Associations between IVIM histogram parameters and histopathology in rectal cancer

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.

Correlation between IVIM parameters and microvessel architecture: direct comparison of MRI images and pathological slices in an orthotopic murine model of rhabdomyosarcoma

OBJECTIVE

This study aimed to explore the correlation between intravoxel incoherent motion (IVIM) parameters and microvessel architecture (microvessel density (MVD), vasculogenic mimicry (VM), and pericyte coverage index (PCI)) in an orthotopic murine model of rhabdomyosarcoma.

METHODS

The murine model was established by injecting rhabdomyosarcoma-derived (RD) cells into the muscle. Nude mice underwent routine magnetic resonance imaging (MRI) and IVIM examinations with ten b values (0, 50, 100, 150, 200, 400, 600, 800, 1000, and 2000 s/mm2). D, D*, and f values were calculated with the ADW4.7 workstation. MRI images and pathological slices were directly compared to ensure that radiology parameters accurately reflect pathology. MVD, VM, PCI, and cellularity were obtained by histological analysis. The correlations were assessed between IVIM parameters (D, D*, f, and fD* values) and pathological markers (MVD, VM, PCI, and cellularity).

RESULTS

The average of D, D*, f, and fD* values were 0.55 ± 0.07 × 10-3 mm2/s, 5.25 ± 0.73 × 10-3 mm2/s, 13.39 ± 7.68%, and 0.73 ± 0.49 × 10-3 mm2/s, respectively. The average of MVD, VM, PCI, and cellularity were 41.91 ± 10.98, 1.16 ± 0.83, 0.49 ± 0.18, and 39.15 ± 9.00%. D*, f, and fD* values showed a positive correlation with MVD separately, while the D value did not correlate with MVD. D value negatively correlated to VM moderately, and other parameters did not associate with VM. D* and fD* values were positively correlated with PCI, but no correlation was observed between other parameters and PCI.

CONCLUSIONS

IVIM may evaluate the tumor microvessel architecture. D*, f, and fD* may reflect the endothelial lining blood vessel; D could indirectly reflect the VM; D* and fD* could reflect PCI(the normal degree of the tumor blood vessel).

CLINICAL RELEVANCE STATEMENT

An intravoxel incoherent motion may be useful in assessing rhabdomyosarcoma microvessel structure to predict the target and effectiveness of anti-angiogenic therapy.

KEY POINTS

• IVIM may be used to evaluate the tumor microvessel architecture in the mouse rhabdomyosarcoma model. • The MRI-pathology control method achieves correspondence between MRI slices and pathology slices, which ensures the consistency of the ROI of MRI and the pathology observation region.

Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology

Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncological applications of body imaging, where new biomarkers are urgently needed. The objective of this article is to review the state-of-the-art of DW-MRI in body imaging (ie, not including the nervous system) in oncology, and to analyze its value as compared to reference colocalized histology measurements, given that demonstrating the histological validity of any new DW-MRI method is essential. In this article, we review the current landscape of DW-MRI techniques that extend standard apparent diffusion coefficient (ADC), describing their acquisition protocols, signal models, fitting settings, microstructural parameters, and relationship with histology. Preclinical, clinical, and in/ex vivo studies were included. The most used techniques were intravoxel incoherent motion (IVIM; 36.3% of used techniques), diffusion kurtosis imaging (DKI; 16.7%), vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT; 13.3%), and imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED; 11.7%). Another notable category of techniques relates to innovative b-tensor diffusion encoding or joint diffusion-relaxometry. The reviewed approaches provide histologically meaningful indices of cancer microstructure (eg, vascularization/cellularity) which, while not necessarily accurate numerically, may still provide useful sensitivity to microscopic pathological processes. Future work of the community should focus on improving the inter-/intra-scanner robustness, and on assessing histological validity in broader contexts. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 2.

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.

Intravoxel incoherent motion imaging used to assess tumor microvascular changes after transarterial chemoembolization in a rabbit VX2 liver tumor model

Purpose

To evaluate the correlation between microvascular density (MVD) and intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) parameters and the effect of glycolytic flux after transarterial chemoembolization (TACE) in a rabbit VX2 liver tumor.

Materials and methods

VX2 liver tumor allografts in 15 New Zealand white rabbits were treated with sterile saline (control group, n = 5) or lipiodol-doxorubicin emulsion (experimental group, n = 10). MRI was performed 2 weeks after the procedure to evaluate IVIM parameters, including apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (PF). All animal samples were taken of the tumor and surrounding liver. Immunostaining for CD31, CD34, CD105, and VEGF was used to evaluate MVD. The protein expression of Glut4, HK2, PKM2, LDHA, and MCT1 was determined using western blotting. Pearson correlation tests were used to analyze the relationship between MVD and IVIM parameters.

Results

D* value in the peritumoral region was negatively correlated with CD34 (r = -0.71, P = 0.01). PF value positively correlated with CD34 (r = 0.68, P = 0.015), CD105 (r = 0.76, P = 0.004) and VEGF (r = 0.72, P = 0.008) in the peritumoral region. Glut4, HK2, PKM2, and MCT1 in the peritumoral regions were higher in the experimental group than in the control group (all P < 0.05).

Conclusion

IVIM parameters were correlated with MVD in the intratumoral and peritumoral regions after TACE in a rabbit liver tumor model. The angiogenesis reflected by MVD may be related to changes of glycolytic flux.

Dynamic Contrast-Enhanced Ultrasound Modeling of an Analog to Pseudo-Diffusivity in Intravoxel Incoherent Motion Magnetic Resonance Imaging

Tumor perfusion and vascular properties are important determinants of cancer response to therapy and thus various approaches for imaging perfusion are being explored. In particular, Intravoxel Incoherent Motion (IVIM) MRI has been actively researched as an alternative to Dynamic-Contrast-Enhanced (DCE) CT and DCE-MRI as it offers non-ionizing, non-contrast-based perfusion imaging. However, for repetitive treatment assessment in a short time period, high cost, limited access, and inability to scan at the bedside remain disadvantages of IVIM MRI. We propose an analysis framework that may enable 3D DCE Ultrasound (DCE-US) - low cost, bedside imaging with excellent safety record - as an alternative modality to IVIM MRI for the generation of DCE-US based pseudo-diffusivity maps in acoustically accessible anatomy and tumors. Modelling intravascular contrast propagation as a convective-diffusive process, we reconstruct parametric maps of pseudo-diffusivity by solving a large-scale fully coupled inverse problem without any assumptions regarding local constancy of the reconstructed parameters. In a mouse tumor model, we demonstrate that the 3D DCE-US pseudo-diffusivity is repeatable, sensitive to treatment with an antiangiogenic agent, and moderately correlated to histological measures of perfusion and angiogenesis.

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.

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.

Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study

Background

To explore the value of the quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in assessing preoperative extramural venous invasion (EMVI) in rectal cancer.

Methods

Eighty-two rectal adenocarcinoma patients who had underwent MRI preoperatively were enrolled in this study. The differences in quantitative DCE-MRI and DWI parameters including Krans, Kep and ADC values were analyzed between MR-detected EMVI (mrEMVI)-positive and -negative groups. Multivariate logistic regression analysis was performed to build the combined prediction model for pathologic EMVI (pEMVI) with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) curve.

Results

Of the 82 patients, 24 were mrEMVI-positive and 58 were -negative. In the mrEMVI positive group, the Ktrans and Kep values were significantly higher than those in the mrEMVI negative group (P < 0.01), but the ADC values were significantly lower (P < 0.01). A negative correlation was observed between the Ktrans vs ADC values and Kep vs ADC values in patients with rectal cancer. Among the four quantitative parameters, Ktrans and ADC value were independently associated with mrEMVI by multivariate logistic regression analysis. ROC analysis showed that combined prediction model based on quantitative DCE parameters and ADC values had a good prediction efficiency for pEMVI in rectal cancer.

Conclusion

The quantitative DCE-MRI parameters, Krans, Kep and ADC values play important role in predicting EMVI of rectal cancer, with Ktrans and ADC value being independent predictors of EMVI in rectal cancer.

Associations Between ADC and Tumor Infiltrating Lymphocytes, Tumor-Stroma Ratio and Vimentin Expression in Head and Neck Squamous Cell Cancer

RATIONALE AND OBJECTIVES

The present study used diffusion-weighted imaging (DWI) to elucidate possible associations with tumor-infiltrating lymphocytes (TIL), tumor-stroma ratio and vimentin expression in head and neck squamous cell cancer (HNSCC).

MATERIALS AND METHODS

30 patients with primary HNSCC of different localizations were involved in the study. DWI was obtained on a 3 T scanner. Apparent diffusion coefficients (ADC) images were analyzed with a whole lesion measurement using a histogram approach. TIL- and vimentin-expression was calculated on biopsy samples before any form of treatment.

RESULTS

Tumor-stroma ratio correlated with ADC kurtosis (r = 0.46, p = 0.01) and ADC skewness (r = 0.42, p = 0.02). Several ADC parameters were significantly different between stroma rich und tumor rich tumors. ADC entropy correlated significantly with the expression of TIL within the tumor compartment (r = 0.44, p = 0.01). No associations were identified between ADC parameters and vimentin expression.

CONCLUSION

ADC skewness and kurtosis histogram parameters can reflect tumor compartments in HNSCC. ADC entropy was associated with TIL of the tumor compartment but not with those of the stroma compartment, which emphasizes the ability of ADC histogram parameters to reflect distinctive differences of tumors.

A Nomogram of Combining IVIM-DWI and MRI Radiomics From the Primary Lesion of Rectal Adenocarcinoma to Assess Nonenlarged Lymph Node Metastasis Preoperatively

BACKGROUND

Lymph node (LN) staging plays an important role in treatment decision-making. Current problem is that preoperative detection of LN involvement is always highly challenging for radiologists.

PURPOSE

To explore the value of the nomogram model combining intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and radiomics features from the primary lesion of rectal adenocarcinoma in assessing the non-enlarged lymph node metastasis (N-LNM) preoperatively.

STUDY TYPE

Retrospective.

POPULATION

A total of 126 patients (43% female) comprising a training group (n = 87) and a validation group (n = 39) with pathologically confirmed rectal adenocarcinoma.

FIELD STRENGTH/SEQUENCE

A 3.0 Tesla (T); T₂ -weighted imaging (T₂ WI) with fast spin-echo (FSE) sequence; IVIM-DWI spin-echo echo-planar imaging sequence.

ASSESSMENT

Based on pathological analysis of the surgical specimen, patients were classified into negative LN (LN-) and positive LN (LN+) groups. Apparent diffusion coefficient (ADC), diffusion coefficient (D), pseudo diffusion coefficient (D*) and microvascular volume fraction (f) values of primary lesion of rectal adenocarcinoma were measured. Three-dimensional (3D) radiomics features were measured on T₂ WI and IVIM-DWI. A nomogram model including IVIM-DWI and radiomics features was developed.

STATISTICAL TESTS

General_univariate_analysis and multivariate logistic regression were used for radiomics features selection. The performance of the nomogram was assessed by the receiver operating characteristic (ROC) curve, calibration, and decision curve analysis (DCA).

RESULTS

The LN+ group had a significantly lower D* value ([13.20 ± 13.66 vs. 23.25 ± 18.71] × 10^-3  mm² /sec) and a higher f value (0.43 ± 0.12 vs. 0.34 ± 0.10) than the LN- group in the training cohort. The nomogram model combined D*, f, and radiomics features had a better evaluated performance (AUC = 0.864) than any other model in the training cohort.

DATE CONCLUSION

The nomogram model including IVIM-DWI and MRI radiomics features in the primary lesion of rectal adenocarcinoma was associated with the N-LNM.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Comparison of different ROI analysis methods for liver lesion characterization with simplified intravoxel incoherent motion (IVIM)

This study investigated the impact of different ROI placement and analysis methods on the diagnostic performance of simplified IVIM-DWI for differentiating liver lesions. 1.5/3.0-T DWI data from a respiratory-gated MRI sequence (b = 0, 50, 250, 800 s/mm²) were analyzed in patients with malignant (n = 74/54) and benign (n = 35/19) lesions. Apparent diffusion coefficient ADC = ADC(0,800) and IVIM parameters D₁' = ADC(50,800), D₂' = ADC(250,800), f₁' = f(0,50,800), f₂' = f(0,250,800), and D*' = D*(0,50,250,800) were calculated voxel-wise. For each lesion, a representative 2D-ROI, a 3D-ROI whole lesion, and a 3D-ROI from "good" slices were placed, including and excluding centrally deviating areas (CDA) if present, and analyzed with various histogram metrics. The diagnostic performance of 2D- and 3D-ROIs was not significantly different; e.g. AUC (ADC/D₁'/f₁') were 0.958/0.902/0.622 for 2D- and 0.942/0.892/0.712 for whole lesion 3D-ROIs excluding CDA at 1.5 T (p > 0.05). For 2D- and 3D-ROIs, AUC (ADC/D₁'/D₂') were significantly higher, when CDA were excluded. With CDA included, AUC (ADC/D₁'/D₂'/f₁'/D*') improved when low percentiles were used instead of averages, and was then comparable to the results of average ROI analysis excluding CDA. For lesion differentiation the use of a representative 2D-ROI is sufficient. CDA should be excluded from ROIs by hand or automatically using low percentiles of diffusion coefficients.

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

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.

Quantitative T2*-Weighted Imaging and Reduced Field-of-View Diffusion-Weighted Imaging of Rectal Cancer: Correlation of R2* and Apparent Diffusion Coefficient With Histopathological Prognostic Factors

Purpose

To assess T2*-weighted imaging (T2*WI) and reduced field-of-view diffusion-weighted Imaging (rDWI) derived parameters and their relationships with histopathological factors in patients with rectal cancer.

Methods

Fifty-four patients with pathologically-proven rectal cancer underwent preoperative T2*-weighted imaging and rDWI in this retrospective study. R2* values from T2*-weighted imaging and apparent diffusion coefficient (ADC) values from rDWI were compared in terms of different histopathological prognostic factors using student’s t-test or Mann-Whitney U-test. The correlations of R2* and ADC with prognostic factors were assessed by Spearman correlation analysis. The diagnostic performances of R2* and ADC were analyzed by receiver operating characteristic curves (ROC) separately and jointly.

Results

Significant positive correlation was found between R2* values and T stage, lymph node involvement, histological grades, CEA level, the presence of EMVI and tumor deposit (r = 0.374 ~ 0.673, p = 0.000–0.006), with the exception of CA19-9 level, CRM status and tumor involvement in the circumference lumen (TIL). Meanwhile, ADC values negatively correlated with almost all the prognostic factors (r = −0.588 to −0.299, p = 0.000–0.030), except CA19-9 level. The AUC range was 0.724–0.907 for R2* and 0.674–0.887 for ADC in discrimination of different prognostic factors. While showing the highest AUC of 0.913 (0.803–1.000) in differentiation of T stage, combination of R2* and ADC with reference to different prognostic factors did not significantly improve the diagnostic performance in comparison with individual R2*/ADC parameter.

Conclusions

R2* and ADC were associated with important histopathological prognostic factors of rectal cancer. R2* might act as additional quantitative imaging marker for tumor characterization of rectal cancer.