters for the detection and diagnosis of prostate cancer (PCa). IVIM imaging enables the differentiation of water molecule diffusion within capillaries and outside vessels, offering valuable insights into tumor characteristics. The proposed approach utilizes a two-step segmentation approach through the use of three U-Net architectures for extracting tumor-containing regions of interest (ROIs) from the segmented images. The performance of the CAD system is thoroughly evaluated, considering the optimal classifier and IVIM parameters for differentiation and comparing the diagnostic value of IVIM parameters with the commonly used apparent diffusion coefficient (ADC). The results demonstrate that the combination of central zone (CZ) and peripheral zone (PZ) features with the Random Forest Classifier (RFC) yields the best performance. The CAD system achieves an accuracy of 84.08% and a balanced accuracy of 82.60%. This combination showcases high sensitivity (93.24%) and reasonable specificity (71.96%), along with good precision (81.48%) and F1 score (86.96%). These findings highlight the effectiveness of the proposed CAD system in accurately segmenting and diagnosing PCa. This study represents a significant advancement in non-invasive methods for early detection and diagnosis of PCa, showcasing the potential of IVIM parameters in combination with machine learning techniques. This developed solution has the potential to revolutionize PCa diagnosis, leading to improved patient outcomes and reduced healthcare costs.

A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer

PURPOSE

To develop and validate a nomogram for the preoperative diagnosis of T2 and T3 stage rectal cancer using MRI radiomics features of mesorectal fat.

METHODS

The data of 288 patients with T2 and T3 stage rectal cancer were retrospectively collected. Radiomics features were extracted from the lesion region of interest (ROI) in the MRI high-resolution T2WI, apparent diffusion coefficient (ADC), and diffusion-weighted imaging (DWI) sequences. After using ICC inter-group consistency analysis and Pearson correlation analysis to reduce dimensions, LASSO regression analysis was performed to select features and calculate Rad-score for each sequence. Then, Combined_Radscore and nomogram were constructed based on the LASSO-selected features and clinical data for each sequence. Receiver operating characteristic curve (ROC) area under the curve (AUC) was used to evaluate the performance of the Rad-score model and nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical usability of the radiomics nomogram, which were combined with calibration curves to evaluate the prediction accuracy.

RESULTS

The nomogram based on MRI-report T status and Combined_Radscore achieved AUCs of 0.921 and 0.889 in the training and validation cohorts, respectively.

CONCLUSION

The nomogram can be stated that the radiomics nomogram based on multi-sequence MRI imaging of the mesorectal fat has excellent diagnosing performance for preoperative differentiation of T2 and T3 stage rectal cancer.

Higher perfusion of rectum carcinoma relative to tumor-free rectal wall: quantification by a new imaging biomarker diffusion-derived vessel density (DDVD)

Background

Diffusion-derived vessel density (DDVD) is a physiological surrogate of the area of micro-vessels per unit tissue area. DDVD is calculated according to: DDVD(b0b5) = Sb0/ROIarea0 - Sb5/ROIarea5, where Sb0 and Sb5 refer to the tissue signal when b is 0 or 5 s/mm2. This study applied DDVD to assess the perfusion of rectal carcinoma (RC).

Methods

MRI was performed with a 3.0-T magnet. Diffusion weighted image with b-values of 0, 5 s/mm2 were acquired in 113 patients with non-mucinous RC and 15 patients with mucinous RC. Diffusion-derived vessel density ratio [DDVDr(b0b5)] was DDVD(b0b5) of RC divided by DDVD(b0b5) of tumor-free rectal wall.

Results

The median value of the DDVDr(b0b5) for non-mucinous RCs was 1.430, with the majority of RCs showing a higher DDVD than the adjacent tumor-free wall [i.e., with DDVDr(b0b5) >1]. 90.3% (102/113) of non-mucinous RCs were hypervascular, 1.77% (2/113) were iso-vascular, and 7.96% (9/113) were hypovascular. The median value of the DDVDr(b0b5) for mucinous RCs was 1.660. 73.3% (11/15) of mucinous RCs were hypervascular, and 26.7% (4/15) were hypovascular. A trend (P=0.09) was noted that earlier clinical grades non-mucinous RCs had a higher DDVDr(b0b5) than those of the advanced clinical grades (2.245 for grade 0&I, 1.460 for grade II, 1.430 for grade III, 1.130 for grade IV). A non-significant trend was noted with well and moderately differentiated non-mucinous RCs had a higher DDVDr(b0b5)than that of poorly differentiated non-mucinous RCs (median: 1.460 vs. 1.320). A non-significant trend was noted with MRI-detected extramural vascular invasion (mrEMVI) positive non-mucinous RCs had a higher DDVDr(b0b5) than that of mrEMVI negative non-mucinous RCs (1.630 vs. 1.370).

Conclusions

DDVD results in this study approximately agree with contrast agent dynamically enhanced CT literature data.

Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers

Background: this study aimed to utilize various diffusion-weighted imaging (DWI) techniques, including mono-exponential DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for the preoperative grading of rectal cancer. Methods: 85 patients with rectal cancer were enrolled in this study. Mann-Whitney U tests or independent Student's t-tests were conducted to identify DWI-derived parameters that exhibited significant differences. Spearman or Pearson correlation tests were performed to assess the relationships among different DWI-derived biological markers. Subsequently, four machine learning classifier-based models were trained using various DWI-derived parameters as input features. Finally, diagnostic performance was evaluated using ROC analysis with 5-fold cross-validation. Results: With the exception of the pseudo-diffusion coefficient (Dp), IVIM-derived and DKI-derived parameters all demonstrated significant differences between low-grade and high-grade rectal cancer. The logistic regression-based machine learning classifier yielded the most favorable diagnostic efficacy (AUC: 0.902, 95% Confidence Interval: 0.754-1.000; Specificity: 0.856; Sensitivity: 0.925; Youden Index: 0.781). Conclusions: utilizing multiple DWI-derived biological markers in conjunction with a strategy employing multiple machine learning classifiers proves valuable for the noninvasive grading of rectal cancer.

A correlative study between IVIM-DWI parameters and VEGF and MMPs expression in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related death worldwide. Angiogenic factors may be valuable indices of tumor recurrence and treatment and potentially useful markers for predicting the response to antiangiogenesis therapy. Vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs) are major drivers of tumor angiogenesis. Preoperatively predicting the expression of VEGF and MMPs is crucial for treating HCC. Intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has been successfully used in the differential diagnosis of HCC, pathological grading, and treatment response evaluation. However, the correlations between IVIM-DWI parameters and VEGF and MMP expression have not been reported. This study provides a preliminary analysis of the correlation between IVIM-DWI parameters and the expression of VEGF, MMP-2, and MMP-9 to investigate the value of IVIM-DWI in the noninvasive evaluation of angiogenesis in HCC.

Methods

IVIM-DWI was performed in 61 patients with HCC 1 week before they underwent surgical resection. VEGF, MMP-2, and MMP-9 expression was detected using immunohistochemistry staining. Spearman correlation analysis was used to analyze the correlations between the IVIM-DWI parameters and VEGF, MMP-2, and MMP-9 expression in HCC.

Results

The fast apparent diffusion coefficient fraction (f) value was positively correlated with the expression of VEGF (P<0.001), MMP-2 (P=0.002), and MMP-9 (P<0.001). The fast apparent diffusion coefficient (D*) was positively correlated with VEGF (P<0.001) and MMP-9 (P<0.001) expression but was not correlated with MMP-2 (P=0.659) expression. The apparent diffusion coefficient (ADC) and slow apparent diffusion coefficient (D) values were not significantly correlated with the expression of VEGF (P=0.103 and P=0.543, respectively), MMP-2 (P=0.596 and P=0.338, respectively), or MMP-9 (P=0.102 and P=0.660, respectively).

Conclusions

IVIM-DWI can be used to noninvasively evaluate angiogenesis in HCC.

Intravoxel incoherent motion MRI for rectal cancer: correlation of diffusion and perfusion characteristics with clinical-pathologic factors

BACKGROUND

Colorectal cancer is the most common cause of cancer-related death worldwide. Magnetic resonance imaging (MRI) has become a promising alternative method for staging the cancer.

PURPOSE

To evaluate parameters of intravoxel incoherent motion (IVIM) and their relationships with clinical-pathologic factors in rectal cancers.

MATERIAL AND METHODS

A total of 51 patients with histopathologically proven rectal cancer who underwent preoperative pelvic MRI were prospectively enrolled. Parameters (ADC, D, D*, and f) derived from IVIM-diffusion-weighted imaging (DWI) were independently measured by two radiologists. Student's t-test, receiver operating characteristic curves, and Spearman correlation were used for statistical analysis.

RESULTS

ADC, D, and D* were significantly higher in pT1-2 tumors than in pT3-4 tumors (1.108 ± 0.233 vs. 0.950 ± 0.176, 0.796 ± 0.199 vs. 0.684 ± 0.114, 0.013 ± 0.005 vs. 0.008 ± 0.003, respectively; P < 0.05). D* exhibited a strong correlation with the tumor stage (r = -0.675, P < 0.001). In poorly differentiated cluster (PDC) grading, ADC, D*, and f were significantly lower in high-grade tumors than in low-grade tumors (0.905 ± 0.148 vs. 1.064 ± 0.200, 0.008 ± 0.002 vs. 0.011 ± 0.005, and 0.252 ± 0.032 vs. 0.348 ± 0.058, respectively; P < 0.05). The f value exhibited a significantly strong correlation with the PDC grades (r = -0.842, P < 0.001), and higher sensitivity and specificity (95.2% and 75.9%) than those shown by the ADC, D, and D* values.

CONCLUSION

IVIM parameters, especially f, demonstrated a strong correlation with histologic grades and showed a better performance in differentiating between high- and low-grade rectal cancers. These parameters would be helpful in predicting tumor aggressiveness and prognosis.

Combining Clinicopathology, IVIM-DWI and Texture Parameters for a Nomogram to Predict Treatment Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients

Objectives

This study aimed to create a nomogram for the risk prediction of neoadjuvant chemoradiotherapy (nCRT) resistance in locally advanced rectal cancer (LARC).

Methods

Clinical data in this retrospective study were collected from a total of 135 LARC patients admitted to our hospital from June 2016 to December 2020. After screening by inclusion and exclusion criteria, 62 patients were included in the study. Texture analysis (TA) was performed on T2WI and DWI images. Patients were divided into response group (CR+PR) and no-response group (SD+PD) according to efficacy assessment. Multivariate analysis was performed on clinicopathology, IVIM-DWI and texture parameters for screening of independent predictors. A nomogram was created and model fit and clinical net benefit were assessed.

Results

Multivariate analysis of clinicopathology parameters showed that the differentiation and T stage were independent predictors (OR values were 14.516 and 11.589, resp.; P<0.05). Multivariate analysis of IVIM-DWI and texture parameters showed that f value and Rads-score were independent predictors (OR values were 0.855, 2.790, resp.; P<0.05). In this study, clinicopathology together with IVIM-DWI and texture parameters showed the best predictive efficacy (AUC=0.979). The nomogram showed good predictive performance and stability in identifying high-risk LARC patients who are resistant to nCRT (C-index=0.979). Decision curve analyses showed that the nomogram had the best clinical net benefit. Ten-fold cross-validation results showed that the average AUC value was 0.967, and the average C-index was 0.966.

Conclusions

The nomogram combining the differentiation, T stage, f value and Rads-score can effectively estimate the risk of nCRT resistance in patients with LARC.

Lymph Nodes Evaluation in Rectal Cancer: Where Do We Stand and Future Perspective

The assessment of nodal involvement in patients with rectal cancer (RC) is fundamental in disease management. Magnetic Resonance Imaging (MRI) is routinely used for local and nodal staging of RC by using morphological criteria. The actual dimensional and morphological criteria for nodal assessment present several limitations in terms of sensitivity and specificity. For these reasons, several different techniques, such as Diffusion Weighted Imaging (DWI), Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Dynamic Contrast Enhancement (DCE) in MRI have been introduced but still not fully validated. Positron Emission Tomography (PET)/CT plays a pivotal role in the assessment of LNs; more recently PET/MRI has been introduced. The advantages and limitations of these imaging modalities will be provided in this narrative review. The second part of the review includes experimental techniques, such as iron-oxide particles (SPIO), and dual-energy CT (DECT). Radiomics analysis is an active field of research, and the evidence about LNs in RC will be discussed. The review also discusses the different recommendations between the European and North American guidelines for the evaluation of LNs in RC, from anatomical considerations to structured reporting.

Application of dual-layer spectral detector computed tomography to evaluate the expression of Ki-67 in colorectal cancer

BACKGROUND

Compared with traditional computed tomography (CT), dual-layer spectral detector CT (SDCT) shows significant improvement in imaging soft tissues of the digestive tract. This work aimed to explore the application of SDCT to evaluate the expression of the molecular marker Ki-67 in colorectal cancer.

METHODS

We retrospectively analyzed the imaging data of the SDCT (IQon Spectral CT; Philips Healthcare) of 45 patients with colorectal cancer in our centre. We used Spearman's test for the imaging parameters (reconstruction of 40, 70, and 100 keV virtual monoenergetic images [VMIs] and the slope of the Hounsfield unit attenuation plot [VMI Slope] based on venous phase CT images, the arterial phase iodine concentration [AP-IC] and venous phase iodine concentration [VP-IC], and the effective atomic number [Z effect]) and correlation analysis for the Ki-67 index. Multivariate logistic regression was used to eliminate confounding factors. We evaluated the expression level of Ki-67 and drew the receiver operating characteristic curve.

RESULTS

The 40-keV VMI, VMI Slope, and AP-IC were found to better reflect the Ki-67 index in patients with colorectal cancer with statistical significance. The 40-keV VMI (r = -0.612, p < 0.001) and VMI Slope (r = -0.523, p < 0.001) were negatively correlated with the Ki-67 index, and AP-IC (r = 0.378, p = 0.010) was positively correlated with the Ki-67 index. The other indexes (p > 0.05) were not statistically significant. The SDCT parameters demonstrated good performance, with area under curves of 0.785 for 40-keV VMI and 0.752 for AP-IC.

CONCLUSION

The SDCT parameters 40-keV VMI and AP-IC can be used for preliminary evaluation of the Ki-67 index in colorectal cancer.

Investigation of breast cancer microstructure and microvasculature from time-dependent DWI and CEST in correlation with histological biomarkers

We investigated the associations of time-dependent DWI, non-Gaussian DWI, and CEST parameters with histological biomarkers in a breast cancer xenograft model. 22 xenograft mice (7 MCF-7 and 15 MDA-MB-231) were scanned at 4 diffusion times [T_d = 2.5/5 ms with 11 b-values (0–600 s/mm²) and T_d = 9/27.6 ms with 17 b-values (0–3000 s/mm²), respectively]. The apparent diffusion coefficient (ADC) was estimated using 2 b-values in different combinations (ADC^0–600 using b = 0 and 600 s/mm² and shifted ADC [sADC^200–1500] using b = 200 and 1500 s/mm²) at each of those diffusion times. Then the change (Δ) in ADC/sADC between diffusion times was evaluated. Non-Gaussian diffusion and intravoxel incoherent motion (IVIM) parameters (ADC₀, the virtual ADC at b = 0; K, Kurtosis from non-Gaussian diffusion; f, the IVIM perfusion fraction) were estimated. CEST images were acquired and the amide proton transfer signal intensity (APT SI) were measured. The ΔsADC_9–27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{9\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC9ms200-1500 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500 and ΔADC_2.5_sADC_27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADC}}_{{2.5\, {\text{ms}}}}^{0{-}600}$$\end{document}ADC2.5ms0-600 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500) was significantly larger for MCF-7 groups, and ΔADC_2.5_sADC_27.6 was positively correlated with Ki67_max and APT SI. ADC₀ decreased significantly in MDA-MB-231 group and K increased significantly with T_d in MCF-7 group. APT SI and cellular area had a moderately strong positive correlation in MDA-MB-231 and MCF-7 tumors combined, and there was a positive correlation in MDA-MB-231 tumors. There was a significant negative correlation between APT SI and the Ki-67-positive ratio in MDA-MB-231 tumors and when combined with MCF-7 tumors. The associations of ΔADC_2.5_sADC_27.6 and API SI with Ki-67 parameters indicate that the T_d-dependent DW and CEST parameters are useful to predict the histological markers of breast cancers.

The Value of Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging Combined With Texture Analysis of Evaluating the Extramural Vascular Invasion in Rectal Adenocarcinoma

Purpose

This study aims to evaluate the value of 3.0T MRI Intravoxel Incoherent motion diffusion-weighted magnetic resonance imaging (IVIM-DWI) combined with texture analysis (TA) for evaluating extramural vascular invasion (EMVI) of rectal adenocarcinoma.

Methods

Ninety-six patients with pathologically confirmed rectal adenocarcinoma after surgical resections were collected. Patients were divided into the EMVI positive group (n=39) and the EMVI negative group (n=57). We measured the IVIM-DWI parameters and TA parameters of rectal adenocarcinoma. We compare the differences of the above parameters between the two groups and establish a prediction model through multivariate logistic regression analysis. the ROC curve was performed for parameters with each individual and in combination.

Results

ADC, D, D* value between the two groups were statistically significant (P= 0.015,0.031,0). Six groups of texture parameters were statistically significant between the two groups (P=0.007,0.037,0.011,0.005,0.007,0.002). Logistic regression prediction model shows that GLCM entropy_ALL DIRECTION_offset7_SD and D* are important independent predictors, and the AUC of the regression prediction model was 0.821, the sensitivity was 92.98%, the specificity was 61.54%, and the Yoden index was 0.5452. The AUC was significantly higher than that of other single parameters.

Conclusion

3.0T MRI IVIM-DWI parameters combined with texture analysis can provide valuable information for EMVI evaluation of rectal adenocarcinoma before the operation.

Pretreatment Apparent Diffusion Coefficient Cannot Predict Histopathological Features and Response to Neoadjuvant Radiochemotherapy in Rectal Cancer: A Meta-Analysis

AIM

Our purpose was to perform a systemic literature review and meta-analysis regarding use of apparent diffusion coefficient (ADC) for prediction of histopathological features in rectal cancer (RC) and to prove if ADC can predict treatment response to neoadjuvant radiochemotherapy (NARC) in RC.

METHODS

MEDLINE library, EMBASE, Cochrane, and SCOPUS database were screened for associations between ADC and histopathology and/or treatment response in RC up to June 2020. Authors, year of publication, study design, number of patients, mean value, and standard deviation of ADC were acquired. The methodological quality of the collected studies was checked according to the Quality Assessment of Diagnostic Studies instrument. The meta-analysis was undertaken by using the RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated.

RESULTS

Overall, 37 items (2,015 patients) were included. ADC values of tumors with different T and N stages and grades overlapped strongly. ADC cannot distinguish RC with a high- and low-carcinoembryonic antigen level. Regarding KRAS status, ADC cannot discriminate mutated and wild-type RC. ADC did not correlate significantly with expression of vascular endothelial growth factor and hypoxia-inducible factor 1a. ADC correlates with Ki 67, with the calculated correlation coefficient: -0.52. The ADC values in responders and nonresponders overlapped significantly.

CONCLUSION

ADC correlates moderately with expression of Ki 67 in RC. ADC cannot discriminate tumor stages, grades, and KRAS status in RC. ADC cannot predict therapy response to NARC in RC.

Tumor Microenvironment Modifications Recorded With IVIM Perfusion Analysis and DCE-MRI After Neoadjuvant Radiotherapy: A Preclinical Study

PURPOSE

Neoadjuvant radiotherapy (NeoRT) improves tumor local control and facilitates tumor resection in many cancers. Some clinical studies demonstrated that both timing of surgery and RT schedule influence tumor dissemination, and subsequently patient overall survival. Previously, we developed a pre-clinical model demonstrating the impact of NeoRT schedule and timing of surgery on metastatic spreading. We report on the impact of NeoRT on tumor microenvironment by MRI.

METHODS

According to our NeoRT model, MDA-MB 231 cells were implanted in the flank of SCID mice. Tumors were locally irradiated (PXI X-Rad SmART) with 2x5Gy and then surgically removed at different time points after RT. Diffusion-weighted (DW) and Dynamic contrast enhancement (DCE) MRI images were acquired before RT and every 2 days between RT and surgery. IntraVoxel Incoherent Motion (IVIM) analysis was used to obtain information on intravascular diffusion, related to perfusion (F: perfusion factor) and subsequently tumor vessels perfusion. For DCE-MRI, we performed semi-quantitative analyses.

RESULTS

With this experimental model, a significant and transient increase of the perfusion factor F [50% of the basal value (n=16, p<0.005)] was observed on day 6 after irradiation as well as a significant increase of the WashinSlope with DCE-MRI at day 6 (n=13, p<0.05). Using immunohistochemistry, a significant increase of perfused vessels was highlighted, corresponding to the increase of perfusion in MRI at this same time point. Moreover, Tumor surgical resection during this peak of vascularization results in an increase of metastasis burden (n=10, p<0.05).

CONCLUSION

Significant differences in perfusion-related parameters (F and WashinSlope) were observed on day 6 in a neoadjuvant radiotherapy model using SCID mice. These modifications are correlated with an increase of perfused vessels in histological analysis and also with an increase of metastasis spreading after the surgical procedure. This experimental observation could potentially result in a way to personalize treatment, by modulating the time of surgery guided on MRI functional data, especially tumor perfusion.

A Correlative Study Between IVIM-DWI Parameters and the Expression Levels of Ang-2 and TKT in Hepatocellular Carcinoma

Background

Noninvasive evaluation of the expression of angiopoietin-2 (Ang-2) and transketolase (TKT) in hepatocellular carcinoma (HCC) is of great significance for the clinical development of individualized treatment plans. However, the correlation between intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and the expression of Ang-2 and TKT has not been reported. We sought to investigate the correlations between IVIM-DWI parameters and Ang-2 and TKT expression levels in HCCs.

Methods

Conventional non-enhanced magnetic resonance imaging (MRI) and IVIM-DWI and dynamic contrast MRI were performed for 61 patients with HCC before surgical treatment. Various IVIM-DWI parameters, such as apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D^*) and fraction of fast apparent diffusion coefficient (f), were calculated using Function-MADC software. Expression levels of Ang-2 and TKT in HCC were detected via immunohistochemical staining and classified into two grades. Independent sample t tests were used to compare differences in parameters between the two groups. The Spearman rank correlation test was used to analyze the correlations between IVIM-DWI parameters and Ang-2 and TKT expression levels in HCCs.

Results

The D^* and f values were significantly higher in the high Ang-2 group than in the low Ang-2 group; there were no obvious between-group differences in ADC and D. Ang-2 expression was positively correlated with D* and f but not with ADC and D. The ADC and D values were significantly lower in the high TKT group than in the low TKT group, whereas the between-group differences for D* and f were not significant. TKT expression was negatively correlated with ADC and D but not with D* and f.

Conclusions

IVIM-DWI can be used to evaluate Ang-2 and TKT expression in HCC.

Associations between IVIM histogram parameters and histopathology in rectal cancer

PURPOSE

Histogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram analysis parameters derived from Intravoxel-incoherent imaging (IVIM) and histopathological features in rectal cancer (RC).

METHODS

Seventeen patients with histopathologically proven rectal adenocarcinomas were retrospectively acquired. In all cases, pelvic MRI was performed. Diffusion weighted imaging was obtained using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm². Simplified IVIM analysis was performed using the IntelliSpace portal, version 10 and the following images were generated: f (perfusion fraction) map, D (true diffusion coefficient) map, and ADC map utilizing all b-values. Histogram based analysis of signal intensities was performed for every IVIM map using an in-house matlab tool. Histopathology was investigated using Ki 67 specimens with calculation of Ki 67-index and cellularity. CD31 stained specimens were used for calculation of microvessel density (MVD).

RESULTS

There were statistically significant correlations between Ki 67 index and mode derived from ADC as well as entropy from f, r=-0.50, p=.04 and r=-0.55, p=.02, respectively. MVD correlated well with parameters derived from f.

CONCLUSION

IVIM histogram analysis parameters can reflect histopathology in RC. ADC and D values are associated with proliferation potential. Perfusion fraction f is associated with MVD.

Preoperatively Grading Rectal Cancer with the Combination of Intravoxel Incoherent Motions Imaging and Diffusion Kurtosis Imaging

Purpose

To combine Intravoxel Incoherent Motions (IVIM) imaging and diffusion kurtosis imaging (DKI) which can aid in the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity to preoperatively grade rectal cancer.

Methods

A total of 58 rectal patients were included into this prospective study. MRI was performed with a 3T scanner. Different combinations of IVIM-derived and DKI-derived parameters were performed to grade rectal cancer. Pearson correlation coefficients were applied to evaluate the correlations. Binary logistic regression models were established via integrating different DWI parameters for screening the most sensitive parameter. Receiver operating characteristic analysis was performed for evaluating the diagnostic performance.

Results

For individual DWI-derived parameters, all parameters except the pseudodiffusion coefficient displayed the capability of grading rectal cancer (p < 0.05). The better discrimination between high- and low-grade rectal cancer was achieved with the combination of different DWI-derived parameters. Similarly, ROC analysis suggested the combination of D (true diffusion coefficient), f (perfusion fraction), and K_app (apparent kurtosis coefficient) yielded the best diagnostic performance (AUC = 0.953, p < 0.001). According to the result of binary logistic analysis, cellularity-related D was the most sensitive predictor (odds ratio: 9.350 ± 2.239) for grading rectal cancer.

Conclusion

The combination of IVIM and DKI holds great potential in accurately grading rectal cancer as IVIM and DKI can provide the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity.

Manual and semi-automated delineation of locally advanced rectal cancer subvolumes with diffusion-weighted MRI

OBJECTIVES

To evaluate interobserver agreement for T₂ weighted (T₂W) and diffusion-weighted MRI (DW-MRI) contours of locally advanced rectal cancer (LARC); and to evaluate manual and semi-automated delineations of restricted diffusion tumour subvolumes.

METHODS

20 cases of LARC were reviewed by 2 radiation oncologists and 2 radiologists. Contours of gross tumour volume (GTV) on T₂W, DW-MRI and co-registered T₂W/DW-MRI were independently delineated and compared using Dice Similarity Coefficient (DSC), mean distance to agreement (MDA) and other metrics of interobserver agreement. Restricted diffusion subvolumes within GTVs were manually delineated and compared to semi-automatically generated contours corresponding to intratumoral apparent diffusion coefficient (ADC) centile values.

RESULTS

Observers were able to delineate subvolumes of restricted diffusion with moderate agreement (DSC 0.666, MDA 1.92 mm). Semi-automated segmentation based on the 40th centile intratumoral ADC value demonstrated moderate average agreement with consensus delineations (DSC 0.581, MDA 2.44 mm), with errors noted in image registration and luminal variation between acquisitions. A small validation set of four cases with optimised planning MRI demonstrated improvement (DSC 0.669, MDA 1.91 mm).

CONCLUSION

Contours based on co-registered T₂W and DW-MRI could be used for delineation of biologically relevant tumour subvolumes. Semi-automated delineation based on patient-specific intratumoral ADC thresholds may standardise subvolume delineation if registration between acquisitions is sufficiently accurate.

ADVANCES IN KNOWLEDGE

This is the first study to evaluate the feasibility of semi-automated diffusion-based subvolume delineation in LARC. This approach could be applied to dose escalation or 'dose painting' protocols to improve delineation reproducibility.

Value of intravoxel incoherent motion magnetic resonance imaging for differentiating metastatic from nonmetastatic mesorectal lymph nodes with different short-axis diameters in rectal cancer

Background

Conventional magnetic resonance imaging (MRI) does not accurately evaluate lymph node (LN) status, which is essential for the treatment and prognosis assessment in patients with rectal cancer.

Objective

The aim of this study is to evaluate the diagnostic value of intravoxel incoherent motion (IVIM) MRI in differentiating metastatic and nonmetastatic mesorectal LNs with different short-axis diameters in rectal cancer patients.

Materials and Methods

Forty patients (154 LNs) were divided into three groups based on short-axis diameter: 3 mm ≤ × ≤5 mm, 5 mm < × ≤7 mm, and × >7 mm. MRI characteristics and IVIM parameters were compared between the metastatic and nonmetastatic LNs to determine the diagnostic value for discriminating them.

Results

In the 3 mm ≤ × ≤ 5 mm group, mean D values were significantly lower in metastatic than in the nonmetastatic LNs (P < 0.001). In the 5 mm < × ≤7 mm group, mean f values were significantly lower in metastatic than nonmetastatic LNs (P < 0.05). In the × >7 mm group, only the short-axis diameter of metastatic LNs was significantly greater than that of nonmetastatic LNs (P < 0.05). The area under the curve, sensitivity, specificity, and cutoff values were used for differentiating the metastatic from the nonmetastatic LNs.

Conclusion

IVIM parameters can differentiate metastatic from nonmetastatic LNs with smaller short-axis diameters (× ≤7 mm) in rectal cancer, and the short-axis diameter is a significant factor in identifying metastatic and nonmetastatic LNs in larger short-axis diameter groups (× >7 mm).

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

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.

Comparative Analysis of Amide Proton Transfer MRI and Diffusion-Weighted Imaging in Assessing p53 and Ki-67 Expression of Rectal Adenocarcinoma

BACKGROUND

The evaluation of prognostic factors in rectal carcinoma patients has important clinical significance. P53 status and the Ki-67 index have served as prognostic factors in rectal carcinoma. Amide proton transfer (APT) imaging has shown great potential in tumor diagnosis. However, few studies reported the value of APT imaging in evaluating p53 and Ki-67 status of rectal carcinoma.

PURPOSE

To investigate the feasibility of amide proton transfer MRI in assessing p53 and Ki-67 expression of rectal adenocarcinoma, and compare it with conventional diffusion-weighted imaging (DWI).

STUDY TYPE

Retrospective.

POPULATION

Forty-three patients with rectal adenocarcinoma (age: 34-85 years).

FIELD STRENGTH/SEQUENCE

3T/APT imaging using a 3D turbo spin echo (TSE)-Dixon pulse sequence with chemical shift-selective fat suppression, 2D DWI, and 2D T₂ -weighted TSE.

ASSESSMENT

Mean tumor APT signal intensity (SI_mean ) and apparent diffusion coefficient (ADC_mean ) were measured. Traditional tumor pathological analysis included WHO grades, pT (pathologic tumor) stages, and pN (pathologic node) stages. Expression levels of p53 and Ki-67 were determined by immunohistochemical assay.

STATISTICAL TESTS

One-way analysis of variance (ANOVA); Student's t-test; Spearman's correlation coefficient; receiver operating characteristic (ROC) curve analysis.

RESULTS

High-grade tumors, more advanced stage tumors, and tumors with lymph node involvement had higher APT SI_mean values: high grade (n = 15) vs. low-grade (n = 28), P < 0.001; pT2 (n = 10) vs. pT3 (n = 20) vs. pT4 (N = 13), P = 0.021; pN0 (n = 24) vs. pN1-2 (n = 19), P = 0.019. ADC_mean differences were found in tumors with different pT stage: pT2 (n = 10) vs. pT3 (n = 20) vs. pT4 (N = 13), P = 0.013, but not in tumors with different histologic grade: high grade (n = 15) vs. low-grade (n = 28), P = 0.3536; or pN stage: pN0 (n = 24) vs. pN1-2 (n = 19), P = 0.624. Tumor with p53 positive status had higher APT SI_mean than tumor with negative p53 status (2.363 ± 0.457 vs. 2.0150 ± 0.3552, P = 0.014). There was no difference in ADC_mean with p53 status (1.058 ± 0.1163 10^-3  mm² /s vs. 1.055 ± 0.128 10^-3  mm² /s, P = 0.935). APT SI_mean and ADC_mean were significantly different in tumors with low and high Ki-67 status (1.7882 ± 0.11386 vs. 2.3975 ± 0.41586, P < 0.001; 1.1741 ± 0.093 10^-3  mm² /s vs. 1.0157 ± 0.10459 10^-3  mm² /s, P < 0.001, respectively). APT SI_mean exhibited a positive correlation with p53 labeling index and Ki-67 labeling index (r = 0.3741, P = 0.0135; r = 0.7048; P < 0.001, respectively). ADC_mean showed no correlation with p53 labeling index, but a negative correlation with Ki-67 labeling index (r = -0.5543, P < 0.0001). ROC curves demonstrated that APT SI_mean had significantly higher diagnostic ability for differentiation of high Ki-67 expression of rectal adenocarcinoma than ADC_mean (81.2% vs. 78.12%, 90.91% vs. 63.64; P < 0.001 vs. P = 0.017), while no difference was found in predicting p53 status (92.86% vs. 71.4%, 53.33% vs. 66.7%; P < 0.001 vs. P = 0.0471).

DATA CONCLUSION

APT SI_mean was related to p53 and Ki-67 expression levels in rectal adenocarcinoma. APT imaging may serve as a noninvasive biomarker for assessing genetic prognostic factors of rectal adenocarcinoma.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

A novel bayesian approach with conditional autoregressive specification for intravoxel incoherent motion diffusion-weighted MRI

The Intra-Voxel Incoherent Motion (IVIM) model is largely adopted to estimate slow and fast diffusion coefficients of water molecules in biological tissues, which are used in cancer applications. The most reported fitting approach is a voxel-wise segmented non-linear least square, whereas Bayesian approaches with a direct fit, also considering spatial regularization, were proposed too. In this work a novel segmented Bayesian method was proposed, also in combination with a spatial regularization through a Conditional Autoregressive (CAR) prior specification. The two segmented Bayesian approaches, with and without CAR specification, were compared with two standard least-square and a direct Bayesian fitting methods. All approaches were tested on simulated images and real data of patients with head-and-neck and rectal cancer. Estimation accuracy and maps noisiness were quantified on simulated images, whereas the coefficient of variation and the goodness of fit were evaluated for real data. Both versions of the segmented Bayesian approach outperformed the standard methods on simulated images for pseudo-diffusion (D^∗ ) and perfusion fraction (f), whilst the segmented least-square fitting remained the less biased for the diffusion coefficient (D). On real data, Bayesian approaches provided the less noisy maps, and the two Bayesian methods without CAR generally estimated lower values for f and D^∗ coefficients with respect to the other approaches. The proposed segmented Bayesian approaches were superior, in terms of estimation accuracy and maps quality, to the direct Bayesian model and the least-square fittings. The CAR method improved the estimation accuracy, especially for D^∗ .

Value of Apparent Diffusion Coefficient for Assessing Preoperative T Staging of Low Rectal Cancer and Whether This Is Correlated With Ki-67 Expression

PURPOSE

To explore the value of the apparent diffusion coefficient (ADC) in assessing preoperative T staging of low rectal cancer and the correlation between ADC value and Ki-67 expression.

METHODS

Data on 77 patients with a proven pathology of low rectal cancer were retrospectively analyzed. All patients underwent a magnetic resonance imaging scan 1 week prior to operation, and the mean ADC value was measured. All tumors were fully removed, and pathologic staging was determined. The Ki-67 expression was determined using immunohistochemical methods in all patients. The correlation between Ki-67 expression and ADC features was studied.

RESULTS

A total of 77 patients with low rectal cancer were included in the study. The pathology type was adenocarcinoma. The numbers of patients with pathological stages T1, T2, T3, and T4 were 9, 23, 32, and 13, respectively. The ADC value of all tumors ranged from 0.60 to 1.20 mm²/s. The average Ki-67 proliferation index was 55.3% ± 20.2%. A significant difference was observed between the preoperative ADC value and pathological T staging of low rectal cancer (P < .01). The more advanced the T stage, the lower the detected ADC values were. A negative correlation was noted between the preoperative ADC value and Ki-67 proliferation index of rectal cancer (r = -0.71, P < .01). When the Ki-67 proliferation index increased, lower ADC values were detected.

CONCLUSION

The ADC values can provide useful information on preoperative tumor staging and may facilitate evaluation of the biological behavior of low rectal cancer. The ADC values should be considered a sensitive image biomarker of rectal cancer.

Role of intravoxel incoherent motion MRI in preoperative evaluation of DNA mismatch repair status in rectal cancers

AIM

To explore the role of intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in evaluating DNA mismatch repair (MMR) status of rectal cancers preoperatively.

MATERIALS AND METHODS

Seventy-six patients with a diagnosis of rectal cancer confirmed at endoscopic biopsy were enrolled prospectively and underwent IVIM MRI before surgery.

RESULTS

The perfusion fraction (f) values of MMR proteins (MMRP) positive rectal cancers were significantly higher than negative cancers. The f values could differentiate MMRP positive rectal cancers from negative cancers with an area under the curve (AUC) of 0.695. The vascular endothelial growth factor (VEGF) and vascular endothelial growth factor receptor 2 (VEGFR2) expression rates of positive MMRP rectal cancers were significantly higher than negative cancers.

CONCLUSION

This pilot study indicated that the f value derived from IVIM MRI differed significantly between rectal cancers with different MMRP expression levels, which might be involved with different VEGF and VEGFR2 expression rates.

Correlation of apparent diffusion coefficient and intravoxel incoherent motion imaging parameters with Ki-67 expression in extrahepatic cholangiocarcinoma

PURPOSE

To investigate the correlation of magnetic resonance imaging (MRI), apparent diffusion coefficient (ADC) and intravoxel incoherent motion imaging parameters with Ki-67 expression in cholangiocarcinoma.

METHODS

A total of 42 extrahepatic cholangiocarcinoma (EHCC) cases confirmed by surgical pathology were analyzed retrospectively. Subjects underwent MRI at 3.0 T and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) sequential scanning prior to surgery, and postoperative Ki-67 expression was recorded by immunohistochemistry (IHC). The patients were divided into 4 groups (I-IV) based on increasing Ki-67 expression from - to +++. ADC values and IVIM-DWI parameters were calculated, including true diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*). The comparison among groups was analyzed by univariate ANOVA (normal distribution) or Kruskal-Wallis H (non-normal distribution). Spearman correlation analysis was used to analyze the correlation of each parameter with Ki-67 expression. The diagnostic efficiency of each parameter was compared using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

RESULTS

Except for D*, other values had statistically significant differences between groups (P < 0.05). ADC, D and f values had negative correlations with Ki-67 expression (r values were -0.607, -0.795, -0.531, respectively, P < 0.05). The AUCs were 0.701, 0.880, 0.623, respectively (P < 0.0001).

CONCLUSION

IVIM-DWI technology can reflect the proliferative activity of EHCC cells to a certain extent, and has clinical value for predicting the degree of malignancy of a tumor.

Intravoxel Incoherent Motion MR Imaging of Pediatric Intracranial Tumors: Correlation with Histology and Diagnostic Utility

BACKGROUND AND PURPOSE

Intravoxel incoherent motion imaging, which simultaneously measures diffusion and perfusion parameters, is promising for brain tumor grading. However, intravoxel incoherent motion imaging has not been tested in children. The purpose of this study was to evaluate the correlation between intravoxel incoherent motion parameters and histology to assess the accuracy of intravoxel incoherent motion imaging for pediatric intracranial tumor grading.

MATERIALS AND METHODS

Between April 2013 and September 2015, 17 children (11 boys, 6 girls; 2 months to 15 years of age) with intracranial tumors were included in this retrospective study. Intravoxel incoherent motion parameters were fitted using 13 b-values for a biexponential model. The perfusion-free diffusion coefficient, pseudodiffusion coefficient, and perfusion fraction were measured in high- and low-grade tumors. These intravoxel incoherent motion parameters and the ADC were compared using the unpaired t test. The correlations between the intravoxel incoherent motion parameters and microvessel density or the MIB-1 index were analyzed using the Spearman correlation test. Receiver operating characteristic analysis was used to evaluate diagnostic performance.

RESULTS

The perfusion-free diffusion coefficient and ADC were lower in high-grade than in low-grade tumors (perfusion-free diffusion coefficient, 0.85 ± 0.40 versus 1.53 ± 0.21 × 10^-3 mm²/s, P < .001; ADC, 1.04 ± 0.33 versus 1.60 ± 0.21 × 10^-3 mm²/s, P < .001). The pseudodiffusion coefficient showed no difference between the groups. The perfusion fraction was higher in high-grade than in low-grade tumors (21.7 ± 8.2% versus 7.6 ± 4.3%, P < .001). Receiver operating characteristic analysis found that the combined perfusion-free diffusion coefficient and perfusion fraction had the best diagnostic performance for tumor differentiation (area under the curve = 0.986).

CONCLUSIONS

Intravoxel incoherent motion imaging reflects tumor histology and may be a helpful, noninvasive method for pediatric intracranial tumor grading.

Diffusion-weighted imaging in rectal cancer: current applications and future perspectives

This review summarizes current applications and clinical utility of diffusion-weighted imaging (DWI) for rectal cancer and in addition provides a brief overview of more recent developments (including intravoxel incoherent motion imaging, diffusion kurtosis imaging, and novel postprocessing tools) that are still in more early stages of research. More than 140 papers have been published in the last decade, during which period the use of DWI have slowly moved from mainly qualitative (visual) image interpretation to increasingly advanced methods of quantitative analysis. So far, the largest body of evidence exists for assessment of tumour response to neoadjuvant treatment. In this setting, particularly the benefit of DWI for visual assessment of residual tumour in post-radiation fibrosis has been established and is now increasingly adopted in clinics. Quantitative DWI analysis (mainly the apparent diffusion coefficient) has potential, both for response prediction as well as for tumour prognostication, but protocols require standardization and results need to be prospectively confirmed on larger scale. The role of DWI for further clinical tumour and nodal staging is less well-defined, although there could be a benefit for DWI to help detect lymph nodes. Novel methods of DWI analysis and post-processing are still being developed and optimized; the clinical potential of these tools remains to be established in the upcoming years.

How clinical imaging can assess cancer biology

Human cancers represent complex structures, which display substantial inter- and intratumor heterogeneity in their genetic expression and phenotypic features. However, cancers usually exhibit characteristic structural, physiologic, and molecular features and display specific biological capabilities named hallmarks. Many of these tumor traits are imageable through different imaging techniques. Imaging is able to spatially map key cancer features and tumor heterogeneity improving tumor diagnosis, characterization, and management. This paper aims to summarize the current and emerging applications of imaging in tumor biology assessment.

A histogram analysis of diffusion and perfusion features of cervical cancer based on intravoxel incoherent motion magnetic resonance imaging

OBJECTIVE

To evaluate the diagnostic potential based on histogram analysis of IVIM parameters between uterine cervical cancers (CC) - normal myometrium (Myo) versus CC - gluteus maximus muscle (GM) and to study the feasibility of histogram analysis of IVIM parameters to differentiate the early from locally advanced stage CCs.

METHODS

64 patients with pathologically confirmed CC were enrolled. Histogram indices mean, median, 25th, and ð 75th percentile of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) value of entire tumor were statistically analyzed and compared between CC - GM versus CC - Myo, as well as between early and locally advanced stage CCs. A multivariate analysis was performed to identify indices that could best distinguish early from locally advanced stage CC. Receiver operating characteristic curves (ROC) were used to evaluate the diagnostic efficiency of every histogram parameter.

RESULTS

All the tested histogram indices significantly differed between the patients with CC - GM vs. CC - Myo, nonetheless, CC - GM yielded higher range area under the curve (AUC) value of 0.8-0.99 vs. 0.6-0.99. The additional significant difference was found among all the tested histogram indices of D*, mean, median, and 75th percentile of f, mean and 75th percentile of ADC, and 75th percentile of D discriminating early from locally advanced CCs. ROC curves indicated that the 75th percentile of D* value 28.17 × 10^-3 mm²/s could best differentiate early from locally advanced stage CCs, with AUC of 0.776. In the multivariate analysis, ROC indicated the 50th percentile of D* and f was the most significant with AUCs of 0.856.

CONCLUSIONS

The histogram analysis of IVIM parameters depicted that gluteus maximus served better reference tissue in comparison to myometrium. The histogram index 75th percentile of ADC, D, D*, and f may serve a diagnostic biomarker to differentiate the early from locally advanced stage CCs.

Histogram parameters derived from T2 weighted images are associated with histopathological findings in rectal cancer - a preliminary study

Histogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram parameters derived from T2 weighted images and histopathological features in rectal cancer. Seventeen patients with histopathological proven rectal adenocarcinoma were retrospectively acquired with prebioptic 3 T MRI and available histopathological specimens. Histogram analysis was performed using an in-house matlab tool conducting a whole lesion measurement. Histopathology was investigated using Ki67 specimens with calculation of Ki67-index as well as cellularity and nucleic areas and CD31 specimens, with estimation of microvessel density. Several histogram parameters correlated with average nucleic area. Skewness showed a moderate correlation with microvessel density (P = 0.54, P = 0.02). None of the parameters correlated with Ki67-index. Skewness derived from T2 weighted images might be used as a surrogate parameter for average nucleic area and microvessel density. However, none of the parameters were associated with proliferation index.

An evidence-based approach to assess the accuracy of intravoxel incoherent motion imaging for the grading of brain tumors

BACKGROUND

Differentiation of high-grade gliomas (HGGs) and low-grade gliomas (LGGs) is an important clinical problem because treatment strategies vary greatly. This study was performed to investigate the potential diagnostic value of incoherent intravoxel motion imaging (IVIM) to distinguish HGG from LGG by meta-analysis.

METHODS

A computerized search of the literature was performed using the free-access PubMed database, Web of Science, and Chinese biomedical database, and relevant articles until September 18, 2018 that used IVIM to distinguish HGG from LGG were included. All analyses were performed using Review Manager 5.3 and Stata. Mean difference (MD) at 95% confidence interval (CI) of the apparent diffusion coefficient (ADC), diffusion coefficient value (D), perfusion fraction value (f), and perfusion coefficient value (D*) were summarized.

RESULTS

Nine studies were used for general data pooling. In the tumor parenchyma (TP) regions, subgroup analysis revealed D* in HGG is higher than in LGG (MD = 1.19, P = .002), and D in HGG is lower than in LGG (MD = -1.06, P = .001). However, no significant difference in f (MD = 0.89, P = .056) was detected between HGG and LGG. In the white matter regions, HGG had higher D* (MD = 0.76, P = .04) compared with LGG, while no marked differences between the D value (P = .07) and f (P = .09) values.

CONCLUSION

The present meta-analysis shows that the ADC, D, and D* values derived from IVIM may be useful in differentiating HGG from LGG. Considering the small sample of this study, we need to be cautious when interpreting the results of this study. Other prospective and large-sample randomized controlled trials were needed to establish the value of IVIM in differentiating HGG from LGG.

Could intravoxel incoherent motion diffusion-weighted magnetic resonance imaging be feasible and beneficial to the evaluation of gastrointestinal tumors histopathology and the therapeutic response?

Gastrointestinal tumors (GTs) are among the most common tumors of the digestive system and are among the leading causes of cancer death worldwide. Functional magnetic resonance imaging (MRI) is crucial for assessment of histopathological changes and therapeutic responses of GTs before and after chemotherapy and radiotherapy. A new functional MRI technique, intravoxel incoherent motion (IVIM), could reveal more detailed useful information regarding many diseases. Currently, IVIM is widely used for various tumors because the derived parameters (diffusion coefficient, D; pseudo-perfusion diffusion coefficient, D*; and perfusion fraction, f) are thought to be important surrogate imaging biomarkers for gaining insights into tissue physiology. They can simultaneously reflect the microenvironment, microcirculation in the capillary network (perfusion) and diffusion in tumor tissues without contrast agent intravenous administration. The sensitivity and specificity of these parameters used in the evaluation of GTs vary, the results of IVIM in GTs are discrepant and the variability of IVIM measurements in response to chemotherapy and/or radiotherapy in these studies remains a source of controversy. Therefore, there are questions as to whether IVIM diffusion-weighted MRI is feasible and helpful in the evaluation of GTs, and whether it is worthy of expanded use.

Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma

Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC).

30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of K_trans, V_e, and K_ep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters.

KI 67 correlated with K_trans min (p = −0.386, P = 0.043) and s K_trans skewness (p = 0.382, P = 0.045), V_e min (p = −0.473, P = 0.011), Ve entropy (p = 0.424, P = 0.025), and K_ep entropy (p = 0.464, P = 0.013). Cell count correlated with K_trans kurtosis (p = 0.40, P = 0.034), V_e entropy (p = 0.475, P = 0.011). Total nucleic area correlated with V_e max (p = 0.386, P = 0.042) and V_e entropy (p = 0.411, P = 0.030).

In G1/2 tumors, only K_trans entropy correlated well with total (P =0.78, P =0.013) and average nucleic areas (p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min (p = −0.552, P = 0.022) and V_e entropy (p = 0.524, P = 0.031). Ve max correlated with total nucleic area (p = 0.483, P = 0.049). Kep max correlated with total area (p = −0.51, P = 0.037), and K_ep entropy with KI 67 (p = 0.567, P = 0.018).

We concluded that histogram-based parameters skewness, kurtosis and entropy of K_trans, V_e, and K_ep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10^-3mm²/s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.

Intravoxel Incoherent Motion MRI of Rectal Cancer: Correlation of Diffusion and Perfusion Characteristics With Prognostic Tumor Markers

OBJECTIVE

The objective of our study was to evaluate the intravoxel incoherent motion (IVIM)-DWI derived parameters and their relationships with tumor prognostic markers using 3-T MRI in patients with rectal cancer.

SUBJECTS AND METHODS

Fifty-two patients with histopathologically proven rectal cancer who underwent preoperative pelvic MRI were prospectively enrolled in this study. Diffusion and perfusion parameters including the apparent diffusion coefficient (ADC), pure diffusion coefficient, perfusion fraction, and pseudodiffusion coefficient derived from IVIMDWI were independently measured by two radiologists. Comparisons of IVIM-DWI-derived parameters in patients with different tumor prognostic markers were made using the independent-samples t test, ANOVA, and Mann-Whitney U test. The correlations between IVIM-DWI-derived parameters and tumor grade and tumor stage were further evaluated using Spearman correlation analysis. Interobserver agreement was evaluated using the intraclass correlation coefficient (ICC).

RESULTS

Excellent interobserver reproducibility was obtained for the IVIM-DWI-derived parameters (range of ICCs with 95% limits of agreement = 0.9309-0.9948, which is narrow). ADC, pseudodiffusion coefficient, and perfusion fraction tended to rise with greater tumor differentiation (r = 0.520, p < 0.001; r = 0.447, p = 0.001; r = 0.354, p = 0.010, respectively). The pure diffusion coefficient and pseudodiffusion coefficient showed a trend of decreasing with increasing tumor stages (r = 0.479, p < 0.001; r = 0.517, p < 0.001). The group of patients with extramural vascular invasion (EMVI) showed lower pseudodiffusion coefficient values than the group of patients with no EMVI (p < 0.05).

CONCLUSION

IVIM-DWI-derived parameters in patients with rectal cancer, especially the pseudodiffusion coefficient, are associated with tumor grade and tumor stage and show statistically significant differences between subjects with EMVI and those without EMVI. IVIM-DWI-derived parameters would be helpful in predicting tumor aggressiveness and prognosis.

Intrahepatic cholangiocarcinoma in the setting of HBV-related cirrhosis: Differentiation with hepatocellular carcinoma by using Intravoxel incoherent motion diffusion-weighted MR imaging

Accurate preoperative differentiation of intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) in the setting of cirrhotic liver is of great clinical significance because the treatment and prognosis of these entities differ markedly. Through a retrospectively research, we sought to determine the diagnostic performances of intravoxel incoherent motion (IVIM) and diffusion weighted imaging (DWI) parameters in the differentiating of ICC and HCC. According to the results, we found that apparent diffusion coefficient (ADC) derived from mono-exponential model and true ADC (ADC^slow) derived from bi-exponential model can be used to distinguish the ICC and HCC, and ADC^slowentailed the higher diagnostic performance than ADC. However, pseudo-ADC (ADC^fast) and perfusion fraction (f) can not be used to differentiate ICC and HCC. These results suggested that IVIM and DWI parameters can be useful in differentiating ICC and HCC and might be helpful in selecting the treatment plan and predicting prognosis.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 2: ADCmin

The purpose of this part of the meta-analysis was to summarize data regarding associations between minimum apparent diffusion coefficient (ADC_min) and KI 67 in different tumors. MEDLINE library was screened for associations between ADC_min and KI 67 in different tumors up to April 2017. Overall, 23 studies with 944 patients were identified. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The pooled correlation coefficient between ADC_min and KI 67 for all included tumors was ρ = -0.47. In detail, the correlation coefficients for separate tumors were as follows: cerebral lymphoma: ρ = -0.61 (95% CI = [-0.82; -0.41]); cervical cancer: ρ = -0.56 (95% CI = [-0.68;-0.43]); pituitary adenoma: ρ = -0.55 (95% CI = [-1.31; 0.22]); glioma: ρ = -0.40 (95% CI = [-0.55; -0.24]); breast cancer: ρ = -0.37 (95% CI = [-0.74; -0.01]); meningioma, ρ = -0.15 (95% CI = [-0.38; 0.07]).

Proving of a Mathematical Model of Cell Calculation Based on Apparent Diffusion Coefficient

OBJECTIVES: Recently, Atuegwu et al. proposed a mathematical model based on ADC_mean and ADC_min to calculation of cellularity. Our purpose was to compare the calculated cellularity according to the formula with the estimated cell count by histopathology in different tumors. METHODS: For this study, we re-analyzed our previous data regarding associations between ADC parameters and histopathological findings. Overall, 134 patients with different tumors were acquired for the analysis. For all tumors, the number of tumor cells was calculated according to Atuegwu et al. 2013. We performed a correlation analysis between the calculated and estimated cellularity. Thereby, Pearson's correlation coefficient was used and P < .05 was taken to indicate statistical significance in all instances. RESULTS: The estimated and calculated cellularity correlated well together in HNSCC (r = 0.701, P = .016) and lymphomas (r = 0.661, P = .001), and moderately in rectal cancer (r = 0.510, P = .036). There were no statistically significant correlations between the estimated and calculated cellularity in uterine cervical cancer, meningiomas, and in thyroid cancer. CONCLUSION: The proposed formula for cellularity calculation does not apply for all tumors. It may be used for HNSCC, cerebral lymphomas and rectal cancer, but not for uterine cervical cancer, meningioma, and thyroid cancer. Furthermore, its usefulness should be proved for other tumors.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean

Diffusion weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion in tissues. This diffusion can be quantified by apparent diffusion coefficient (ADC). Some reports indicated that ADC can reflect tumor proliferation potential. The purpose of this meta-analysis was to provide evident data regarding associations between ADC and KI 67 in different tumors. Studies investigating the relationship between ADC and KI 67 in different tumors were identified. MEDLINE library was screened for associations between ADC and KI 67 in different tumors up to April 2017. Overall, 42 studies with 2026 patients were identified. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The reported Pearson correlation coefficients in some studies were converted into Spearman correlation coefficients. The pooled correlation coefficient between ADC_mean and KI 67 for all included tumors was ρ = -0.44. Furthermore, correlation coefficient for every tumor entity was calculated. The calculated correlation coefficients were as follows: ovarian cancer: ρ = -0.62, urothelial carcinomas: ρ = -0.56, cerebral lymphoma: ρ = -0.55, neuroendocrine tumors: ρ = -0.52, glioma: ρ = -0.51, lung cancer: ρ = -0.50, prostatic cancer: ρ = -0.43, rectal cancer: ρ = -0.42, pituitary adenoma:ρ = -0.44, meningioma, ρ = -0.43, hepatocellular carcinoma: ρ = -0.37, breast cancer: ρ = -0.22.