Contribution of mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging in the diagnosis and differentiation of uterine cervical carcinoma

Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy

PURPOSE

To investigate the predictive power of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) in prognosis and survival risk of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.

MATERIALS AND METHODS

Forty-five patients with laryngeal or hypopharyngeal squamous cell carcinoma were retrospectively enrolled. All patients had undergone pretreatment IVIM examination, subsequently, mean apparent diffusion coefficient (ADCmean), maximum ADC (ADCmax), minimum ADC (ADCmin) and ADCrange (ADCmax - ADCmean) by mono-exponential model, true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f) by bi-exponential model, distributed diffusion coefficient (DDC), and diffusion heterogeneity index (α) by stretched exponential model were measured. Survival data were collected for 5 years.

RESULTS

Thirty-one cases were in the treatment failure group and fourteen cases were in the local control group. Significantly lower ADCmean, ADCmax, ADCmin, D, f, and higher D* values were observed in the treatment failure group than in the local control group (p < 0.05). D* had the greatest AUC of 0.802, with sensitivity and specificity of 77.4 and 85.7% when D* was 38.85 × 10^-3 mm²/s. Kaplan-Meier survival analysis showed that the curves of N stage, ADCmean, ADCmax, ADCmin, D, D*, f, DDC, and α values were significant. Multivariate Cox regression analysis showed ADCmean and D* were independently correlated with progression-free survival (PFS) (hazard ratio [HR] = 0.125, p = 0.001; HR = 1.008, p = 0.002, respectively).

CONCLUSION

The pretreatment parameters of mono-exponential and bi-exponential models were significantly correlated with prognosis of LHSCC, ADCmean and D* values were independent factors for survival risk prediction.

Value of non-Gaussian diffusion imaging with a fractional order calculus model combined with conventional MRI for differentiating histological types of cervical cancer

OBJECTIVE

This study aimed to evaluate the value of a fractional order calculus (FROC) model combined with conventional magnetic resonance imaging (MRI) for differentiating cervical adenocarcinoma (CAC) from squamous cell carcinoma (SCC).

METHODS

Diffusion-weighted imaging (DWI) with 9 b values (0-2000s/mm²) was carried out in 57 cervical cancer patients. Diffusion coefficient (D), fractional order parameter (β), and microstructural quantity (μ) together with apparent diffusion coefficient (ADC) were calculated and compared between the CAC and SCC groups. Conventional MRI features included T₂WI signal intensity (SI), unenhanced-T₁WI SI, enhanced-T₁WI SI, and ∆T₁WI SI, which were also compared between the two groups. Receiver operating characteristic (ROC) analysis was employed to assess the performance of FROC parameters, ADC, and conventional MRI features in differentiating CAC from SCC.

RESULTS

β was significantly lower in the CAC group than in the SCC group (0.682 ± 0.054 vs. 0.723 ± 0.084, P = 0.035), while D and μ were not significantly different between the two groups (D, P = 0.171; μ, P = 0.127). There was no significant difference in the ADC value between the two groups (P = 0.053). In conventional MRI features, enhanced-T₁WI SI was significantly higher in the SCC group than in the CAC group (985.78 ± 130.83 vs. 853.92 ± 149.65, P = 0.002). The area under the curve (AUC) of β, ADC, and enhanced-T₁WI SI was 0.700, 0.683, and 0.799, respectively. The combination of β, ADC, and enhanced-T₁WI SI revealed optimal diagnostic performance in differentiating CAC from SCC (AUC = 0.930), followed by β + enhanced-T₁WI SI (AUC = 0.869), ADC+ enhanced-T₁WI SI (AUC = 0.817), and β + ADC (AUC = 0.761).

CONCLUSION

The FROC model can serve as a noninvasive and quantitative imaging technique for differentiating CAC from SCC. β combined with ADC and enhanced-T₁WI SI had the highest diagnostic efficiency.

The value of diffusion kurtosis imaging, diffusion weighted imaging and 18F-FDG PET for differentiating benign and malignant solitary pulmonary lesions and predicting pathological grading

Objective

To explore the value of PET/MRI, including diffusion kurtosis imaging (DKI), diffusion weighted imaging (DWI) and positron emission tomography (PET), for distinguishing between benign and malignant solitary pulmonary lesions (SPLs) and predicting the histopathological grading of malignant SPLs.

Material and methods

Chest PET, DKI and DWI scans of 73 patients with SPL were performed by PET/MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), maximum standard uptake value (SUV_max), metabolic total volume (MTV) and total lesion glycolysis (TLG) were calculated. Student’s t test or the Mann–Whitney U test was used to analyze the differences in parameters between groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy. Logistic regression analysis was used to evaluate independent predictors.

Results

The MK and SUV_max were significantly higher, and the MD and ADC were significantly lower in the malignant group (0.59 ± 0.13, 10.25 ± 4.20, 2.27 ± 0.51[×10^-3 mm²/s] and 1.35 ± 0.33 [×10^-3 mm²/s]) compared to the benign group (0.47 ± 0.08, 5.49 ± 4.05, 2.85 ± 0.60 [×10^-3 mm²/s] and 1.67 ± 0.33 [×10^-3 mm²/s]). The MD and ADC were significantly lower, and the MTV and TLG were significantly higher in the high-grade malignant SPLs group (2.11 ± 0.51 [×10^-3 mm²/s], 1.35 ± 0.33 [×10^-3 mm²/s], 35.87 ± 42.24 and 119.58 ± 163.65) than in the non-high-grade malignant SPLs group (2.46 ± 0.46 [×10^-3 mm²/s], 1.67 ± 0.33[×10^-3 mm²/s], 20.17 ± 32.34 and 114.20 ± 178.68). In the identification of benign and malignant SPLs, the SUV_max and MK were independent predictors, the AUCs of the combination of SUV_max and MK, SUV_max, MK, MD, and ADC were 0.875, 0.787, 0.848, 0.769, and 0.822, respectively. In the identification of high-grade and non-high-grade malignant SPLs, the AUCs of MD, ADC, MTV, and TLG were 0.729, 0.680, 0.693, and 0.711, respectively.

Conclusion

DWI, DKI, and PET in PET/MRI are all effective methods to distinguish benign from malignant SPLs, and are also helpful in evaluating the pathological grading of malignant SPLs.

Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model?

Background

To evaluate and compare the potential performance of various diffusion parameters obtained from mono-exponential model (MEM)-, bi-exponential model (BEM)-, and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in grading of esophageal squamous carcinoma (ESC).

Methods

Eighty-two patients with pathologically confirmed ESC without treatment underwent multi-b-value DWI scan with 13 b values (0~12,00 s/mm²). The apparent diffusion coefficient (ADC) deriving from the MEM; the pure molecular diffusion (ADC_slow), pseudo-diffusion coefficient (ADC_fast), perfusion, and fraction (f) deriving from the BEM; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) deriving from the SEM were calculated and compared between poorly differentiated and well/moderately differentiated ESC, respectively. The prediction parameters and diagnostic efficiency were compared by drawing receiver operating characteristic (ROC) curves.

Results

The ADC, ADC_slow, ADC_fast, and DDC in poorly ESC were significantly lower than those in well/moderately differentiated ones. By using only one parameter, ADC_slow, DDC had the moderate diagnostic efficiency and the areas under the curve (AUC) were 0.758 and 0.813 in differentiating ESC. The DDC had the maximum AUC with sensitivity (88.00%) and specificity (68.42%). Combining ADC with ADC_fast, ADC_slow, and DDC and combining ADC_slow with ADC_fast can provide a higher diagnostic accuracy with AUC ranging from 0.756, 0.771, 0.816, and 0.793, respectively.

Conclusion

Various parameters derived from different DWI models including MEM, BEM, and SEM were potentially helpful in grading ESC. DDC obtained from SEM was the most promising diffusion parameter for predicting the grade of ESC.

Cervical Carcinoma: Evaluation Using Diffusion MRI With a Fractional Order Calculus Model and its Correlation With Histopathologic Findings

Objective

The objective of the study is to investigate the feasibility of using the fractional order calculus (FROC) model to reflect tumor subtypes and histological grades of cervical carcinoma.

Methods

Sixty patients with untreated cervical carcinoma underwent multi-b-value diffusion-weighted imaging (DWI) at 3.0T magnetic resonance imaging (MRI). The mono-exponential and the FROC models were fitted. The differences in the histological subtypes and grades were evaluated by the Mann–Whitney U test. Receiver operating characteristic (ROC) analyses were performed to assess the diagnostic performance and to determine the best predictor for both univariate analysis and multivariate analysis. Differences between ROC curves were tested using the Hanley and McNeil test, while the sensitivity, specificity, and accuracy were compared using the McNemar test. P-value <0.05 was considered as significant difference. The Bonferroni corrections were applied to reduce problems associated with multiple comparisons.

Results

Only the parameter β, derived from the FROC model could differentiate cervical carcinoma subtypes (P = 0.03) and the squamous cell carcinoma (SCC) lesions exhibited significantly lower β than that in the adenocarcinoma (ACA) lesions. All the individual parameters, namely, ADC, β, D, and μ derived from the FROC model, could differentiate low-grade cervical carcinomas from high-grade ones (P = 0.022, 0.009, 0.004, and 0.015, respectively). The combination of all the FROC parameters showed the best overall performance, providing the highest sensitivity (81.2%) and AUC (0.829).

Conclusion

The parameters derived from the FROC model were able to differentiate the subtypes and grades of cervical carcinoma.

Application Value of Real-Time Ultrasonic Elastograph with Serum Human Epididymis Protein 4, Interleukin-33, and Carbohydrate Antigen 153 in Diagnosis of Early Cervical Cancer

Objective

To explore the application value of real-time ultrasonic elastograph (USE) with serum human epididymis protein 4 HE4, interleukin-33 (IL-33), and carbohydrate antigen 153 (CA153) in the diagnosis of early cervical cancer.

Methods

A total of 120 cervical cancer patients treated in our hospital (06, 2019-06, 2021) and meeting the study criteria were screened and divided into the benign group (BG, n = 70) and malignant group (MG, n = 50) according to their final diagnostic results, and healthy females who received physical examination in our hospital in the same period were selected as the control group (CG, n = 60). Patients in the three groups received real-time USE and detection of serum HE4, IL-33, and CA153 so as to analyze the diagnostic value of single examination and combined examination in diagnosing early cervical cancer.

Results

The patients' real-time USE score, E _max, E _mean, and elastic fibers were significantly higher in the MG than those in the BG (P < 0.05), and the patients' real-time USE E _min, stroma ratio and collagen fibers were significantly lower in the MG than those in the BG (P < 0.05); the HE4, IL-33, and CA153 levels were obviously higher in the MG than those in the BG (P < 0.05) and were significantly higher in the BG than those in the CG (P < 0.05); the positive detection rate of combining real-time USE with serum HE4, IL-33, and CA153 was higher than that of single examination, and the diagnostic accuracy rate, sensitivity, specificity, positive predictive value, and negative predictive value of the combined examination were significantly higher than those of single examination (P < 0.05); according to the diagnostic efficacy of single examination and combined examination in diagnosing early cervical cancer by ROC curve, it was combined diagnosis > real-time USE > HE4 > CA153 > IL-33.

Conclusion

Combined examination of real-time USE and serum HE4, IL-33, and CA153 has higher diagnostic value in diagnosing early cervical cancer, which can obviously improve the diagnostic accuracy rate of cervical cancer.

A comparative study of four diffusion-weighted imaging models in the diagnosis of cervical cancer

BACKGROUND

Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue.

PURPOSE

To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue.

MATERIAL AND METHODS

Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis.

RESULTS

All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue (P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models (P < 0.05).

CONCLUSION

All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.

Value of diffusion-weighted imaging in preoperative evaluation and prediction of postoperative supplementary therapy for patients with cervical cancer

Background

With the continuous progress of medical imaging technology, evaluation of cervical cancer is increasingly dependent on imaging methods. Diffusion-weighted imaging (DWI) plays an important role, and apparent diffusion coefficient (ADC) value is a unique quantitative parameter in the research of cervical cancer.

Methods

In this prospective study, a total of 273 patients diagnosed with stage IB1 to IIIC1 cervical cancer based on the International Federation of Gynecology and Obstetrics (FIGO) 2018 staging guidelines who underwent pelvic 3.0T magnetic resonance imaging (MRI), including MRI and DWI, were enrolled, and the diagnostic value of preoperative staging of cervical cancer was compared between the MRI and DWI groups. The DWI group was used to explore the potential association of mean ADC (ADC_mean) with different pathological characteristics and receiver operating characteristic (ROC) curves of ADC_mean generated to predict the appropriate postoperative supplementary therapy.

Results

The diagnostic coincidence rate of DWI was higher than that of MRI in preoperative staging of cervical cancer (χ², P<0.05) and determined as stages IB1 + IB2 + IIA1 (90.91%), IB3 + IIA2 (93.48%), and IIIC1p (95.16%). The DWI staging results were consistent with postoperative pathological staging (Kappa value =0.865, P<0.001). We observed significant differences in ADC_mean values in relation to pathological type, histological grade, depth of stromal infiltration, tumor diameter, lymphovascular invasion, and pelvic lymph node metastasis of cervical cancer (all P<0.05). The area under the ROC curve (AUC) was 0.815, with the best predictive value for postoperative supplementary therapy in cervical cancer (sensitivity 80.0%, specificity 74.0%) at ADC_mean of 0.910×10^-3 mm²/s.

Conclusions

The DWI is a useful tool for preoperative evaluation of cervical cancer. In local cervical lesions, ADC_mean varies in relation to different clinicopathological characteristics and a reference index of <0.910×10^-3 mm²/s can be effectively applied to predict the need for postoperative supplementary therapy.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Predicting and Monitoring the Response of Anti-Angiogenic Treatment in the Orthotopic Nude Mouse Model of Lung Adenocarcinoma

BACKGROUND

The treatment efficacy of angiogenesis inhibitor could be underestimated at an early stage based on tumor volume changes. Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) can quantitatively assess tumors at the cellular level, but it is unclear whether it can provide useful information for assessing treatment response of anti-angiogenic treatment for lung adenocarcinoma.

PURPOSE

To determine the use of IVIM-DWI for non-invasive monitoring of the early response to anti-angiogenic treatment in the orthotopic transplantation of lung adenocarcinoma model.

STUDY TYPE

Prospective.

POPULATION

Thirty-seven nude mice were randomized into two groups: treatment group (received bevacizumab + cisplatin, N = 20) and control group (received saline, N = 17).

FIELD STRENGTH/SEQUENCE

Single-shot turbo spin-echo (TSE) IVIM-DWI, TSE T2-weighted imaging at 3.0 T.

ASSESSMENT

Tumor volume, IVIM parameters (apparent diffusion coefficient [ADC], diffusivity [D], perfusion fraction [f], and pseudo-diffusion coefficient [D*]) were measured before and 2 hours, 3, 7, 10 and 14 days after treatment. Regions of interest were manually drawn along the inner edge of the tumor by two radiologists with 5 and 10-year experience in magnetic resonance imaging. Pathological examinations (hematoxylin and eosin stain, cluster of differentiation 34) were performed.

STATISTICAL TESTS

Kolmogorov-Smirnov test, repeated-measure two-way analysis of variance test, Mann-Whitney U test, Pearson correlation analysis, receiver operating characteristic curve. P < 0.05 was considered statistically significant.

RESULTS

The tumor volume of the two groups was significantly different only on day 14 (control group vs. treatment group, 43.15 ± 18.28 mm³ vs. 28.41 ± 1.71 mm³ ). ADC_2h , ADC_10d , D_2h , D_7d , D_10d , and D_14d were significantly higher, while f_10d and f_14d were significantly lower in the treatment group compared to those of the control group. Both the △ADC_2h (r = -0.631) and △D_2h (r = -0.700) showed moderate correlations with the relative tumor volume on day 14.

DATA CONCLUSION

IVIM has the potential to predict and monitor the early response to anti-angiogenic treatment, earlier than size changes, for lung adenocarcinoma.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 4.

Comparison of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted MR imaging models in differentiating hepatic hemangiomas from liver metastases

PURPOSE

This study aims to compare the diagnostic values of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted imaging (DWI) in differentiating hepatic hemangiomas and liver metastases.

METHOD

This prospective study was approved by our institutional review board, and written informed consent was obtained from all patients. In this study, 244 patients with known or suspected liver disease underwent magnetic resonance imaging. Among them, 37 patients who had focal hepatic lesions with a maximum diameter of ≥10 mm were evaluated. Using home-built software, two radiologists measured the DWI parameters of hepatic lesions for the three models: the apparent diffusion coefficient (ADC) from a mono-exponential model; the true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from a bi-exponential model; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) from a stretched exponential model. The parameters were compared between hepatic hemangiomas and liver metastases.

RESULTS

In total, 64 focal hepatic lesions were evaluated, of which 22 were identified to be hepatic hemangiomas and 42 were liver metastases. ADC, D, f, and DDC values were significantly lower in liver metastases than in hepatic hemangiomas (P <  0.0001, <  0.0001, 0.015, and <  0.0001, respectively); whereas, the α value was significantly higher in liver metastases than in hepatic hemangiomas (P =  0.028). The areas under the ROC curve (AUCs) for differentiating hepatic hemangiomas and liver metastases in ADC, D, D*, f, DDC, and α were 0.940, 0.908, 0.608, 0.686, 0.952, and 0.667, respectively. The AUC values of ADC and DDC were significantly greater than those of D* (P <  0.0001), f (P =  0.0001), and α values (P =  0.0001).

CONCLUSION

ADC and DDC values from the mono-exponential and stretched exponential models could be considered as quantitative imaging biomarkers for differentiating hepatic hemangiomas and liver metastases.

Diagnostic Value of Combined Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging with Diffusion Tensor Imaging in Predicting Parametrial Infiltration in Cervical Cancer

Objective

This study sought to determine the diagnostic value of combined intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) in predicting parametrial infiltration (PMI) in patients with cervical cancer.

Materials and Methods

We enrolled 65 patients with cervical cancer confirmed by radical hysterectomy (25 PMI-negative and 40 PMI-positive) who underwent IVIM and DTI pretreatment. The parameters of IVIM (ADC, D, D  ^∗ , and f) and DTI (average diffusion coefficient (DCavg) and fractional anisotropy (FA)) were recorded by two observers. All parameter differences were tested, and the receiver operating characteristic (ROC) curves were generated to estimate the diagnostic performance of significant metrics and their combinations.

Results

Compared to the PMI-negative group, the PMI-positive group had significantly lower D (0.632 ± 0.017 vs. 0.773 ± 0.024, p < 0.001) and lower FA (0.073 ± 0.002 vs. 0.085 ± 0.003, p=0.003). The area under the ROC curve (AUC) of D and FA was 0.801 and 0.726, respectively, and the combination of D and FA improved the AUC to 0.931, with a sensitivity and specificity of 80.0% and 97.5%, respectively.

Conclusion

D and FA values could be used to help diagnose PMI in patients with cervical cancer. The combination of IVIM and DTI was more valuable than either option alone.

Influence of menstrual status and pathological type on the apparent diffusion coefficient in cervical cancer: a primary study

BACKGROUND

Apparent diffusion coefficient (ADC) value is an important quantitative parameter in the research of cervical cancer, affected by some factors.

PURPOSE

To investigate the effect of pathological type and menstrual status on the ADC value of cervical cancer.

MATERIAL AND METHODS

A total of 352 individuals with pathologically confirmed cervical cancer between January 2015 to December 2017 were retrospectively enrolled in this study, including 317 cases with squamous cell carcinomas (SCC) and 35 cases with adenocarcinomas (AC); 177 patients were non-menopausal and 175 were menopausal. All patients underwent a routine 3.0-T magnetic resonance imaging (MRI) scan and diffusion-weighted imaging (DWI) examination using b-values of 0, 800, and 1000 s/mm². Three parameters including mean ADC (ADC_mean), maximum ADC (ADC_max), and minimum ADC (ADC_min) of cervical cancer lesions were measured and retrospectively analyzed. Independent samples t-test was used to compare the difference of ADC values in different menstrual status and pathological types.

RESULTS

In all menopausal and non-menopausal patients, the ADC_mean and ADC_min values of SCC were lower than those of AC (P<0.05), the ADC_max of two pathological types showed no statistical difference (P > 0.05). In menopausal patients, the ADC_mean, ADC_max, and ADC_min values of SCC were not statistically different compared with those of AC (P > 0.05). The ADC_mean, ADC_max, and ADC_min values of different pathological types cervical cancers in non-menopausal patients were all higher than those in menopausal patients (P<0.05).

CONCLUSION

The ADC values of the cervical cancers were different in different pathological types and were also affected by menstrual status.

B-Value Optimization in the Estimation of Intravoxel Incoherent Motion Parameters in Patients with Cervical Cancer

Objective

This study aimed to find the optimal number of b-values for intravoxel incoherent motion (IVIM) imaging analysis, using simulated and in vivo data from cervical cancer patients.

Materials and Methods

Simulated data were generated using literature pooled means, which served as reference values for simulations. In vivo data from 100 treatment-naïve cervical cancer patients with IVIM imaging (13 b-values, scan time, 436 seconds) were retrospectively reviewed. A stepwise b-value fitting algorithm calculated optimal thresholds. Feed forward selection determined the optimal subsampled b-value distribution for biexponential IVIM fitting, and simplified IVIM modeling using monoexponential fitting was attempted. IVIM parameters computed using all b-values served as reference values for in vivo data.

Results

In simulations, parameters were accurately estimated with six b-values, or three b-values for simplified IVIM, respectively. In vivo data showed that the optimal threshold was 40 s/mm² for patients with squamous cell carcinoma and a subsampled acquisition of six b-values (scan time, 198 seconds) estimated parameters were not significantly different from reference parameters (individual parameter error rates of less than 5%). In patients with adenocarcinoma, the optimal threshold was 100 s/mm², but an optimal subsample could not be identified. Irrespective of the histological subtype, only three b-values were needed for simplified IVIM, but these parameters did not retain their discriminative ability.

Conclusion

Subsampling of six b-values halved the IVIM scan time without significant losses in accuracy and discriminative ability. Simplified IVIM is possible with only three b-values, at the risk of losing diagnostic information.

Investigating the value of arterial spin labeling and intravoxel incoherent motion imaging on diagnosing nasopharyngeal carcinoma in T1 stage

BACKGROUND

To investigate the diagnostic value of arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM) imaging in distinguishing nasopharyngeal carcinoma (NPC) in T1 stage from healthy controls (HC).

METHODS

Forty-five newly diagnosed NPC patients in the T1 stage and thirty-one healthy volunteers who underwent MR examinations for both 3D pseudo-continuous ASL (pCASL) and IVIM were enrolled in this study. The Mann-Whitney test was used to compare the mean values of blood flow (BF) derived from pCASL and IVIM derived parameters, including apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f) between NPC tumor and benign nasopharyngeal mucosa of HC. Receiver Operating Characteristic (ROC) was performed to determine diagnostic cutoff and efficiency. The correlation coefficients among parameters were investigated using Spearman's test.

RESULTS

The NPC in the T1 stage showed higher mean BF, lower ADC, D, and f compared to benign nasopharyngeal mucosa (P < 0.001) with the area under curve of ROC of 0.742-0.996 (highest by BF). BF cutoff was set at > 36 mL/100 g/min; the corresponding sensitivity, specificity, and accuracy in differentiating NPC stage T1 from benign nasopharyngeal mucosa were 95.56% (43/45), 100% (31/31) and 97.37% (74/76), respectively. BF demonstrated moderate negative correlation with D* on HC (ρ [Spearman correlation coefficients] = - 0.426, P = 0.017).

CONCLUSIONS

ASL and IVIM could reflect the difference in perfusion and diffusion between tumor and benign nasopharyngeal mucosa, indicating a potential for accessing early diagnosis of NPC. Notably, BF, with a specificity of 100%, demonstrated better performance compared to IVIM in distinguishing malignant lesions from healthy tissue.

Potentialities of multi-b-values diffusion-weighted imaging for predicting efficacy of concurrent chemoradiotherapy in cervical cancer patients

BACKGROUND

To testify whether multi-b-values diffusion-weighted imaging (DWI) can be used to ultra-early predict treatment response of concurrent chemoradiotherapy (CCRT) in cervical cancer patients and to assess the predictive ability of concerning parameters.

METHODS

Fifty-three patients with biopsy proved cervical cancer were retrospectively recruited in this study. All patients underwent pelvic multi-b-values DWI before and at the 3rd day during treatment. The apparent diffusion coefficient (ADC), true diffusion coefficient (D_slow), perfusion-related pseudo-diffusion coefficient (D_fast), perfusion fraction (f), distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index(α) were generated by mono-exponential, bi-exponential and stretched exponential models. Treatment response was assessed based on Response Evaluation Criteria in Solid Tumors (RECIST v1.1) at 1 month after the completion of whole CCRT. Parameters were compared using independent t test or Mann-Whitney U test as appropriate. Receiver operating characteristic (ROC) curves was used for statistical evaluations.

RESULTS

ADC-T0 (p = 0.02), D_slow-T0 (p <  0.01), DDC-T0 (p = 0.03), ADC-T1 (p <  0.01), D_slow-T1 (p <  0.01), ΔADC (p = 0.04) and Δα (p <  0.01) were significant lower in non-CR group patients. ROC analyses showed that ADC-T1 and Δα exhibited high prediction value, with area under the curves of 0.880 and 0.869, respectively.

CONCLUSIONS

Multi-b-values DWI can be used as a noninvasive technique to assess and predict treatment response in cervical cancer patients at the 3rd day of CCRT. ADC-T1 and Δα can be used to differentiate good responders from poor responders.

Perfusion parameters of intravoxel incoherent motion based on tumor edge region of interest in cervical cancer: evaluation of differentiation and correlation with dynamic contrast-enhanced MRI

BACKGROUND

Intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) is a functional magnetic resonance imaging (MRI) sequence.

PURPOSE

To evaluate the value of perfusion parameters derived from IVIM-DWI based on tumor edge region of interest (ROI) in differentiation in cervical cancer and investigate the relationship between IVIM and dynamic contrast-enhanced MRI (DCE-MRI).

MATERIAL AND METHODS

Thirty-three patients with pathologically diagnosed squamous cell carcinoma who underwent IVIM-DWI (nine b-values: 1-1000 s/mm²) and DCE-MRI were retrospectively assessed in this study. Parameters of IVIM (D, f, D*, fD*) and quantitative parameters of DCE-MRI (Ktrans, Kep, Ve) were derived using tumor edge ROI. Mann-Whitney U test was used to compare parameters between pathological grades and receiver operating characteristic (ROC) curves were used. Pearson's correlation coefficient (r) evaluated the correlation between perfusion parameters derived from IVIM and DCE-MRI.

RESULTS

The poorly differentiated group showed the significantly lower D value and the higher f, Ktrans and Kep values than the well-to-moderately differentiated group (P < 0.05). ROC curves indicated that f < 26%, Ktrans <0.38/min, and Kep <1.62/min could differentiate the poorly differentiated group from the well-to-moderately differentiated group (AUC 0.753-0.808). Significantly positive correlations were found between f and Ktrans (r = 0.422, P = 0.014) and between fD* and Ktrans (r = 0.448, P = 0.009).

CONCLUSION

Perfusion parameters derived from IVIM based on tumor edge ROI may offer additional value in differentiation in cervical cancer, and the IVIM perfusion parameters showed moderate positive correlations with quantitative perfusion parameters from DCE-MRI, while f and fD* showed promising significance.

Differentiation of endometrial adenocarcinoma from adenocarcinoma of cervix using kinetic parameters derived from DCE-MRI

PURPOSE

This prospective study aimed to investigate the value of kinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating uterine endometrioid adenocarcinoma (EAC) from adenocarcinoma of cervix (AdC).

METHODS

Seventy-five newly diagnosed patients with distinctive pathology underwent DCE-MRI. Observers independently calculated the tumor diameters and DCE-MRI parameters using both population and individual-based arterial input function (AIF). Inter-observer consistency was evaluated, and a comparative analysis between EAC (n = 47) and AdC (n = 28) was performed. Regression analysis was used to select parameters that best distinguished EAC from AdC, and to generate predictive models. Receiver operating characteristic curve (ROC) was applied to calculate the diagnostic efficiency of single parameter and the predictive models.

RESULTS

Inter-observer consistency was excellent (intra-class correlation [ICC] = 0.902-0.981), especially when calculated via population AIF with relatively higher ICC and smaller SD on Bland-Altman plot. Tumor diameters were not correlated with tumor types. All the DCE-MRI parameters were lower in EAC compared to AdC, except K_ep by population AIF and TTP by both sets of AIFs. The statistical parameters were V_e, Maxslop, and Maxconc by population AIF, and Maxslop and K^trans by individual AIF included in the predictive models, respectively. The two predictive models with combined parameters showed improved diagnostic efficiency in differentiating these two diseases compared with a single parameter.

CONCLUSION

DCE-MRI can quantitatively evaluate the perfusion difference between EAC and AdC, thus improving the identification of uterine adenocarcinoma with uncertain biopsy pathology.

Comparing mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted MR imaging for stratifying non-alcoholic fatty liver disease in a rabbit model

OBJECTIVES

To compare diffusion parameters obtained from mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) in stratifying non-alcoholic fatty liver disease (NAFLD).

METHODS

Thirty-two New Zealand rabbits were fed a high-fat/cholesterol or standard diet to obtain different stages of NAFLD before 12 b-values (0-800 s/mm²) DWI. The apparent diffusion coefficient (ADC) from the mono-exponential model; pure water diffusion (D), pseudo-diffusion (D*), and perfusion fraction (f) from bi-exponential DWI; and distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) from stretched-exponential DWI were calculated for hepatic parenchyma. The goodness of fit of the three models was compared. NAFLD severity was pathologically graded as normal, simple steatosis, borderline, and non-alcoholic steatohepatitis (NASH). Spearman rank correlation analysis and receiver operating characteristic curves were used to assess NAFLD severity.

RESULTS

Upon comparison, the goodness of fit chi-square from stretched-exponential fitting (0.077 ± 0.012) was significantly lower than that for the bi-exponential (0.110 ± 0.090) and mono-exponential (0.181 ± 0.131) models (p < 0.05). Seven normal, 8 simple steatosis, 6 borderline, and 11 NASH livers were pathologically confirmed from 32 rabbits. Both α and D increased with increasing NAFLD severity (r = 0.811 and 0.373, respectively; p < 0.05). ADC, f, and DDC decreased as NAFLD severity increased (r = - 0.529, - 0.717, and - 0.541, respectively; p < 0.05). Both α (area under the curve [AUC] = 0.952) and f (AUC = 0.931) had significantly greater AUCs than ADC (AUC = 0.727) in the differentiation of NASH from borderline or less severe groups (p < 0.05).

CONCLUSIONS

Stretched-exponential DWI with higher fitting efficiency performed, as well as bi-exponential DWI, better than mono-exponential DWI in the stratification of NAFLD severity.

KEY POINTS

• Stretched-exponential diffusion model fitting was more reliable than the bi-exponential and mono-exponential diffusion models (p = 0.039 and p < 0.001, respectively). • As NAFLD severity increased, the diffusion heterogeneity index (α) increased, while the perfusion fraction (f) decreased (r = 0.811, - 0.717, p < 0.05). • Both α and f showed superior NASH diagnostic performance (AUC = 0.952, 0.931) compared with ADC (AUC = 0.727, p < 0.05).

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.

Multiple mathematical models of diffusion-weighted imaging for endometrial cancer characterization: Correlation with prognosis-related risk factors

PURPOSE

To investigate mono-exponential, bi-exponential, and stretched-exponential models of diffusion-weighted imaging (DWI) for evaluation of prognosis-related risk factors of endometrial cancer (EC).

METHOD

Sixty-one consecutive patients with EC who preoperatively underwent pelvic MRI with multiple b value DWI between September 2016 and May 2018 were enrolled. The apparent-diffusion-coefficient (ADC), bi-exponential model parameters (D, D* and f) and stretched-exponential model parameters (DDC and α) were measured and compared to analyze the following prognosis-related risk factors confirmed by pathology: histological grade, depth of myometrial invasion, cervical stromal infiltration (CSI) and lymphovascular invasion (LVSI). A stepwise multilvariate logistic regression and the receiver operating characteristic (ROC) curves were performed for further statistical analysis.

RESULTS

Lower ADC, D, f, and DDC were observed in tumor with high grade compared with a low-grade group, and the largest area under curve (AUC) was obtained when combining f and DDC values. ADC, D, f, DDC, and α were significantly different in patients with deep myometrial invasion (DMI) compared to those without DMI; the combination of f, DDC and α showed the highest AUC. Significantly different ADC and f were found between patients' presence and absence CSI; the f values showed the highest diagnostic performance with an AUC of 0.825. Regarding the LVSI, ADC, D*, f, and DDC were significantly lower in tumors with LVSI compared to those without LVSI; the combination of f and DDC showed the largest AUC.

CONCLUSION

Multiple mathematical DWI models are a useful approach for the prediction of prognosis-related risk factors in EC.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging of Lung Cancer: Comparison Between Turbo Spin-Echo and Echo-Planar Imaging

OBJECTIVE

The aim of the study was to compare intravoxel incoherent motion diffusion-weighted imaging (DWI) for evaluating lung cancer using single-shot turbo spin-echo (TSE) and single-shot echo-planar imaging (EPI) in a 3T MR system.

METHODS

Both single-shot TSE-DWI and single-shot EPI-DWI were scanned twice respectively for 15 patients with lung cancer. Distortion ratio, signal-to-noise ratio, and contrast-to-noise ratio were compared between the 2 techniques. The Bland-Altman analysis was performed to analyze reproducibility between the parameters of TSE-DWI and EPI-DWI. Short-term test-retest repeatability, as well as interobserver agreement, was evaluated using the coefficient of variation (CV) and the intraclass correlation coefficient (ICC).

RESULT

Turbo spin-echo DWI has lower signal-to-noise ratio and similar contrast-to-noise ratio compared with EPI-DWI. Distortion ratio of TSE-DWI was significantly smaller than that of EPI-DWI. The apparent diffusion coefficient (ADC) and true diffusivity (D) of TSE-DWI showed higher values than those of EPI-DWI. The Bland-Altman analysis showed unacceptable limits of agreement between these 2 sequences. Test-retest repeatability was good for ADC and D of EPI-DWI (CV, 14.11%-16.60% and 17.08%-19.53%) and excellent for ADC and D of TSE-DWI (CV, 4.8%-6.19% and 6.05%-8.71%), but relatively poor for perfusion fraction (f) and pseudo-diffusion coefficient (D*) (CV, 25.95%-27.70% and 56.92%-71.84% for EPI, 23.67%-28.67% and 60.85%-70.17% for TSE). For interobserver agreement, both techniques were good to excellent in ADC and D (The lower limit of 95% confidence interval for ICC was almost all greater than 0.75), whereas D* and f had higher interobserver variabilities with D* of TSE-DWI showing poorest reproducibility (ICC, -0.27 to 0.12).

CONCLUSIONS

Lung DWI or IVIM using TSE could provide distortion-free images and improve the test-retest robustness of ADC and D as compared with EPI-DWI; however, it might exert a negative effect on perfusion parameter D*.

Histogram analysis from stretched exponential model on diffusion-weighted imaging: evaluation of clinically significant prostate cancer

OBJECTIVE

To evaluate the usefulness of histogram analysis of stretched exponential model (SEM) on diffusion-weighted imaging in evaluating clinically significant prostate cancer (CSC).

METHODS

A total of 85 patients with prostate cancer underwent 3 T multiparametric MRI, followed by radical prostatectomy. Histogram parameters of the tumor from the SEM [distributed diffusion coefficient (DDC) and α] and the monoexponential model [MEM; apparent diffusion coefficient (ADC)] were evaluated. The associations between parameters and Gleason score or Prostate Imaging Reporting and Data System v. 2 were evaluated. The area under the receiver operating characteristics curve was calculated to evaluate diagnostic performance of parameters in predicting CSC.

RESULTS

The values of histogram parameters of DDC and ADC were significantly lower in patients with CSC than in patients without CSC (p < 0.05), except for skewness and kurtosis. The value of the 25th percentile of α was significantly lower in patients with CSC than in patients without CSC (p = 0.014). Histogram parameters of ADC and DDC had significant weak to moderate negative associations with Gleason score or Prostate Imaging Reporting and Data System v. 2 (p < 0.001), except for skewness and kurtosis. For predicting CSC, the area under the curves of mean ADC (0.856), 50th percentile DDC (0.852), and 25th percentile α (0.707) yielded the highest values compared to other histogram parameters from each group.

CONCLUSION

Histogram analysis of the SEM on diffusion-weighted imaging may be a useful quantitative tool for evaluating CSC. However, the SEM did not outperform the MEM.

ADVANCES IN KNOWLEDGE

Histogram parameters of SEM may be useful for evaluating CSC.

The Value of IVIM DWI in Combination with Conventional MRI in Identifying the Residual Tumor After Cone Biopsy for Early Cervical Carcinoma

RATIONALE AND OBJECTIVES

To investigate the value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in combination with conventional MRI in identifying the residual tumor after biopsy for early cervical carcinoma.

MATERIALS AND METHODS

Eighty patients with histologically proven early cervical carcinoma were enrolled into this study. MRI sequences included two sets of MRI sequences including conventional MRI (T1WI, T2WI, and dynamic contrast-enhanced MRI) and IVIM DWI/conventional MRI combinations. The patients were classified into residual tumor and nonresidual tumor group after biopsy. IVIM parameters were quantitatively analyzed and compared between two groups. The diagnostic ability of two sets of MRI sequences were calculated and compared.

RESULTS

The mean D and f values were significantly lower in residual tumor group than in nonresidual tumor group (p < 0.05). The areas under receiver operating characteristic curves of D and f for discriminating between residual tumor and nonresidual tumor group were 0.848 and 0.767, respectively. The sensitivity and accuracy of conventional MRI/IVIM DWI combinations for the detection of residual tumor were 82.7% and 83.8%, respectively, while the sensitivity and accuracy of conventional MRI were 52.4% and 53.8%, respectively.

CONCLUSION

The addition of IVIM DWI to conventional MRI considerably improves the sensitivity and accuracy of the detection of residual tumor after biopsy for early cervical carcinoma.

Characterization of focal liver lesions using the stretched exponential model: comparison with monoexponential and biexponential diffusion-weighted magnetic resonance imaging

OBJECTIVE

To compare the stretched exponential model of diffusion-weighted imaging (DWI) with monoexponential and biexponential models in terms of the ability to characterize focal liver lesions (FLLs).

METHODS

This retrospective study included 180 patients with FLLs who underwent magnetic resonance imaging including DWI with nine b values at 3.0 T. The distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched exponential model; true diffusion coefficient (D_t), pseudo-diffusion coefficient (D_p), and perfusion fraction (f) from a biexponential model; and apparent diffusion coefficient (ADC) were calculated for each lesion. Diagnostic performances of the parameters were assessed through receiver operating characteristic (ROC) analysis. For 20 patients with treated hepatic metastases, the correlation between the DWI parameters and the percentage of tumor necrosis on pathology was evaluated using the Spearman correlation coefficient.

RESULTS

DDC had the highest area under the ROC curve (AUC, 0.905) for differentiating malignant from benign lesions, followed by D_t (0.903) and ADC (0.866), without significant differences among them (DDC vs. D_t, p = 0.946; DDC vs. ADC, p = 0.157). For distinguishing hypovascular from hypervascular lesions, and hepatocellular carcinoma from metastasis, f  had a significantly higher AUC than the other DWI parameters (p < 0.05). The α had the strongest correlation with the degree of tumor necrosis (ρ = 0.655, p = 0.002).

CONCLUSION

The DDC from stretched exponential model of DWI demonstrated excellent diagnostic performance for differentiating malignant from benign FLLs. The α is promising for evaluating the degree of necrosis in treated metastases.

KEY POINTS

• The stretched exponential DWI model is valuable for characterizing focal liver lesions. • The DDC from stretched exponential model shows excellent performance for differentiating malignant from benign focal liver lesions. • The α from stretched exponential model is promising for evaluating the degree of necrosis in hepatic metastases after chemotherapy.

Comparison of the Diagnostic Value of Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MRI in Differentiating Tumor Stage and Histological Grade of Bladder Cancer

RATIONALE AND OBJECTIVES

We aimed to determine the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging (DWI) models in differentiating tumor stage and grade of bladder cancer.

MATERIALS AND METHODS

Forty-five patients with pathologically confirmed bladder cancer underwent multi-b-value DWI. An apparent diffusion coefficient (ADC) was calculated from DWI by using a monoexponential model. A true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) were calculated from DWI by using a biexponential model. A water molecular diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were calculated from DWI by using a stretched exponential model. All parameters were compared between different stages and grades by using the Mann-Whitney U test. Receiver operating characteristic and intrareader correlation coefficient analysis were used for statistical evaluations.

RESULTS

ADC, D, f, and DDC values were significantly higher in the non-muscle-invasive vs muscle-invasive bladder cancers (P = .000, .000, .002, and .000, respectively) and in low-grade vs high-grade ones (P = .000, .000, .018, and .000, respectively). D* value was significantly lower in the low-grade bladder cancers compared to high-grade ones (P = .012). The areas under the receiver operating characteristic curve of ADC, D, and DDC values were 0.945, 0.912, and 0.946 in staging bladder cancers; 0.866, 0.862, and 0.856 in grading bladder cancers, respectively.

CONCLUSION

Biexponential and stretched exponential DWI models may provide more parameters in staging and grading bladder cancers and show a slight difference between DDC and ADC values in staging bladder cancers. These two DWI models, as well as the monoexponential models, were very helpful in staging and grading bladder cancers.

Differentiating between malignant and benign solid solitary pulmonary lesions: are intravoxel incoherent motion and diffusion kurtosis imaging superior to conventional diffusion-weighted imaging?

OBJECTIVE

To quantitatively compare the diagnostic values of various diffusion parameters obtained from mono- and biexponential diffusion-weighted imaging (DWI) models and diffusion kurtosis imaging (DKI) in differentiating between benign and malignant solitary pulmonary lesions (SPLs).

METHODS

Multiple b-value DWIs and DKIs were performed in 89 patients with SPL by using a 3-T magnetic resonance (MR) imaging unit. The apparent diffusion coefficient (ADC) of various b-value sets, true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), apparent diffusional kurtosis (K_app), and kurtosis-corrected diffusion coefficient (D_app) were calculated and compared between the malignant and benign groups using a Mann-Whitney U test. Receiver-operating characteristic analysis was performed for all parameters.

RESULT

The ADC_{(0, 150)} values of malignant tumors were lower than those of the benign group (p = 0.01). The ADC_{(0, 300)}, ADC_{(0, 500)}, ADC_{(0, 600),} ADC_{(0, 800)}, ADC_{(0, 1000),} ADC_total, D, and D_app of malignant tumors were significantly lower than those of benign lesions (all p < 0.001). D*, f, and K_app showed no statistically significant differences between the two groups. ADC_total showed the highest area under the curve (AUC = 0.862), followed by ADC_{(0, 800)}(AUC = 0.844), ADC_{(0, 600)}(AUC = 0.843), D(AUC = 0.834), ADC_{(0, 1000)}(AUC = 0.834) and ADC_{(0, 500)}(AUC = 0.824), D_app(AUC = 0.796), and ADC_{(0, 300)} (AUC = 0.773). However, the difference in diagnostic efficacy among these parameters was not statistically significant (p > 0.05).

CONCLUSION

Intravoxel incoherent motion (IVIM) and DKI-derived parameters have similar performance compared with conventional ADC in differentiating SPLs.

KEY POINTS

• Mono- and biexponential DWI and DKI are feasible for differentiating SPLs. • ADC _{(0, ≥500)} has better performance than ADC _{(0, <500)} in assessing SPLs. • IVIM and DKI have similar performance compared with conventional DWI in differentiating SPLs.

The impact of MRI sequence on tumour staging and gross tumour volume delineation in squamous cell carcinoma of the anal canal

OBJECTIVES

To compare maximum tumour diameter (MTD) and gross tumour volume (GTV) measurements between T2-weighted (T2-w) and diffusion-weighted (DWI) MRI in squamous cell carcinoma of the anal canal (SCCA) and assess sequence impact on tumour (T) staging. Second, to evaluate interobserver agreement and reader delineation confidence.

METHODS

The staging MRI scans of 45 SCCA patients (25 females) were assessed retrospectively by two independent radiologists (0 and 5 years' experience of anal cancer MRI). MTD and GTV were delineated on both T2-w and high-b-value DWI images and compared between sequences; T staging was derived from MTD. Interobserver agreement was assessed and delineation confidence scored (1 to 5) by each observer.

RESULTS

GTV and MTD were significantly and systematically lower on DWI versus T2-w sequences by 14.80%/9.98% (MTD) and 29.70%/12.25% (GTV) for each reader, respectively, causing T staging discordances in approximately a quarter of cases. Bland-Altman limits of agreement were narrower and intraclass correlation coefficients higher for DWI. Delineation confidence was greater on DWI: 40/42 cases were scored confidently (4 or 5) by each reader, respectively, versus 31/36 cases based on T2-w images.

CONCLUSIONS

Sequence selection affects SCCA measurements and T stage. DWI yields higher interobserver agreement and greater tumour delineation confidence.

KEY POINTS

• MTD and GTV measurements are significantly lower on DWI than on T 2 -w MRI. • Such differences cause T staging discordances in up to a quarter of cases. • DWI results in higher agreement between inexperienced and experienced observers. • DWI offers greater tumour delineation confidence to inexperienced readers.

Multi-model Analysis of Diffusion-weighted Imaging of Normal Testes at 3.0 T: Preliminary Findings

RATIONALE AND OBJECTIVES

This study aimed to establish diffusion quantitative parameters (apparent diffusion coefficient [ADC], DDC, α, D_app, and K_app) in normal testes at 3.0 T.

MATERIALS AND METHODS

Sixty-four healthy volunteers in two age groups (A: 10-39 years; B: ≥ 40 years) underwent diffusion-weighted imaging scanning at 3.0 T. ADC₁₀₀₀, ADC₂₀₀₀, ADC₃₀₀₀, DDC, α, D_app, and K_app were calculated using the mono-exponential, stretched-exponential, and kurtosis models. The correlations between parameters and the age were analyzed. The parameters were compared between the age groups and between the right and the left testes.

RESULTS

The average ADC₁₀₀₀, ADC₂₀₀₀, ADC₃₀₀₀, DDC, α, D_app, and K_app values did not significantly differ between the right and the left testes (P > .05 for all). The following significant correlations were found: positive correlations between age and testicular ADC₁₀₀₀, ADC₂₀₀₀, ADC₃₀₀₀, DDC, and D_app (r = 0.516, 0.518, 0.518, 0.521, and 0.516, respectively; P < .01 for all) and negative correlations between age and testicular α and K_app (r = -0.363, -0.427, respectively; P < .01 for both). Compared to group B, in group A, ADC₁₀₀₀, ADC₂₀₀₀, ADC₃₀₀₀, DDC, and D_app were significantly lower (P < .05 for all), but α and K_app were significantly higher (P < .05 for both).

CONCLUSIONS

Our study demonstrated the applicability of the testicular mono-exponential, stretched-exponential, and kurtosis models. Our results can help establish a baseline for the normal testicular parameters in these diffusion models. The contralateral normal testis can serve as a suitable reference for evaluating the abnormalities of the other side. The effect of age on these parameters requires further attention.