Apparent diffusion coefficient (ADC) measurements in pancreatic adenocarcinoma: A preliminary study of the effect of region of interest on ADC values and interobserver variability

Values of apparent diffusion coefficient in pancreatic cancer patients receiving neoadjuvant therapy

BACKGROUND

To investigate the values of apparent diffusion coefficient (ADC) for the treatment response evaluation in pancreatic cancer (PC) patients receiving neoadjuvant therapy (NAT).

METHODS

This study included 103 NAT patients with histologically proven PC. ADC maps were generated using monoexponential diffusion-weighted imaging (b values: 50, 800 s/mm2). Tumors' minimum, maximum, and mean ADCs were measured and compared pre- and post-NAT. Variations in ADC values measured between pre- and post-NAT completion for NAT methods (chemotherapy, chemoradiotherapy), tumor locations (head/neck, body/tail), tumor regression grade (TRG) levels (0-2, 3), N stages (N0, N1/N2) and tumor resection margin status (R0, R1), were further analyzed.

RESULTS

The minimum, maximum, and mean ADC values all increased dramatically after NAT, rising from 23.4 to 25.4% (all p < 0.001): mean (average: 1.626 × 10- 3 mm2/s vs. 1.315 × 10- 3 mm2/s), minimum (median: 1.274 × 10- 3 mm2/s vs. 1.034 × 10- 3 mm2/s), and maximum (average: 1.981 × 10- 3 mm2/s vs. 1.580 × 10- 3 mm2/s). The ADCs between the subgroups of all the criteria under investigation did not differ significantly for the minimum, maximum, or mean values pre- or post-NAT (P = 0.08 to 1.00). In the patients with borderline resectable PC (n = 47), the rate of tumor size changes after NAT was correlated with the pre-NAT mean ADC values (Spearman's coefficient: 0.288, P = 0.049).

CONCLUSIONS

The ADC values of PC increased significantly following NAT; however, the percentage increases failed to provide any predictive value for the resection margin status or TRG levels.

Quantitative Assessment of Breast Tumor: Comparison of Four Methods of Positioning Region of Interest for Synthetic Relaxometry and Diffusion Measurement

RATIONALE AND OBJECTIVES

To compare the differences in apparent diffusion coefficient (ADC) and synthetic magnetic resonance (MR) measurements of four region of interest (ROI) placement methods for breast tumor and to investigate their diagnostic performance.

METHODS

110 (70 malignant, 40 benign) newly diagnosed breast tumors were evaluated. The patients underwent 3.0 T MR examinations including diffusion-weighted imaging and synthetic MR. Two radiologists independently measured ADCs, T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) using four ROI methods: round, square, freehand, and whole-tumor volume (WTV). The interclass correlation coefficient (ICC) was used to assess their measurement reliability. Diagnostic performance was evaluated using multivariate logistic regression analysis and the receiver operating characteristic (ROC) curves.

RESULTS

The mean values of all ROI methods showed good or excellent interobserver reproducibility (0.79-0.99) and showed the best diagnostic performance compared to the minimum and maximum values. The square ROI exhibited superior performance in differentiating between benign from malignant breast lesions, followed by the freehand ROI. T2, PD, and ADC values were significantly lower in malignant breast lesions compared to benign ones for all ROI methods (p < 0.05). Multiparameters of T2 + ADC demonstrated the highest AUC values (0.82-0.95), surpassing the diagnostic efficacy of ADC or T2 alone (p < 0.05).

CONCLUSION

ROI placement significantly influences ADC and synthetic MR values measured in breast tumors. Square ROI and mean values showed superior performance in differentiating benign and malignant breast lesions. The multiparameters of T2 + ADC surpassed the diagnostic efficacy of a single parameter.

A novel model based on liver/spleen volumes and portal vein diameter on MRI to predict variceal bleeding in HBV cirrhosis

OBJECTIVE

To develop a novel logistic regression model based on liver/spleen volumes and portal vein diameter measured on magnetic resonance imaging (MRI) for predicting oesophagogastric variceal bleeding (OVB) secondary to HBV cirrhosis.

METHODS

One hundred eighty-five consecutive cirrhotic patients with hepatitis B undergoing abdominal contrast-enhanced MRI were randomly divided into training cohort (n = 130) and validation cohort (n = 55). Spleen volume, total liver volume, four liver lobe volumes, and diameters of portal venous system were measured on MRI. Ratios of spleen volume to total liver and to individual liver lobe volumes were calculated. In training cohort, univariate analyses and binary logistic regression analyses were to determine independent predictors. Performance of the model for predicting OVB constructed based on independent predictors from training cohort was evaluated by receiver operating characteristic (ROC) analysis, and was validated by Kappa test in validation cohort.

RESULTS

OVB occurred in 42 and 18 individuals in training and validation cohorts during the 2 years' follow-up, respectively. An OVB prediction model was constructed based on the independent predictors including right liver lobe volume (RV), left gastric vein diameter (LGVD) and portal vein diameter (PVD) (odds ratio = 0.993, 2.202 and 1.613, respectively; p-values < 0.001 for all). The logistic regression model equation (-0.007 × RV + 0.79 × LGVD + 0.478 × PVD-6.73) for predicting OVB obtained excellent performance with an area under ROC curve of 0.907. The excellent performance was confirmed by Kappa test with K-value of 0.802 in validation cohort.

CONCLUSION

The novel logistic regression model can be reliable for predicting OVB.

KEY POINTS

• Patients with oesophagogastric variceal bleeding are mainly characterized by decreased right lobe volume, and increased spleen volume and diameters of portal vein system. • The right liver lobe volume, left gastric vein diameter and portal vein diameter are the independent predictors of oesophagogastric variceal bleeding. • The novel model developed based on the independent predictors performed well in predicting oesophagogastric variceal bleeding with an area under the receiver operating characteristic curve of 0.907.

A diagnostic scoring model of ENKTCL in the nose-Waldeyer's ring based on logistic regression: Differential diagnosis from DLBCL

Objective

To establish a logistic regression model based on CT and MRI imaging features and Epstein-Barr (EB) virus nucleic acid to develop a diagnostic score model to differentiate extranodal NK/T nasal type (ENKTCL) from diffuse large B cell lymphoma (DLBCL).

Methods

This study population was obtained from two independent hospitals. A total of 89 patients with ENKTCL (n = 36) or DLBCL (n = 53) from January 2013 to May 2021 were analyzed retrospectively as the training cohort, and 61 patients (ENKTCL=27; DLBCL=34) from Jun 2021 to Dec 2022 were enrolled as the validation cohort. All patients underwent CT/MR enhanced examination and EB virus nucleic acid test within 2 weeks before surgery. Clinical features, imaging features and EB virus nucleic acid results were analyzed. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors of ENKTCL and establish a predictive model. Independent predictors were weighted with scores based on regression coefficients. A receiver operating characteristic (ROC) curve was created to determine the diagnostic ability of the predictive model and score model.

Results

We searched for significant clinical characteristics, imaging characteristics and EB virus nucleic acid and constructed the scoring system via multivariate logistic regression and converted regression coefficients to weighted scores. The independent predictors for ENKTCL diagnosis in multivariate logistic regression analysis, including site of disease (nose), edge of lesion (blurred), T2WI (high signal), gyrus like changes, EB virus nucleic acid (positive), and the weighted score of regression coefficient was 2, 3, 4, 3, 4 points. The ROC curves, AUCs and calibration tests were carried out to evaluate the scoring models in both the training cohort and the validation cohort. The AUC of the scoring model in the training cohort were 0.925 (95% CI, 0.906-0.990) and the cutoff point was 5 points. In the validation cohort, the AUC was 0.959 (95% CI, 0.915-1.000) and the cutoff value was 6 points. Four score ranges were as follows: 0-6 points for very low probability of ENKTCL, 7-9 points for low probability; 10-11 points for middle probability; 12-16 points for very high probability.

Conclusion

The diagnostic score model of ENKTCL based on Logistic regression model which combined with imaging features and EB virus nucleic acid. The scoring system was convenient, practical and could significantly improve the diagnostic accuracy of ENKTCL and the differential diagnosis of ENKTCL from DLBCL.

Combinations of liver lobe and spleen volumes obtained on magnetic resonance imaging to predict esophagogastric variceal bleeding in hepatitis B-related cirrhotic patients: A prospective cohort study

To evaluate whether combinations of liver lobe and spleen volumes obtained on magnetic resonance imaging (MRI) could predict esophagogastric variceal bleeding (EVB) in hepatitis B-related cirrhotic patients. Ninety-six consecutive patients with hepatitis B-related cirrhosis underwent upper abdominal contrast-enhanced MRI within 1 week after initial hospitalization, and grouped based on outcomes of EVB during the 2 years' follow-up after being discharged. Total liver volume (TLV), spleen volume (SV) and 4 liver lobe volumes including right lobe volume (RV), left medial lobe volume (LMV), left lateral lobe volume (LLV), and caudate lobe volume (CV) were measured on MRI. Percentages of individual liver lobe volumes in TLV (including RV/TLV, LMV/TLV, LLV/TLV, and CV/TLV), ratios of SV to individual liver lobe volumes (including SV/RV, SV/LMV, SV/LLV, and SV/CV), and SV/TLV were statistically analyzed to predict EVB. Patients with EVB had lower RV than without EVB (P value = .001), whereas no differences in LMV, LLV, CV, and TLV were found (P values >.05 for all). Among percentages of individual liver lobe volumes in TLV, RV/TLV was lower whereas LMV/TLV and LLV/TLV were greater in patients with EVB than without EVB (P values <.05 for all). SV, ratios of SV to individual liver lobe volumes, and SV/TLV in patients with EVB were larger than without EVB (P values <.05 for all). Among parameters with difference between patients with and without EVB, SV/RV could best predict EVB with an area under receiver operating characteristic curve of 0.84. SV/RV could best predict EVB in hepatitis B-related cirrhotic patients.

Repeatability of Apparent Diffusion Coefficient at 3.0 Tesla in Normal Pancreas

Purpose: To evaluate the apparent diffusion coefficient (ADC) test-retest repeatability of the normal pancreas based on diffusion-weighted imaging (DWI).

Methods: Twenty-six healthy volunteers (mean 47.6 years; 13 men) were included and scanned twice with reposition for a DWI sequence at 3.0-T. Two readers measured the ADCs of pancreatic head, body and tail for two DWIs, independently. The mean ADCs of the pancreatic head, body and tail were calculated as the global pancreatic ADC. Test-retest repeatability and agreement of ADC measurement were evaluated by the Bland-Altman analysis, intra-class correlation coefficient (ICC) and coefficient of variation (CV).

Results: The global pancreatic ADC showed the best test-retest repeatability (mean difference ± limits of agreement were 0.05 ± 0.25×10^-3 mm²/s; ICC, 0.79; CV, 6%). Test-retest repeatabilities for ADC of pancreatic head, body or tail were scattered, with mean difference ± limits of agreement between two tests were 0.03 ± 0.47, 0.05 ± 0.42 and 0.06 ± 0.31 (×10^-3 mm²/s) (ICCs, 0.81, 0.52 and 0.68; CVs, 9%, 8% and 8%), respectively. Both intra-observer repeatability and inter-observer reproducibility were acceptable for global pancreatic ADC between measurements of the two DWIs.

Conclusions:The best test-retest repeatability of ADC in the normal pancreas was only for the whole pancreas with a CV of 6%. Cautions should be taken in interpreting longitudinal clinical changes in ADC values of the normal pancreas for the measurements do have an inherent variability by locations.

Diagnostic performance of diffusion MRI for pancreatic ductal adenocarcinoma characterisation: A meta-analysis

PURPOSE

To assess the diagnostic performance of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) for characterising pancreatic ductal adenocarcinoma (PDAC).

METHOD

A literature search was performed through PubMed, Web of Science, the Cochrane Library, and Embase databases. The search date was updated to extend until 28 October 2020, with no starting time limitation. The pooled sensitivity and specificity were calculated using a bivariate random effects model. Summary receiver operating characteristic curves were constructed, and area under the curve (AUC) of each diffusion parameter was calculated. Subgroup and meta-regression analyses were performed to assess for heterogeneity. Study quality was assessed.

RESULTS

Twenty-nine studies involving 1579 participants were included, of which 26 evaluated the apparent diffusion coefficient (ADC) and eight evaluated IVIM, with five evaluating both ADC and IVIM. Pooled sensitivity and specificity of ADC were 83 % (95 % CI, 76 %-88 %, I² = 86 %) and 85 % (95 % CI, 79 %-90 %, I² = 77 %), respectively, and AUC was 0.91 (95 % CI, 0.88-0.93). The perfusion fraction had the highest diagnostic accuracy in the IVIM model; the pooled sensitivity, specificity, and AUC were 87 % (95 % CI, 81 %-92 %, I² = 45 %), 88 % (95 % CI, 77 %-94 %, I² = 57 %), and 0.93 (95 % CI, 0.91-0.95), respectively. The pooled sensitivity, specificity and AUC for the tissue diffusion coefficient were 74 % (95 % CI, 55 %-87 %, I² = 87 %), 69 % (95 % CI, 52 %-82 %, I² = 73 %), and 0.77 (95 % CI, 0.73-0.81), respectively. And the pooled sensitivity, specificity, and AUC for the pseudodiffusion coefficient were 89 % (95 % CI, 77 %-96 %, I² = 79 %), 74 % (95 % CI, 60 %-84 %, I² = 78 %), and 0.88(95 %CI,0.85-0.91), respectively. Meta-regression analyses revealed that study design (specificity, P＜0.01), region-of-interest delineation (sensitivity, P = 0.02;specificity, P = 0.03), field strength (sensitivity, P＜0.01), and thickness (sensitivity, P＜0.01; specificity, P = 0.01) were sources of ADC heterogeneity.

CONCLUSIONS

DWI and IVIM have comparable diagnostic power and good diagnostic performance for characterising PDAC.

Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10⁻³ mm² s⁻¹ with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

Performance of diffusion-weighted imaging for the diagnosis of parotid gland malignancies: A meta-analysis

PURPOSE

This study aimed to assess the diagnostic performance of diffusion-weighted imaging (DWI) for parotid gland malignancies.

METHODS

Four databases (PubMed, the Cochrane Library, Embase, and Web of Science) were searched systematically and retrospectively by two researchers until May 18, 2020. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to pool the sensitivity and specificity data for the apparent diffusion coefficient (ADC). Summary receiver operating characteristic curve was constructed, and the area under the curve (AUC) was calculated. The positive (LR+) and negative likelihood ratios (LR-) were also calculated. Subgroup and meta-regression analyses were performed to evaluate heterogeneity within studies.

RESULTS

Sixteen studies involving 1004 patients were included. The pooled sensitivity, specificity, and AUC for the ADC to distinguish malignant from begin parotid lesions were 89 %, 76 %, and 0.91, respectively. The LR + was 3.7 and LR- was 0.15, respectively. Subgroup analyses revealed that the applied cut-off b values and study size were sources of heterogeneity for the ADC. There were publication bias concerns.

CONCLUSIONS

Our meta-analysis suggests that the ADC value provides excellent sensitivity and moderate specificity for the diagnosis of malignant lesions in the parotid gland. However, substantial heterogeneity was found. Therefore, additional larger, prospective studies in combination with standard techniques focusing on parotid tumors should be conducted to determine the true performance of DWI for the differential diagnosis of parotid lesions.

Investigation of the feasibility of synthetic MRI in the differential diagnosis of non-keratinising nasopharyngeal carcinoma and benign hyperplasia using different contoured methods for delineation of the region of interest

AIM

To assess the feasibility and preliminary diagnostic performances of relaxation times derived from synthetic magnetic resonance imaging (syMRI) for differentiating nasopharyngeal carcinoma from nasopharyngeal benign lymphoid hyperplasia, and to assess the influence of tissue segmentation method on relaxation estimates.

MATERIALS AND METHODS

Fifty participants with nasopharyngeal carcinoma (NPC) and 40 participants with benign hyperplasia (NPH) who underwent syMRI examination were enrolled prospectively. T1, T2, and proton density (PD) values were obtained from four different regions of interest (ROIs), namely, partial-section, single-section, three-sections, and whole-lesion. The metrics between NPC and NPH or among different ROIs were compared using Student's t-test or one-way ANOVA. The area under curve (AUC) was calculated to assess the performance of metrics obtained from different ROIs to differentiate NPC and NPH.

RESULTS

The T1, T2, and PD values for NPH were significantly higher than those for NPC, regardless of the type of ROI used, except for the PD value obtained from the whole-lesion ROI. The T2 values obtained from the single-section ROI showed the highest diagnostic accuracy in distinguishing NPC from NPH, with an AUC of 0.894, sensitivity of 0.900, and specificity of 0.800. Additionally, the T1, T2, and PD values for nasopharyngeal lesions showed no statistical difference among different kinds of ROI, except for the difference in T1 value between partial-section and other methods.

CONCLUSION

Quantitative analysis of syMRI has the potential to distinguish NPC from NPH. Moreover, different types of ROI showed limited influence on the relaxation time estimation for nasopharyngeal lesions.

Borderline Resectable and Locally Advanced Pancreatic Cancer: FDG PET/MRI and CT Tumor Metrics for Assessment of Pathologic Response to Neoadjuvant Therapy and Prediction of Survival

BACKGROUND. Imaging biomarkers of response to neoadjuvant therapy (NAT) for pancreatic ductal adenocarcinoma (PDA) are needed to optimize treatment decisions and long-term outcomes. OBJECTIVE. The purpose of this study was to investigate metrics from PET/MRI and CT to assess pathologic response of PDA to NAT and to predict overall survival (OS). METHODS. This retrospective study included 44 patients with ¹⁸F-FDG-avid borderline resectable or locally advanced PDA on pretreatment PET/MRI who also underwent post-NAT PET/MRI before surgery between August 2016 and February 2019. Carbohydrate antigen 19-9 (CA 19-9) level, metabolic metrics from PET/MRI, and morphologic metrics from CT (n = 34) were compared between pathologic responders (College of American Pathologists scores 0 and 1) and nonresponders (scores 2 and 3). AUCs were measured for metrics significantly associated with pathologic response. Relation to OS was evaluated with Cox proportional hazards models. RESULTS. Among 44 patients (22 men, 22 women; mean age, 62 ± 11.6 years), 19 (43%) were responders, and 25 (57%) were nonresponders. Median OS was 24 months (range, 6-42 months). Before treatment, responders and nonresponders did not differ in CA 19-9 level, metabolic metrics, or CT metrics (p > .05). After treatment, responders and nonresponders differed in complete metabolic response (CMR) (responders, 89% [17/19]; nonresponders, 40% [10/25]; p = .04], mean change in SUV_max (ΔSUV_max; responders, -70% ± 13%; nonresponders, -37% ± 42%; p < .001), mean change in SUV_max corrected to serum glucose level (ΔSUV_gluc) (responders, -74% ± 12%; nonresponders, -30% ± 58%; p < .001), RECIST response on CT (responders, 93% [13/14]; nonresponders, 50% [10/20]; p = .02)], and mean change in tumor volume on CT (ΔTvol) (responders, -85% ± 21%; nonresponders, 57% ± 400%; p < .001). The AUC of CMR for pathologic response was 0.75; ΔSUV_max, 0.83; ΔSUV_gluc, 0.87; RECIST, 0.71; and ΔTvol 0.86. The AUCs of bivariable PET/MRI and CT models were 0.83 (CMR and ΔSUV_max), 0.87 (CMR and ΔSUV_gluc), and 0.87 (RECIST and ΔTvol). OS was associated with CMR (p = .03), ΔSUV_max (p = .003), ΔSUV_gluc (p = .003), and RECIST (p = .046). CONCLUSION. Unlike CA 19-9 level, changes in metabolic metrics from PET/MRI and morphologic metrics from CT after NAT were associated with pathologic response and OS in patients with PDA, warranting prospective validation. CLINICAL IMPACT. Imaging metrics associated with pathologic response and OS in PDA could help guide clinical management and outcomes for patients with PDA who undergo emergency therapeutic interventions.

Prediction of tumour grade and survival outcome using pre-treatment PET- and MRI-derived imaging features in patients with resectable pancreatic ductal adenocarcinoma

OBJECTIVES

To perform a correlation analysis between histopathology and imaging in patients with previously untreated pancreatic ductal adenocarcinoma (PDAC) and to determine the prognostic values of clinical, histological, and imaging parameters regarding overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS).

METHODS

This single-centre study prospectively included 61 patients (32 males; median age, 68.0 years [IQR, 63.0-75.0 years]) with histologically confirmed PDAC and following surgical resection who preoperatively underwent ¹⁸F-FDG PET/CT and DW-MRI. On whole lesions, we measured, using a 42% SUV_max threshold volume of interest (VOI), the following quantitative parameters: mean and maximum standardised uptake values (SUV_mean and SUV_max), total lesion glycolysis (TLG), metabolic tumour volume (MTV), mean and minimum apparent diffusion coefficient (ADC_mean and ADC_min), diffusion total volume (DTV), and MTV/ADC_min ratio. Spearman's correlation analysis was performed to assess relationships between these markers and histopathological findings from surgical specimens (stage; grade; resection quality; and vascular, perineural, and lymphatic invasion). Kaplan-Meier and Cox hazard ratio methods were used to evaluate the impacts of imaging parameters on OS (n = 41), DSS (n = 36), and PFS (n = 41).

RESULTS

Inverse correlations between ADC_min and SUV_max (rho = - 0.34; p = 0.0071), and between SUV_mean and ADC_mean (rho = - 0.29; p = 0.026) were identified. ADC_min was inversely correlated with tumour grade (rho = - 0.40; p = 0.0015). MTV was an independent predictive factor for OS and DSS, while DTV was an independent predictive factor for PFS.

CONCLUSION

In previously untreated PDAC, ADC and SUV values are correlated. Combining PET-MRI metrics may help predict PDAC grade and patients' survival.

KEY POINTS

• Minimum apparent diffusion coefficient derived from DW-MRI inversely correlates with tumour grade in pancreatic ductal adenocarcinoma. • In pancreatic ductal adenocarcinoma, metabolic tumour volume has been confirmed as a predictive factor for patients' overall survival and disease-specific survival. • Combining PET and MRI metrics may help predict grade and patients' survival in pancreatic ductal adenocarcinoma.

Magnetic resonance imaging in the assessment of pancreatic cancer with quantitative parameter extraction by means of dynamic contrast-enhanced magnetic resonance imaging, diffusion kurtosis imaging and intravoxel incoherent motion diffusion-weighted imaging

BACKGROUND

Despite great technical advances in imaging, such as multidetector computed tomography and magnetic resonance imaging (MRI), diagnosing pancreatic solid lesions correctly remains challenging, due to overlapping imaging features with benign lesions. We wanted to evaluate functional MRI to differentiate pancreatic tumors, peritumoral inflammatory tissue, and normal pancreatic parenchyma by means of dynamic contrast-enhanced MRI (DCE-MRI)-, diffusion kurtosis imaging (DKI)-, and intravoxel incoherent motion model (IVIM) diffusion-weighted imaging (DWI)-derived parameters.

METHODS

We retrospectively analyzed 24 patients, each with histopathological diagnosis of pancreatic tumor, and 24 patients without pancreatic lesions. Functional MRI was acquired using a 1.5 MR scanner. Peritumoral inflammatory tissue was assessed by drawing regions of interest on the tumor contours. DCE-MRI, IVIM and DKI parameters were extracted. Nonparametric tests and receiver operating characteristic (ROC) curves were calculated.

RESULTS

There were statistically significant differences in median values among the three groups observed by Kruskal-Wallis test for the DKI mean diffusivity (MD), IVIM perfusion fraction (fp) and IVIM tissue pure diffusivity (Dt). MD had the best results to discriminate normal pancreas plus peritumoral inflammatory tissue versus pancreatic tumor, to separate normal pancreatic parenchyma versus pancreatic tumor and to differentiate peritumoral inflammatory tissue versus pancreatic tumor, respectively, with an accuracy of 84%, 78%, 83% and area under ROC curve (AUC) of 0.85, 0.82, 0.89. The findings were statistically significant compared with those of other parameters (p value < 0.05 using McNemar's test). Instead, to discriminate normal pancreas versus peritumoral inflammatory tissue or pancreatic tumor and to differentiate normal pancreatic parenchyma versus peritumoral inflammatory tissue, there were no statistically significant differences between parameters' accuracy (p > 0.05 at McNemar's test).

CONCLUSIONS

Diffusion parameters, mainly MD by DKI, could be helpful for the differentiation of normal pancreatic parenchyma, perilesional inflammation, and pancreatic tumor.

Combined Diagnosis of Whole-Lesion Histogram Analysis of T1- and T2-Weighted Imaging for Differentiating Adrenal Adenoma and Pheochromocytoma: A Support Vector Machine-Based Study

PURPOSE

This study aimed to determine whether a combined diagnosis of whole-lesion histogram analysis of T1- and T2-weighted imaging based on support vector machine (SVM) can distinguish pheochromocytoma from adrenal adenoma.

METHODS

A pathology database was retrospectively appraised over a period of 7 years and we obtained 40 histopathologically proven adrenal adenomas and 20 pheochromocytomas with magnetic resonance images. The T1-weighted imaging (T₁WI, including both in phase and opposed phase) and T2-weighted imaging (T₂WI) images of each patients were analyzed using Mazda software. Nine parameters were selected as indicators of comparison: variance, skewness, kurtosis, mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, and 99th percentile. The parameters with differential-diagnosis significance were used to establish the combined diagnostic model of SVM.

RESULTS

Among the 9 parameters extracted using histogram analysis, the 1st percentile, 10th percentile, and 50th percentile of T₁WI (in phase) and the skewness of T₂WI and almost all parameters of T₁WI (opposed phase), except variance and 99th percentile, showed statistical significance between groups. Among the above parameters, the area under the curve (AUC) of 10th percentile of T₁WI (opposed phase) was the largest with the value of 0.909 (100.0% sensitivity and 80.0% specificity). After the analysis of combined diagnosis was performed, the AUC of SVM model in testing set showed the value of 0.917 (85.0% accuracy).

CONCLUSIONS

Whole-lesion histogram analysis of T₁WI and T₂WI may help differentiate adrenal adenomas from pheochromocytomas. Furthermore, the combined diagnosis of T₁WI and T₂WI histogram based on SVM was more effective than most of individual histogram parameters.

Quantitative Assessment of Bladder Cancer Reflects Grade and Recurrence: Comparing of Three Methods of Positioning Region of Interest for ADC Measurements at Diffusion-weighted MR Imaging

PURPOSE

To determine the impact of three different regions of interests (ROIs) positioning methods for apparent diffusion coefficient (ADC) measurements on the assessment of the grade and recurrence and to examine the correlation between ADC value and histopathological grade/ Ki-67 labeling index (LI) in patients with bladder cancer.

MATERIALS AND METHODS

Sixty-one patients with bladder cancer were retrospectively evaluated. Two observers measured mean ADC values using whole-volume-ROIs, single-section-ROI and three-ROIs methods. Interclass correlation coefficient was analyzed to assess interobserver variability. The grade and recurrence in patients with bladder cancer were assessed by calculating the areas under the receiver operating characteristic curves with Az values. Spearman's correlation was used to analyze the correlations of ADC value with grade and Ki-67 LI.

RESULTS

For the mean ADC value, the interclass correlation coefficient were excellent with the whole-volume and the single-section method (0.90 [95% CI: 0.84, 0.94] and 0.89 [95% CI: 0.81, 0.93]) and was good with the three-ROIs method (0.72 [95% CI: 0.53, 0.83]). The Az value for determining histological grade and recurrence of bladder cancer were not significantly different from each positioning method (all p > 0.05). There's significant correlation between histological grade and ADC measuring by whole-volume-ROIs and single-section-ROI methods (r = 0.31, p = 0.02; r = 0.37, p < 0.05). The ADC measured by whole-volume-ROIs, single-section-ROI, and three-ROIs methods were significantly and inversely correlated with the Ki-67 LI (r = -0.3; r = -0.49; r = -0.40, all p < 0.05).

CONCLUSION

There's no significant difference among any of the ROI positioning methods in evaluation of tumor grade and recurrence. There's significant correlation between histological grade and ADC measuring by whole-volume-ROIs and single-section-ROI methods. The ADC value obtained by either of three methods was significantly and inversely correlated with the Ki-67 LI.

Effect of region of interest on ADC and interobserver variability in thyroid nodules

BACKGROUND

To determine the effect of region of interest (ROI) on tumor's apparent diffusion coefficient (ADC) and interobserver variability in thyroid nodules.

METHODS

Thirty-three individuals with 45 pathologically-confirmed thyroid nodules were assessed by preoperative diffusion-weighted imaging (DWI) with b values of 0 and 400 s/mm², respectively. Two readers evaluated the ADC values of lesions based on three ROI techniques: whole-volume, single-slice and small solid-sample groups. Interobserver variability was analyzed for all ROI techniques, and the mean ADCs of benign and cancerous thyroid nodules were compared.

RESULTS

For the mean ADCs of non-cancerous thyroid nodules, average differences and limits of agreement (LOAs) between readers were 0.00 [- 0.17-0.17] × 10^- 3 mm²/s for whole-volume ROI (ICC = 0.967), 0.00 [- 0.26-0.26] × 10^- 3 mm²/s for single-slice ROI (ICC = 0.932) and - 0.02 [- 0.38-0.41] × 10^- 3 mm²/s for small solid-sample ROI (ICC = 0.823). For the mean ADCs of cancerous thyroid nodules, average differences and LOAs between readers were - 0.05 [- 0.23-0.13] × 10^- 3 mm²/s (ICC = 0.885), 0.01 [- 0.23-0.25] × 10^- 3 mm²/s (ICC = 0.839) and - 0.07 [- 0.52-0.39] × 10^- 3 mm²/s (ICC = 0.579) for the three ROI methods, respectively. The mean ADC values were more scattered in the small solid-sample ROI group in comparison with the whole-volume and single-slice groups, in noncancerous and cancerous specimens. Of all three ROI techniques, whole-volume ROI-determined ADC had the highest combined sensitivity (80.0%), specificity (88.3%) and Youden index (0.683), with a cut-off of 1.84 × 10^- 3 mm²/s.

CONCLUSIONS

The ROI method overtly affects ADC measurements in benign and cancerous thyroid nodules. Small solid-sample ROI yielded the worst interobserver variability of average ADC measurements.

Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Differentiation of Minimal Fat Angiomyolipoma from Clear Cell Renal Cell Carcinoma

AIM

To evaluate the diagnostic value of whole-tumor quantitative apparent diffusion coefficient (ADC) histogram and texture analysis for differentiation of minimal fat angiomyolipoma (MFAML) from clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

We retrospectively reviewed 27 patients with MFAML and 113 patients with ccRCC pathologically proven. All patients performed magnetic resonance imaging (MRI) including diffusion-weighted imaging (b = 0, 800s/mm²). Whole-tumor regions of interest were drawn on all slices of diffusion-weighted imaging to obtain histogram and texture parameters, including the mean ADC, median ADC, 10th, 25th, 75th, 90th percentiles ADC, standard deviation, skewness, kurtosis, and entropy. The Student's t test was used to compare the parameters between MFAML and ccRCC. Receiver operating characteristic curves analysis was used to compare the diagnostic value of each significant parameter.

RESULTS

MFAML had significantly lower mean ADC, median ADC, 10th, 25th, 75th, 90th percentiles ADC than ccRCC (p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, respectively). Skewness of MFAML was significantly higher than that of ccRCC (p = 0.016). However, standard deviation, kurtosis, and entropy were not significantly different (p = 0.409, p = 0.085, p = 0.206, respectively). The 90th percentile ADC generated the highest AUC (AUC, 0.854; Sensitivity, 78.8%; Specificity, 81.5%) for differentiating MFAML from ccRCC.

CONCLUSION

Whole-tumor ADC histogram and texture analysis could be considered a useful and noninvasive method to help differentiate MFAML of ccRCC with higher accuracy.

Effects of region of interest sizes on apparent diffusion coefficient measurements of pleomorphic adenoma, Warthin tumor, and normal parotid parenchyma

Background

Tumor apparent diffusion coefficient (ADC) measurements may be influenced by region of interest (ROI) sizes; however, this effect has not been systematically studied in parotid tumors. Our purpose was to determine the effects of ROI size on ADC measurements for the differentiation of pleomorphic adenoma (PA), Warthin tumor (WT), and normal parotid parenchyma.

Methods

Sixty-five patients including 37 with PA (lesions, n=37) and 28 with WT (lesions, n=36) were examined with diffusion-weighted imaging (DWI). Participants with normal contralateral parenchyma of the parotid gland constituted the control group (n=56). The mean ADC values and standard deviations (SDs) of the ADC (ADC_SD) of 12 concentric round ROIs (areas: 9, 28, 34, 50, 60, 82, 93, 98, 115, 130, 136, and 149 mm²) for tumors and normal tissue were measured by using custom-made software. Homogeneity index, which was defined by the ADC_SD/mean ADC, was also calculated. One-way repeated analyses of variance (ANOVAs) were performed on the mean ADCs, ADC_SDs, and homogeneity indices of the 12 ROIs in each group. The three parameters at different ROIs among PA, WT, and normal parotid parenchyma were compared using Kruskal-Wallis tests.

Results

There was excellent agreement for the ADC measurements with the 12 ROIs for PA [intraclass correlation coefficient (ICC), 0.98], WT (ICC, 0.99), and normal parotid parenchyma (ICC, 0.95). No significant differences were observed in the mean ADCs of the 12 ROIs for each of the three groups (P=0.744-0.990). Among the three groups, the mean ADC of normal parotid parenchyma [(0.94±0.003)×10^-3 mm²/s] was significantly lower than that of both PA [(1.72±0.01)×10^-3 mm²/s] and WT [(1.16±0.01)×10^-3 mm²/s] in the 12 ROIs, whereas the PA group had the highest mean ADC values. No significant differences were found in the mean ADC_SDs with each ROI between PA and WT (all P>0.017). PAs had lower homogeneity indices compared with WTs and normal parotid parenchyma (all P<0.01).

Conclusions

The effect of ROI size on ADC measurements could be excluded from the differentiation of PA, WT, and normal parotid parenchyma. Homogeneity index was a useful parameter in discriminating between the three groups.

Correlation between apparent diffusion coefficient values in breast magnetic resonance imaging and prognostic factors of breast invasive ductal carcinoma

BACKGROUND

We wanted to examine whether the apparent diffusion coefficient values obtained by diffusion-weighted imaging techniques could indicate an early prognostic assessment for patients with Invasive Ductal Carcinoma and, therefore, influence the treatment decision making.

OBJECTIVE

The main objective was to evaluate the correlation between the apparent diffusion coefficient values obtained by diffusion-weighted imaging and the key prognostic factors in breast invasive ductal carcinoma. Secondary objectives were to analyze the eventual correlations between magnetic resonance imaging findings and prognostic factors in breast cancer; and to perform a comparison between results in 1.5 and 3.0 T scanners.

METHODS

Breast magnetic resonance imaging with diffusion-weighted imaging sequence was performed on 100 patients, who were proven histopathologically to have breast invasive ductal carcinoma. We compared the apparent diffusion coefficient values, obtained previous to biopsy, with the main prognostic factors in breast cancer: tumor size, histologic grade, hormonal receptors, Ki67 index, human epidermal growth factor receptor type 2, and axillary lymph node status. The Mann-Whitney U test and the Kruskal-Wallis analysis were used to establish these correlations.

RESULTS

The mean apparent diffusion coefficient value was inferior in the estrogen receptor-positive group than in the estrogen receptor-negative group (1.04 vs 1.17 × 10-3 mm2/s, P = .004). Higher histologic grade related to larger tumor size (P = .002). We found association between spiculated margins and positive axillary lymph node status [odds ratio = 4.35 (1.49-12.71)]. There were no differences in apparent diffusion coefficient measurements between 1.5 and 3.0 T magnetic resonance imaging scanners (P = .513).

CONCLUSIONS

Low apparent diffusion coefficient values are related with positive expression of estrogen receptor. Larger tumors and spiculated margins are associated to worse prognosis. Rim enhancement is more frequently observed in estrogen receptor-negative tumors. There are no differences in apparent diffusion coefficient measurements between different magnetic resonance imaging scanners.

DWI of Pancreatic Ductal Adenocarcinoma: A Pilot Study to Estimate the Correlation With Metastatic Disease Potential and Overall Survival

OBJECTIVE

The purpose of this study is to analyze the relationship between the apparent diffusion coefficient (ADC) of pancreatic ductal adenocarcinoma (PDAC) and the presence or development of metastasis and overall survival (OS).

MATERIALS AND METHODS

Of 290 consecutive patients with histopathologically proven PDAC from January 2013 to December 2014, staging DWI was performed for 124 patients. Image quality was adequate in 112 studies. Sixty-five patients were treatment naïve, but 17 of the 65 were excluded because of the presence of other associated pancreatic pathologic abnormalities. Data for the remaining 48 patients (24 men and 24 women; median age, 65.5 years; interquartile range, 56-77 years) were obtained during a 4-year follow-up period (mean [± SD], 397 ± 415.1 days). The correlation between ADC and the presence or development of metastasis was assessed using descriptive statistics. OS was determined and mortality analysis was performed using Pearson correlation and Kaplan-Meier curves.

RESULTS

Of 48 patients, 10 had metastases at staging MRI, and 12 later developed metastatic disease. Among the latter, the mean time from staging MRI to metastasis was 258 ± 274.1 days. Most (86%) metastases were hepatic (n = 19). During the follow-up period, the remaining 26 patients (54%) never developed metastases. Patients with metastatic disease (n = 22) had significantly lower mean ADCs than did those without metastases (1.27 × 10^-3 vs 1.43 × 10^-3 mm²/s; p = 0.047). The ADC of PDAC had a positive correlation with survival: patients with PDAC with lower ADCs (< 1.36 × 10^-3 mm²/s) had significantly worse 4-year OS rates than did patients with higher ADC values (p = 0.036).

CONCLUSION

Pretreatment ADC values of PDAC may be significantly lower in patients who have or will develop metastatic disease and may correlate with worse OS.

Diffusion-weighted imaging of rectal cancer on repeatability and cancer characterization: an effect of b-value distribution study

BACKGROUND

To explore the effect of b-value distributions on the repeatability and diagnostic performance of the ADC value in rectal cancer patients using multiple b-values and mono-exponential model diffusion-weighted imaging (DWI).

METHODS

Thirty-two preoperative rectal cancer patients, without receiving neoadjuvant therapy, were scanned on a 3 Tesla magnetic resonance imaging scanner using DWI with 10 b-values ranging from 0 to 2000 s/mm². The apparent diffusion coefficient (ADC) value was calculated using a mono-exponential model and 31 b-value combinations consisting of 2 to 10 b-values were explored. Regions of interest with the maximum cross-sectional tumour size were outlined on the ADC map by two independent observers. Intraclass correlation coefficients (ICC), coefficient of variation (CV), and Bland-Altman plots between the two observers were calculated and evaluated to determine repeatability. Areas under receiver operating characteristic curves (AUCs) were evaluated for rectal cancer characterization. Correlations between the mean ADC values and T stage were assessed using the Spearman correlation coefficient (ρ). α (= ICC + AUC + |ρ|- CV - |bias|) was defined and used to assess the optimal b-value distribution.

RESULTS

Postoperative pathology tests revealed 4 patients with T1, 10 patients with T2, and 18 patients with T3 stages. There were no significant difference in age and sex between the two groups (T1-2 vs. T3). Excellent reproducibility was observed for ADC values between two observers with ICC and CV values ranging from 0.920 to 0.998, and 1.475 to 5.568%, respectively. The mean percent difference and ρ between the paired measurements was ranged from - 2.7 to 1.2% and from - 0.759 to - 0.407, respectively. The b-value combinations with the top three α values were b(0, 1000 s/mm²), b(500, 1500, 2000 s/mm²) and b(100, 1000, 1500 s/mm²) for α = 2.581, 2.571 and 2.569, respectively.

CONCLUSIONS

The number of b-values and their distributions influenced the repeatability of the ADC values and their diagnostic performance. The optimal b-value combination was 0 and 1000 s/mm² for DWI examination of rectal cancer patients.

Preoperative histogram analysis of intravoxel incoherent motion (IVIM) for predicting microvascular invasion in patients with single hepatocellular carcinoma

PURPOSE

To evaluate the value of intravoxel incoherent motion (IVIM) histogram analysis based on whole tumor volume in predicting microvascular invasion (MVI) of single hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

The study enrolled 41 patients with pathologically proven HCCs who underwent IVIM diffusion-weighted imaging with nine b values and contrast-enhanced magnetic resonance imaging (MRI). Histogram parameters including mean; skewness; kurtosis; and percentiles (5th, 10th, 25th, 50th, 75th, 90th, 95th) were derived from apparent diffusion coefficient (ADC), perfusion fraction (f), true diffusion coefficient (D), and pseudo diffusion coefficient (D*). Quantitative histogram parameters and clinical data were compared between HCCs with and without MVI. For significant parameters, receiver operating characteristic (ROC) curves were further plotted to compare the diagnosis performance for identifying MVI.

RESULTS

The mean, 5th, 10th, 25th, 50th, and 75th percentiles of D, and the 5th, 10th, and 25th percentiles of ADC between HCCs with and without MVI were statistically significant (all P＜0.05). The histogram parameters of D* and f showed no statistically significant differences between HCCs with and without MVI (all P＞0.05). The areas under the ROC curves (AUCs) were 0.707-0.874 for D and 0.668-0.720 for ADC. The largest AUC of D (5th percentile) showed significantly higher accuracy than that of ADC or tumor size (P = 0.009-0.046). With a cut-off of 0.403 × 10^-3 mm²/s, the 5th percentile of D value provided a sensitivity of 81% and a specificity of 85% in the prediction of MVI.

CONCLUSIONS

Histogram analysis of IVIM based on whole tumor volume can be useful for predicting MVI. The 5th percentile of D was most useful value to predict MVI of HCC.

How reliable are ADC measurements? A phantom and clinical study of cervical lymph nodes

Objective

To assess the reliability of ADC measurements in vitro and in cervical lymph nodes of healthy volunteers.

Methods

We used a GE 1.5 T MRI scanner and a first ice-water phantom according to recommendations released by the Quantitative Imaging Biomarker Alliance (QIBA) for assessing ADC against reference values. We analysed the target size effect by using a second phantom made of six inserted spheres with diameters ranging from 10 to 37 mm. Thirteen healthy volunteers were also scanned to assess the inter- and intra-observer reproducibility of volumetric ADC measurements of cervical lymph nodes.

Results

On the ice-water phantom, the error in ADC measurements was less than 4.3 %. The spatial bias due to the non-linearity of gradient fields was found to be 24 % at 8 cm from the isocentre. ADC measure reliability decreased when addressing small targets due to partial volume effects (up to 12.8 %). The mean ADC value of cervical lymph nodes was 0.87.10^-3 ± 0.12.10^-3 mm²/s with a good intra-observer reliability. Inter-observer reproducibility featured a bias of -5.5 % due to segmentation issues.

Conclusion

ADC is a potentially important imaging biomarker in oncology; however, variability issues preclude its broader adoption. Reliable use of ADC requires technical advances and systematic quality control.

Key Points

• ADC is a promising quantitative imaging biomarker.

• ADC has a fair inter-reader variability and good intra-reader variability.

• Partial volume effect, post-processing software and non-linearity of scanners are limiting factors.

• No threshold values for detecting cervical lymph node malignancy can be drawn.

Electronic supplementary material

The online version of this article (10.1007/s00330-017-5265-2) contains supplementary material, which is available to authorized users.

Pre-treatment DWI as a predictor of overall survival in locally advanced pancreatic cancer treated with Cyberknife radiotherapy and sequential S-1 therapy

Background

To identify the value of the pre-treatment apparent diffusion coefficient (ADC) derived from diffusion weighted imaging (DWI) in predicting the overall survival (OS) for locally advanced pancreatic cancer (LAPC) treated with Cyberknife followed by sequential S-1 chemotherapy.

Methods

Patients with UICC-T4 LAPC who underwent DWI scan (3.0 Tesla) using two b-values (0, 600 s/mm²) in our center between 2015 and 2017 were enrolled. Mean ADCs of the region of interest (ROI) drawn manually on DWI imaging were measured by two independent radiologists at an interval of 1 month. The association between prognostic factors and patient survival was determined using univariate and multivariate analyses. Cox proportional hazard model was used for identification of independent prognostic factors of OS.

Results

A total of 41 patients (28 males and 13 females) were included, with a median age of 64 years, with 5 patients (3 males and 2 females) lost. The median OS was 11.7 months (range 2.8–23.3) among all 41 patients. The 1-year OS was 46% (95% CI 30%–62%). Univariate and multivariate analyses indicated that pre-treatment ADC value (HR 10.652, P = 0.0093), age (HR 0.952, P = 0.015), CA19–9 (HR 1.001, P = 0.0022) and administration of S-1 (HR 0.128, P = 0.0002) were independent predicting factors of OS.

Conclusion

The mean ADC value of the primary tumor on pre-treatment DWI imaging was an independent predictor of OS in patients with LAPC receiving Cyberknife followed by sequential S-1.

Combination of Pre-Treatment DWI-Signal Intensity and S-1 Treatment: A Predictor of Survival in Patients with Locally Advanced Pancreatic Cancer Receiving Stereotactic Body Radiation Therapy and Sequential S-1

OBJECTIVE: To identify whether the combination of pre-treatment radiological and clinical factors can predict the overall survival (OS) in patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiation and sequential S-1 (a prodrug of 5-FU combined with two modulators) therapy with improved accuracy compared with that of established clinical and radiologic risk models. METHODS: Patients admitted with LAPC underwent diffusion weighted imaging (DWI) scan at 3.0-T (b = 600 s/mm²). The mean signal intensity (SI_b = 600) of region-of-interest (ROI) was measured. The Log-rank test was done for tumor location, biliary stent, S-1, and other treatments and the Cox regression analysis was done to identify independent prognostic factors for OS. Prediction error curves (PEC) were used to assess potential errors in prediction of survival. The accuracy of prediction was evaluated by Integrated Brier Score (IBS) and C index. RESULTS: 41 patients were included in this study. The median OS was 11.7 months (2.8-23.23 months). The 1-year OS was 46%. Multivariate analysis showed that pre-treatment SI_b = 600 value and administration of S-1 were independent predictors for OS. The performance of pre-treatment SI_b = 600 and S-1 treatment in combination was better than that of SI_b = 600 or S-1 treatment alone. CONCLUSION: The combination of pre-treatment SI_b = 600 and S-1 treatment could predict the OS in patients with LAPC undergoing SBRT and sequential S-1 therapy with improved accuracy compared with that of established clinical and radiologic risk models.

Application values of 3.0T magnetic resonance diffusion weighted imaging for distinguishing liver malignant tumors and benign lesions

The aim of the present study was to investigate the significance and values of 3.0T diffusion weighted imaging (DWI) to differentially diagnose benign and malignant space-occupying liver lesions. A total of 91 patients with liver space-occupying lesions (145 lesions) were admitted into Zhongnan Hospital of Wuhan University (Wuhan, China) from November 2015 to May 2016. Routine scanning, DWI and high-resolution T2-weighted imaging using spin-echo echo-planar imaging were performed on all patients, to compare the apparent diffusion coefficient (ADC) values of three regions of interest in lesions with normal liver tissue. The ADC values of malignant liver lesions compared with benign liver cysts demonstrated a statistically significant difference in low b-value (P<0.05) and there was also a significant difference between malignant lesion and hepatic cyst, hepatic hemangioma or hepatic abscess in middle b-value (P<0.05). The measured ADC value may be more conducive to identify the nature of the liver space-occupying lesions; as the ADC values of malignant liver lesion, liver cyst, and liver abscesses demonstrated a statistical significance in high b-value (P<0.05). The mean ADC values between malignant liver tumors compared with benign lesions indicated a statistically significant difference. In the present study, liver space-occupying lesions demonstrated different DWI features and ADC ranges, and 3.0T DWI may be a potential means to accurately determine the nature of lesions, identifying benign and malignant space-occupying lesions.

Optimized ROI size on ADC measurements of normal pancreas, pancreatic cancer and mass-forming chronic pancreatitis

Objectives

To investigate the effects of region of interest (ROI) sizes on apparent diffusion coefficient (ADC) measurements for the differentiation of normal pancreas (NP), pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP).

Results

There were no significant differences for the mean ADCs measured by 12 different-size ROIs for MFCP, or PDAC and NP (P = 0.858–1.0). With the increase of ROI size (≥ 55 mm²), ADCs of PDAC were significantly lower than those of NP (all P < 0.05), but there was no difference of the accuracy in ADC for differentiating the two groups only at a ROI size of 214 mm². When ROI size was above 99 mm², ADCs of MFCP were significantly lower than those of NP (all P < 0.05). There were no significant differences for any of the mean ADCs measured by 12 different-size ROIs between PDAC and MFCP (P > 0.05).

Materials and Methods

Diffusion-weighted imaging (DWI) was performed on 89 participants: 64 with PDAC, 7 with MFCP, as well as 18 healthy volunteers. ADC maps were created using mono-exponential model. A homemade software was used to measure the mean ADC values of 12 concentric round ROIs (areas: 15, 46, 55, 82, 99, 121, 134, 152, 161, 189, 214, 223, and 245 mm²) for the mass of lesions and the NP tissue.

Conclusions

In ADC measurements, the optimized ROI size is 214 mm² for the differentiation of PDAC and NP; ROI size of ≥ 99 mm² is recommended to differentiate between MFCP and NP. ADC was not useful for the differentiation of PDAC and MFCP.

Effect of region of interest size on ADC measurements in pancreatic adenocarcinoma

BACKGROUND

To investigate the influence of region of interest (ROI) size on tumor apparent diffusion coefficient (ADC) measurements in pancreatic cancer.

METHODS

The study population consisted of 64 patients with pathologically proved pancreatic ductal adenocarcinomas (PDACs), who underwent preoperative magnetic resonance imaging (MRI) examinations including diffusion-weighted imaging (DWI). The tumor ADCs were measured by two independent readers using six round ROIs with sizes ranging from 20 to 214 mm² (9 to 97 pixels) in both the six separate measurements. The intra- and inter-observer variabilities were analyzed by using the coefficient of variance (CV), the interclass correlation coefficient (ICC) and Bland-Altman analysis. The mean ADCs measured with the 6 different-sized ROIs were compared using one-way repeated analysis of variance. The sample sizes were calculated by using 80% power and a 5% significance level to detect 10 to 25% changes in ADC measurements.

RESULTS

The largest ROI (ROI₂₁₄) yielded the best intra-observer repeatability (CV, 6.3%; ICC, 0.93) and inter-observer reproducibility (CV, 10.1%; ICC, 0.84). The mean differences in ADC measurements ± limits of agreement between the two readers were (0.06 ± 0.47) × 10^-3 mm² for ROI₂₀, (0.08 ± 0.46) × 10^-3 mm² for ROI₄₆, (0.05 ± 0.37) × 10^-3 mm² for ROI₈₂, (0.07 ± 0.42) × 10^-3 mm² for ROI₁₁₅, (0.05 ± 0.43) × 10^-3 mm² for ROI₁₅₂ and (-0.02 ± 0.29) × 10^-3 mm² for ROI₂₁₄.

CONCLUSIONS

ROI size had a considerable influence on the ADC measurements of PDACs.

Diffusion-weighted quantitative MRI of pleural abnormalities: Intra- and interobserver variability in the apparent diffusion coefficient measurements

PURPOSE

To assess intra- and interobserver variability in the apparent diffusion coefficient (ADC) measurements of pleural abnormalities.

MATERIALS AND METHODS

Diffusion-weighted magnetic resonance imaging was performed in 34 patients to characterize pleural abnormalities, with a 1.5T unit at b values of 0/150/500/800 sec/mm² . In two sessions held 3 months apart, on perfusion-free ADC maps, two independent readers measured the ADC of pleural abnormalities (two readings for each reader in each case) using different methods of region-of-interest (ROI) positioning. In three methods, freehand ROIs were drawn within tumor boundaries to encompass the entire lesion on one or more axial slices (whole tumor volume [WTV], three slices observer-defined [TSOD], single-slice [SS]), while in two methods one or more ROIs were placed on the more restricted areas (multiple small round ROI [MSR], one small round ROI [OSR]). Measurement variability between readings by each reader (intraobserver repeatability) and between readers in first reading (interobserver repeatability) were assessed using intraclass correlation coefficient (ICC) and coefficient of variation (CoV). Analysis of variance (ANOVA) was performed to compare ADC values between the different methods. The measurement time of each case for all methods in first reading was recorded and compared between methods and readers.

RESULTS

All methods demonstrated good (MSR, OSR) and excellent (WTV, TSOD, SS) intra- and interreader agreement, with best and worst repeatability in WTV (lower ICC, 0.977; higher CoV, 3.5%) and OSR (lower ICC, 0.625; higher CoV, 22.8%), respectively. The lower 95% confidence interval of ICC resulted in fair to moderate agreement for OSR (up to 0.379) and in excellent agreement for WTV, TSV, and SS (up to 0.918). ADC values of OSR and MSR were significantly lower compared to other methods (P < 0.001). The OSR and SS required less measurement time (10 and 21/22 sec, respectively) compared to the others (P < 0.0001), while the WTV required the longest measurement time (132/134 sec) (P < 0.0001).

CONCLUSION

ADC measurements of pleural abnormalities are repeatable. The SS method has excellent repeatability, similar to WTV, but requires significantly less measurement time. Thus, its use should be preferred in clinical practice.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:769-782.

Effects of regions of interest methods on apparent coefficient measurement of the parotid gland in early Sjögren's syndrome at 3T MRI

BACKGROUND

The apparent diffusion coefficient (ADC) has been used to assess parotid gland abnormalities in Sjögren's syndrome (SS) patients; however, few data exist on the influence of region of interest (ROI) methods on ADC measurements.

PURPOSE

To assess the influence of ROI methods on ADC measurement, and their diagnostic ability in detecting parotid gland abnormalities in early SS patients.

MATERIAL AND METHODS

Thirteen early SS patients underwent parotid gland diffusion-weighted imaging scans at a 3.0 T MR unit. Two readers independently measured the parotid gland ADC value using three different ROIs (whole-gland [WG], single-slice [SS], and reader-based circular [RBC]). The ADC value based on three different ROIs (ADC-ROI_WG, ADC-ROI_SS, ADC-ROI_RBC) were compared between the SS group and a matched healthy control (HC) group (n = 19). Receiver operating characteristic (ROC) curves and intra-class correlation coefficients (ICC) were used to determine the diagnostic ability and reproducibility of the parameters.

RESULTS

The ADC-ROI_WG, ADC-ROI_SS, and ADC-ROI_RBC in the SS group were all significantly higher than those in HC group (all P < 0.05). The ADC-ROI_WG showed better diagnostic ability than did ADC-ROI_RBC (P = 0.0200), while no significant difference was found between ADC-ROI_WG and ADC-ROI_SS (P = 0.4636). The ROI_WG method showed the best inter- and intra-reader agreement (ICC, 0.902 and 0.928, respectively), followed by ROI_SS and ROI_RBC.

CONCLUSION

The ROI methods can influence the parotid gland ADC measurements and their diagnostic ability. Considering our results, we suggest using in clinical practice single-slice ROIs to measure the ADC of the parotid gland.

ADC histogram analysis for adrenal tumor histogram analysis of apparent diffusion coefficient in differentiating adrenal adenoma from pheochromocytoma

PURPOSE

To determine the diagnostic performance of apparent diffusion coefficient (ADC) histogram analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI) for differentiating adrenal adenoma from pheochromocytoma.

MATERIALS AND METHODS

We retrospectively evaluated 52 adrenal tumors (39 adenomas and 13 pheochromocytomas) in 47 patients (21 men, 26 women; mean age, 59.3 years; range, 16-86 years) who underwent DW 3.0T MRI. Histogram parameters of ADC (b-values of 0 and 200 [ADC₂₀₀ ], 0 and 400 [ADC₄₀₀ ], and 0 and 800 s/mm² [ADC₈₀₀ ])-mean, variance, coefficient of variation (CV), kurtosis, skewness, and entropy-were compared between adrenal adenomas and pheochromocytomas, using the Mann-Whitney U-test. Receiver operating characteristic (ROC) curves for the histogram parameters were generated to differentiate adrenal adenomas from pheochromocytomas. Sensitivity and specificity were calculated by using a threshold criterion that would maximize the average of sensitivity and specificity.

RESULTS

Variance and CV of ADC₈₀₀ were significantly higher in pheochromocytomas than in adrenal adenomas (P < 0.001 and P = 0.001, respectively). With all b-value combinations, the entropy of ADC was significantly higher in pheochromocytomas than in adrenal adenomas (all P ≤ 0.001), and showed the highest area under the ROC curve among the ADC histogram parameters for diagnosing adrenal adenomas (ADC₂₀₀ , 0.82; ADC₄₀₀ , 0.87; and ADC₈₀₀ , 0.92), with sensitivity of 84.6% and specificity of 84.6% (cutoff, ≤2.82) with ADC₂₀₀ ; sensitivity of 89.7% and specificity of 84.6% (cutoff, ≤2.77) with ADC₄₀₀ ; and sensitivity of 94.9% and specificity of 92.3% (cutoff, ≤2.67) with ADC₈₀₀ .

CONCLUSION

ADC histogram analysis of DW MRI can help differentiate adrenal adenoma from pheochromocytoma.

LEVEL OF EVIDENCE

3 J. Magn. Reson. Imaging 2017;45:1195-1203.

Diffusion Weighted Imaging for Differentiating Benign from Malignant Orbital Tumors: Diagnostic Performance of the Apparent Diffusion Coefficient Based on Region of Interest Selection Method

Objective

To evaluate the differences in the apparent diffusion coefficient (ADC) measurements based on three different region of interest (ROI) selection methods, and compare their diagnostic performance in differentiating benign from malignant orbital tumors.

Materials and Methods

Diffusion-weighted imaging data of sixty-four patients with orbital tumors (33 benign and 31 malignant) were retrospectively analyzed. Two readers independently measured the ADC values using three different ROIs selection methods including whole-tumor (WT), single-slice (SS), and reader-defined small sample (RDSS). The differences of ADC values (ADC-ROI_WT, ADC-ROI_SS, and ADC-ROI_RDSS) between benign and malignant group were compared using unpaired t test. Receiver operating characteristic curve was used to determine and compare their diagnostic ability. The ADC measurement time was compared using ANOVA analysis and the measurement reproducibility was assessed using Bland-Altman method and intra-class correlation coefficient (ICC).

Results

Malignant group showed significantly lower ADC-ROI_WT, ADC-ROI_SS, and ADC-ROI_RDSS than benign group (all p < 0.05). The areas under the curve showed no significant difference when using ADC-ROI_WT, ADC-ROI_SS, and ADC-ROI_RDSS as differentiating index, respectively (all p > 0.05). The ROI_SS and ROI_RDSS required comparable measurement time (p > 0.05), while significantly shorter than ROI_WT (p < 0.05). The ROI_SS showed the best reproducibility (mean difference ± limits of agreement between two readers were 0.022 [-0.080–0.123] × 10^-3 mm²/s; ICC, 0.997) among three ROI methods.

Conclusion

Apparent diffusion coefficient values based on the three different ROI selection methods can help to differentiate benign from malignant orbital tumors. The results of measurement time, reproducibility and diagnostic ability suggest that the ROI_SS method are potentially useful for clinical practice.

Differentiation between malignant and benign thyroid nodules and stratification of papillary thyroid cancer with aggressive histological features: Whole-lesion diffusion-weighted imaging histogram analysis

PURPOSE

To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features.

MATERIALS AND METHODS

This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC.

RESULTS

Mean ADC, median ADC, 5^th percentile ADC, 25^th percentile ADC, 75^th percentile ADC, 95^th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10^-6 mm² /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5^th percentile ADC, and 25^th percentile ADC. The 5^th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10^-6 mm² /s for differentiating between PTCs with and without extrathyroidal extension.

CONCLUSION

Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555.

Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility

There is considerable disparity in the published apparent diffusion coefficient (ADC) values across different anatomies. Institutions are increasingly assessing repeatability and reproducibility of the derived ADC to determine its variation, which could potentially be used as an indicator in determining tumour aggressiveness or assessing tumour response. In this manuscript, a review of selected articles published to date in healthy extra-cranial body diffusion-weighted magnetic resonance imaging is presented, detailing reported ADC values and discussing their variation across different studies. In total 115 studies were selected including 28 for liver parenchyma, 15 for kidney (renal parenchyma), 14 for spleen, 13 for pancreatic body, 6 for gallbladder, 13 for prostate, 13 for uterus (endometrium, myometrium, cervix) and 13 for fibroglandular breast tissue. Median ADC values in selected studies were found to be 1.28 × 10(-3) mm(2)/s in liver, 1.94 × 10(-3) mm(2)/s in kidney, 1.60 × 10(-3) mm(2)/s in pancreatic body, 0.85 × 10(-3) mm(2)/s in spleen, 2.73 × 10(-3) mm(2)/s in gallbladder, 1.64 × 10(-3) mm(2)/s and 1.31 × 10(-3) mm(2)/s in prostate peripheral zone and central gland respectively (combined median value of 1.54×10(-3) mm(2)/s), 1.44 × 10(-3) mm(2)/s in endometrium, 1.53 × 10(-3) mm(2)/s in myometrium, 1.71 × 10(-3) mm(2)/s in cervix and 1.92 × 10(-3) mm(2)/s in breast. In addition, six phantom studies and thirteen in vivo studies were summarized to compare repeatability and reproducibility of the measured ADC. All selected phantom studies demonstrated lower intra-scanner and inter-scanner variation compared to in vivo studies. Based on the findings of this manuscript, it is recommended that protocols need to be optimised for the body part studied and that system-induced variability must be established using a standardized phantom in any clinical study. Reproducibility of the measured ADC must also be assessed in a volunteer population, as variations are far more significant in vivo compared with phantom studies.