Apparent diffusion coefficient measurements in the differentiation between benign and malignant lesions: a systematic review

Quantitative diffusion weighted imaging in patients with hepatocellular carcinoma: effects of simultaneous multi-slice acceleration and gadoxetic acid administration

PURPOSE

To investigate whether simultaneous multi-slice (SMS) acceleration and gadoxetic acid administration affect the quantitative apparent diffusion coefficient (ADC) and signal-to-noise ratio (SNR) measurement of DWI in patients with HCC.

METHODS

This prospective study initially enrolled 208 patients with clinically suspected HCC. Free breathing SMS-DWI and conventional DWI (CON-DWI) were performed before and after gadoxetic acid administration. Lesion conspicuity, ADCs and SNRs of the HCC lesion and normal liver parenchyma were independently measured by two radiologists. The paired t test or Wilcoxon signed rank test was used to evaluate the differences of lesion conspicuity, ADCs and SNRs between SMS-DWI and CON-DWI, as well as those before and after gadoxetic acid administration.

RESULTS

A total of 102 HCC patients (90 men and 12 women; mean age, 54.6 ± 11.7 years) were finally included for analysis. SMS-DWI and CON-DWI demonstrated comparable lesion conspicuity (P = 0.081-0.566). For the influence of SMS acceleration, the SNRs of liver parenchyma on enhanced SMS-DWI were significantly higher than enhanced CON-DWI (P = 0.015). For the influence of gadoxetic acid administration, the mean ADCs were significantly higher on enhanced SMS-DWI than unenhanced SMS-DWI (HCC, P = 0.013; liver parenchyma, P = 0.032).

CONCLUSION

Quantitative ADC measurements of HCC and liver parenchyma were not affected by SMS acceleration, and SMS-DWI can provide higher SNR than CON-DWI. However, the ADC measurements can be affected by gadoxetic acid administration on SMS-DWI, so it is recommended to perform SMS-DWI before gadoxetic acid administration.

Multi-modal 3-Dimensional Visualization of Pediatric Neuroblastoma: Aiding Surgical Planning Beyond Anatomical Information

BACKGROUND

Patient-specific 3D models of neuroblastoma and relevant anatomy are useful tools for surgical planning. However, these models do not represent the heterogenous biology of neuroblastoma. This heterogeneity is visualized with the ADC and 123I-MIGB-SPECT-CT imaging. Combining these multi-modal data into preoperative 3D heatmaps, may allow differentiation of the areas of vital and non-vital tumor tissue. We developed a workflow to create multi-modal preoperative 3D models for neuroblastoma surgery.

METHODS

We included 7 patients who underwent neuroblastoma surgery between 2022 and 2023. We developed 3D models based on the contrast enhanced T1-weighted MRI scans. Subsequently, we aligned the corresponding ADC and 123I-MIBG-SPECT-CT images using rigid transformation. We estimated registration precision using the Dice score and the target registration error (TRE). 3D heatmaps were computed based on ADC and 123I-MIBG uptake.

RESULTS

The registration algorithm had a median Dice score of 0.81 (0.75-0.90) for ADC and 0.77 (0.65-0.91) for 123I-MIBG-SPECT. For the ADC registration, the median TRE of renal vessels was 4.90 mm (0.86-10.18) and of the aorta 4.67 mm (1.59-12.20). For the 123I -MIBG-SPECT imaging the TRE of the renal vessels was 5.52 mm (1.71-10.97) and 5.28 mm (3.33-16.77) for the aorta.

CONCLUSIONS

We successfully developed a registration workflow to create multi-modal 3D models which allows the surgeon to visualize the tumor and its biological behavior in relation to the surrounding tissue. Future research will include linking of pathological results to imaging data, to validate these multi-modal 3D models.

LEVEL OF EVIDENCE

Level IV.

TYPE OF STUDY

Clinical Research.

Computed diffusion-weighted imaging with a low-apparent diffusion coefficient-pixel cut-off technique for breast cancer detection

OBJECTIVE

This study aimed to compare the image quality and diagnostic performance of computed diffusion-weighted imaging (DWI) with low-apparent diffusion coefficient (ADC)-pixel cut-off technique (cDWI cut-off) and actual measured DWI (mDWI).

METHODS

Eighty-seven consecutive patients with malignant breast lesions and 72 with negative breast lesions who underwent breast MRI were retrospectively evaluated. Computed DWI with high b-values of 800, 1200, and 1500 s/mm2 and ADC cut-off thresholds of none, 0, 0.3, and 0.6 (×10-3 mm2/s) were generated from DWI with two b-values (0 and 800 s/mm2). To identify the optimal conditions, two radiologists evaluated the fat suppression and lesion reduction failure using a cut-off technique. The contrast between breast cancer and glandular tissue was evaluated using region of interest analysis. Three other board-certified radiologists independently assessed the optimised cDWI cut-off and mDWI data sets. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.

RESULTS

When an ADC cut-off threshold of 0.3 or 0.6 (× 10-3 mm2/s) was applied, fat suppression improved significantly (p < .05). The contrast of the cDWI cut-off with a b-value of 1200 or 1500 s/mm2 was better than the mDWI (p < .01). The ROC area under the curve for breast cancer detection was 0.837 for the mDWI and 0.909 for the cDWI cut-off (p < .01).

CONCLUSION

The cDWI cut-off provided better diagnostic performance than mDWI for breast cancer detection.

ADVANCES IN KNOWLEDGE

Using the low-ADC-pixel cut-off technique, computed DWI can improve diagnostic performance by increasing contrast and eliminating un-suppressed fat signals.

Apparent Diffusion Coefficient Reproducibility Across 3 T Scanners in a Breast Diffusion Phantom

BACKGROUND

To date, the accuracy and variability of diffusion-weighted MRI (DW-MRI) metrics have been reported in a limited number of scanner/protocol/coil combinations.

PURPOSE

To evaluate the reproducibility of DW-MRI estimates across multiple scanners and DW-MRI protocols and to assess the effects of using an 8-channel vs. 16-channel breast coil in a breast phantom.

STUDY TYPE

Prospective.

PHANTOM

Breast phantom containing tubes of water and differing polyvinylpyrrolidone (PVP) concentrations with apparent diffusion coefficients (ADCs) matching breast tissue.

FIELD STRENGTH/SEQUENCE

3 T (three standard and one wide bore), three DW-MRI single-shot echo planar imaging protocols of varying acquired spatial resolution.

ASSESSMENT

Accuracy of estimated ADCs was assessed using percent differences (PD) relative to nuclear magnetic resonance spectroscopy-derived reference values. Coefficients of variation (CV) were calculated to determine variation across scanners. CVs based on the median standard deviation (CV_M ) were used to evaluate tube-specific dispersion using 8- or 16-channel coils at a single scanner. ADCs of PVP-containing tubes were additionally normalized by the median water tube ADC to account for temperature effects.

STATISTICAL TESTS

Two-way repeated measures analysis of variance and post hoc tests were used to evaluate differences in ADC, CV, and CV_M across scanners and protocols (α = 0.05).

RESULTS

ADCs were within 11% (interquartile range [IQR] 7%) of reference values and significantly improved to 2% (IQR 7%) after normalization to an internal water reference. Normalization significantly reduced interscanner variability of ADC estimates from 7% to 4%. DW-MRI protocol did not affect ADC accuracy; however, the clinical and higher-resolution clinical protocols resulted in the greatest (9%) and least (6%) interscanner variability, respectively. The 8- and 16-channel receive coils yielded similar accuracy (PD: 12% vs. 16%) and precision (CV_M : 2.7% vs. 2.9%).

DATA CONCLUSION

Normalization by an internal reference improved interscanner ADC reproducibility. High-resolution protocols yielded comparably accurate and significantly less variable ADCs compared to a clinical standard protocol.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Diffusion Weighted Imaging of the Abdomen and Pelvis: Recent Technical Advances and Clinical Applications

Diffusion weighted imaging (DWI) serves as one of the most important functional magnetic resonance imaging techniques in abdominal and pelvic imaging. It is designed to reflect the diffusion of water molecules and is particularly sensitive to the malignancies. Yet, the limitations of image distortion and artifacts in single-shot DWI may hamper its widespread use in clinical practice. With recent technical advances in DWI, such as simultaneous multi-slice excitation, computed or reduced field-of-view techniques, as well as advanced shimming methods, it is possible to achieve shorter acquisition time, better image quality, and higher robustness in abdominopelvic DWI. This review discussed the recent advances of each DWI approach, and highlighted its future perspectives in abdominal and pelvic imaging, hoping to familiarize physicians and radiologists with the technical improvements in this field and provide future research directions.

[Radiologic Evaluation of Uterine Lesions Using a Pattern Recognition Approach]

It is important to distinguish uterine lesions from other lesions occurring in the pelvic cavity for the proper management. The primary radiological evaluation of uterine lesions is performed using transvaginal ultrasonography, and if the lesion is too large or shows atypical benign imaging findings, magnetic resonance imaging should be performed. Analyzing radiological findings of uterine lesions through a pattern recognition approach can help establish the accurate diagnosis and treatment plan. In this pictorial assay, we describe imaging characteristics of various lesions arising from the uterus and evaluate them based on the pattern recognition approach.

Preliminary Experience of 5.0 T Higher Field Abdominal Diffusion-Weighted MRI: Agreement of Apparent Diffusion Coefficient With 3.0 T Imaging

BACKGROUND

Recently, a prototype 5.0 T whole-body MRI scanner was developed. A 5.0 T diffusion-weighted imaging (DWI) may help overcome the issues that limit 3.0 T DWI.

PURPOSE

To evaluate the feasibility of 5.0 T high-field DWI in the upper abdomen and assess the agreement of the apparent diffusion coefficient (ADC) with that from 3.0 T abdominal DWI.

STUDY TYPE

Prospective proof of concept.

POPULATION

Nine volunteers (mean ± SD age: 37.3 ± 7.0 years, 8 M), eight healthy and one with liver and kidney cysts.

FIELD STRENGTH/SEQUENCE

3.0 T and 5.0 T; respiratory-triggered spin-echo echo-planar-imaging (SE-EPI)-based DWI sequence.

ASSESSMENT

Subjective image quality scores. The ADC values in abdominal organs (liver, pancreas, spleen, and kidney) were measured by two observers for evaluating the interobserver and interfield agreement.

STATISTICAL TESTS

Wilcoxon-rank sum test, Bland-Altman analysis, intraclass correlation coefficients (ICCs), and coefficients of variation (CVs).

RESULTS

The 5.0 T DWI displayed an increase in subjective image quality score compared to 3.0 T DWI without the significant difference (3.0 T DWI: 3.50 ± 0.47, 5.0 T DWI: 3.72 ± 0.42, P = 0.157). Both the interfield and interobserver agreements of ADC values were substantial to excellent (ICCs = 0.640-0.902). For all four upper abdominal organs, there were no significant differences between the ADC values measured by two observers and between the ADC values of 3.0 T and 5.0 T DWI (P = 0.134-1.000). The CVs of ADC measurements from 3.0 T and 5.0 T DWI were all less than 15.0% (6.7%-14.2%).

DATA CONCLUSION

The substantial to excellent agreements between the ADC values measured with 3.0 T and 5.0 T DWI for liver, pancreas, spleen, and kidney suggested that 5.0 T DWI can be applied for abdominal imaging. The ADC values from 5.0 T abdominal DWI hold the potential to serve as the quantitative markers for clinical investigations.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Diagnostic value of texture analysis of apparent diffusion coefficient maps for differentiating fat-poor angiomyolipoma from non-clear-cell renal cell carcinoma

PURPOSE

To investigate the feasibility of texture analysis of apparent diffusion coefficient (ADC) maps for differentiating fat-poor angiomyolipomas (fpAMLs) from non-clear-cell renal cell carcinomas (non-ccRCCs).

METHODS

In this bi-institutional study, we included two consecutive cohorts from different institutions with pathologically confirmed solid renal masses: 67 patients (fpAML = 46; non-ccRCC = 21) for model development and 39 (fpAML = 24; non-ccRCC = 15) for validation. Patients underwent preoperative magnetic resonance imaging (MRI), including diffusion-weighted imaging. We extracted 45 texture features using a software with volumes of interest on ADC maps. Receiver operating characteristic curve analysis was performed to compare the diagnostic performance between the random forest (RF) model (derived from extracted texture features) and conventional subjective evaluation using computed tomography and MRI by radiologists.

RESULTS

RF analysis revealed that grey-level zone length matrix long-zone high grey-level emphasis was the dominant texture feature for diagnosing fpAML. The area under the curve (AUC) of the RF model to distinguish fpAMLs from non-ccRCCs was not significantly different between the validation and development cohorts (p = .19). In the validation cohort, the AUC of the RF model was similar to that of board-certified radiologists (p = .46) and significantly higher than that of radiology residents (p = .03).

CONCLUSIONS

Texture analysis of ADC maps demonstrated similar diagnostic performance to that of board-certified radiologists for discriminating between fpAMLs and non-ccRCCs. Diagnostic performances in the development and validation cohorts were comparable despite using data from different imaging device manufacturers and institutions.

Whole-body [18F]-FDG-PET/MRI for staging of pediatric non-Hodgkin lymphoma: first results from a single-center evaluation

Aim

In 2015, the revised International Pediatric Non-Hodgkin Lymphoma Staging System was published. It mentions [¹⁸F]-FDG-PET/MRI as the latest method to perform whole-body imaging. However, supporting data are pending. Our aim was to investigate the performance of whole-body [¹⁸F]-FDG-PET/MRI in pediatric non-Hodgkin lymphoma patients by using a limited number of MRI sequences.

Materials and methods

Ten pediatric patients with histologically proven non-Hodgkin lymphoma underwent whole-body [¹⁸F]-FDG-PET/MRI at staging. The retrospective analysis included three steps: First, [¹⁸F]-FDG-PET and MR scans were evaluated separately by a nuclear medicine physician and a pediatric radiologist. Nineteen nodal and two extranodal regions as well as six organs were checked for involvement. Second, discrepant findings were reviewed together in order to reach consensus. Third, [¹⁸F]-FDG-PET/MRI findings were correlated with the results of other clinical investigations.

Results

Of the 190 lymph node regions evaluated, four were rated controversial. Consensus was reached by considering metabolic, functional and morphologic information combined. Concordantly, [¹⁸F]-FDG-PET and MRI detected Waldeyer’s ring involvement in two patients whose Waldeyer’s ring was negative on clinical assessment. In four patients MRI showed pleural effusion. However, in only two of them an increased glucose metabolism as a reliable sign of pleural involvement was detectable. In six patients [¹⁸F]-FDG-PET and MRI detected skeletal lesions although bone marrow biopsy was positive in only one of them.

Conclusion

Despite the small number of cases evaluated, whole-body [¹⁸F]-FDG-PET turned out to be a valuable tool for staging of pediatric non-Hodgkin lymphoma.

The value of diffusion-weighted imaging in diagnosing gallbladder malignancy: performance of a new parameter

AIM

To assess the value of the ratio of signal intensities at high and low b-values (b800/b0 ratio) during diffusion-weighted imaging (DWI) for gallbladder cancer diagnosis.

MATERIALS AND METHODS

All patients presenting with suspicious gallbladder lesions between January 2011 and December 2016 who underwent DWI and histopathological diagnoses of the lesions were assessed.

RESULTS

Thirty-two patients (24 men, eight women) were identified. Eighteen patients had benign gallbladder lesions while 14 had malignant lesions. The mean apparent diffusion coefficient (ADC) value was 1.62 (±0.57)×10^-3 mm²/s for benign cases and 1.27 (±0.39)×10^-3 mm²/s for malignant cases; this difference was not significant (p=0.0773). The mean b800/b0 ratio was 0.31 (±0.19) for benign cases and 0.48 (±0.13) for malignant cases; this difference was significant (p=0.007). The ROC curve for b800/b0 had an AUC of 0.782 (95% confidence interval [CI]: 0.616-0.947) with a sensitivity and specificity of 85.7% and 72.2%, respectively, at a cut-off point of 0.33.

CONCLUSION

The b800/b0 ratio can help differentiate benign and malignant gallbladder lesions and may be more reliable than ADC values in quantitative DWI assessments.

Differentiating Between Low- and High-grade Glioma Tumors Measuring Apparent Diffusion Coefficient Values in Various Regions of the Brain

Objectives

Our study aimed to apply the apparent diffusion coefficient (ADC) values to quantify the differences between low- and high-grade glioma tumors.

Methods

We conducted a multicenter, retrospective study between September to December 2019. Magnetic resonance imaging (MRI) diffusion-weighted images (DWIs), and the pathologic findings of 56 patients with glioma tumors (low grade = 28 and high grade = 28) were assessed to measure the ADC values in the tumor center, tumor edema, boundary area between tumor with normal tissue, and inside the healthy hemisphere. These values were compared between the two groups, and cut-off values were calculated using the receiver operating characteristic curve.

Results

We saw significant differences between the mean ADC values measured in the tumor center and edema between high- and low-grade tumors (p< 0.005). The ADC values in the boundary area between tumors with normal tissue and inside healthy hemisphere did not significantly differ in the groups. The ADC values at tumor center and edema were higher than 1.12 × 10^-3 mm²/s (sensitivity = 100% and specificity = 96.0%) and 1.15 × 10^-3 mm²/s (sensitivity = 75.0% and specificity = 64.0%), respectively, could be classified as low-grade tumors.

Conclusions

The ADC values from the MRI DWIs in the tumor center and edema could be used as an appropriate method for investigating the differences between low- and high-grade glioma tumors. The ADC values in the boundary area and healthy tissues had no diagnostic values in grading the glioma tumors.

Diagnostic performance of apparent diffusion coefficient (ADC) for differentiating endometrial carcinoma from benign lesions: a systematic review and meta-analysis

To determine the diagnostic performance of mean ADC values in the characterization of endometrial carcinoma (EC) from benign lesions by systematic review of the literature and performing meta-analysis. A systematic search of major electronic bibliographic databases was performed to find studies that used ADC values for differentiating EC from benign lesions. Two reviewers independently screened the titles and abstracts of the search results and then by reading the full texts selected the pertinent studies for final analyses. A bivariate random-effects model with pooled sensitivity and specificity values with 95% CI (confidence interval) was used. Summary receiver operating characteristic (SROC) curve and area under curve (AUC) were created. Between-study heterogeneity was measured using I squared (I2) index. Eleven studies including 269 ECs and 208 benign lesions were analyzed. Pooled average (95% CI) ADC in EC and benign lesions groups were, respectively, 0.82 (0.77-0.87) × 10-3 mm2/s and 1.41 (1.29-1.52) × 10-3 mm2/s. The combined (95% CI) sensitivity and specificity of mean ADC values for differentiating EC from benign lesions were 93% (87-96%; I2 = 41.19%) and 94% (88-97%; I2 = 46.91%), respectively. The AUC (95% CI) of the SROC curve was 98% (96-99%). ADC values had good diagnostic accuracy for differentiating EC from benign lesions. In order to recommend ADC measurement for detecting endometrial lesions in routine clinical practice, more primary studies, especially trials and comparative studies including hysteroscopically-guided biopsy method, with larger sample sizes are still required.

Differentiating malignant from benign salivary gland lesions: a multiparametric non-contrast MR imaging approach

The purpose of this study is to determine whether multiparametric non-contrast MR imaging including diffusion-weighted imaging (DWI), arterial spin labeling (ASL), and amide proton transfer (APT) weighted imaging can help differentiate malignant from benign salivary gland lesions. The study population consisted of 42 patients, with 31 benign and 11 malignant salivary gland lesions. All patients were evaluated using DWI, three-dimensional pseudo-continuous ASL, and APT-weighted imaging on 3 T MR imaging before treatment. Apparent diffusion coefficient (ADC), tumor blood flow (TBF), and APT-related signal intensity (APTSI) values within the lesion were compared between the malignant and benign lesions by Mann–Whitney U test. For each parameter, optimal cutoff values were chosen using a threshold criterion that maximized the Youden index for predicting malignant lesions. The performance of ADC, TBF, APTSI, individually and combined, was evaluated in terms of diagnostic ability for malignant lesions. Diagnostic performance was compared by McNemar test. APTSI was significantly higher in malignant lesions (2.18 ± 0.89%) than in benign lesions (1.57 ± 1.09%, p = 0.047). There was no significant difference in ADC or TBF between benign and malignant lesions (p = 0.155 and 0.498, respectively). The accuracy of ADC, TBF, and APTSI for diagnosing malignant lesions was 47.6%, 50.0%, and 66.7%, respectively; whereas the accuracy of the three parameters combined was 85.7%, which was significantly higher than that of each parameter alone (p = 0.001, 0.001, and 0.008, respectively). Therefore, the combination of ADC, TBF, and APTSI can help differentiate malignant from benign salivary gland lesions.

Differentiation of follicular carcinomas from adenomas using histogram obtained from diffusion-weighted MRI

AIM

To evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps from diffusion-weighted imaging (DWI) in the differentiation of follicular thyroid carcinoma (FTC) from follicular adenoma (FA) in nodules indeterminate on ultrasound-guided core needle biopsy (USCNB).

MATERIALS AND METHODS

This study was performed with institutional review board approval. Seventeen patients who were planned to undergo diagnostic lobectomy for an indeterminate thyroid nodule (atypical of unknown significance/follicular lesion of undetermined significance [AUS/FLUS] or suspicious for follicular neoplasm/follicular neoplasm [SFN]) on USCNB were enrolled prospectively. All patients underwent DWI on the day before surgery. Histogram parameters were derived from ADC values obtained from the whole extent of the tumours. The parameters were compared with the final diagnosis based on histopathological examination after surgery. The accuracy of the parameters in differentiating FTC from FA was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Twelve patients were confirmed as having FA and five patients as having FTC. Histogram parameters including the 10^th (ADC₁₀), 25^th (ADC₂₅), and 50^th (ADC₅₀) percentiles of the ADC values were significantly lower in FA than in FTC (p < 0.05, all). ROC curve analysis revealed that ADC₂₅ resulted in the highest AUC (0.867; confidence interval, 0.616-0.980), with a cut-off value of 0.352×10^-3 mm²/s.

CONCLUSION

Histogram parameters from ADC maps could differentiate FTC from FA effectively in indeterminate nodules on USCNB, with ADC₂₅ being the most promising parameter.

Applying Amide Proton Transfer-Weighted Imaging (APTWI) to Distinguish Papillary Thyroid Carcinomas and Predominantly Solid Adenomatous Nodules: Comparison With Diffusion-Weighted Imaging

Background: Amide proton transfer-weighted (ATPw) imaging is a novel MRI technique that has been used to identify benign and malignant tumors. The present study evaluated the role of APTw imaging in differentiating papillary thyroid carcinoma from predominantly solid adenomatous nodule.

Methods: This study included 24 cases of solitary papillary thyroid carcinoma, and 20 cases of solid adenomatous nodules. Normal thyroid tissues were examined in 12 healthy subjects. The healthy subjects, eight cases of adenomatous nodule with cystic degeneration, and 12 cases of thyroid goiter, were only considered in the descriptive analysis, not included in our statistical analysis. The mean APTw value and the apparent diffusion coefficients (ADCs) of papillary thyroid carcinoma and solid adenomatous nodule were compared via a Mann-Whitney U test and receiver operating characteristic (ROC)-curve analyses.

Results: The adenomatous nodule (3.3 ± 1.3%) exhibited significantly higher APTw value (p < 0.05) than that of the papillary thyroid carcinoma (1.8 ± 0.7%). The optimal cut-off value of the mean APTw value in differentiating papillary thyroid carcinoma from adenomatous nodule was 3.15%, with a sensitivity of 60% and a specificity of 100%. The mean ADC of papillary thyroid carcinoma (1.2 ± 0.2 × 10⁻³ mm²/s) was significantly lower than that of adenomatous nodule (2.0 ± 0.4 × 10⁻³ mm²/s). The optimal cut-off value of the mean ADC was 1.35 × 10⁻³ mm²/s, with a sensitivity of 100% and a specificity of 75%. Based on the ROC-curve analysis of APT and ADC, the ADC showed a higher area under the curve (AUC) than that of APT (AUC_APT = 0.84, AUC_ADC = 0.95).

Conclusion: APTw imaging may be as useful as DWI for the differentiation of papillary thyroid carcinoma from predominantly solid adenomatous nodule. Although the sensitivity of ADC was greater than that of APT, APT had greater specificity.

Pathologic Correlation of Cellular Imaging Using Apparent Diffusion Coefficient Quantification in Patients with Brain Metastases After Gamma Knife Radiosurgery

OBJECTIVE

To evaluate the role of apparent diffusion coefficient (ADC) in differentiating radiation necrosis (RN) from recurrent tumor after Gamma Knife radiosurgery (GKRS) for brain metastases (BMs).

METHODS

Forty-one patients with BM who underwent surgical intervention after GKRS at Cleveland Clinic (2006-2017) were included in this retrospective study. The ADC values of the growing lesions and the contralateral hemisphere were calculated using picture archiving and communication system. These values were correlated to the percentage of RN identified on pathologic evaluation of the surgical specimen.

RESULTS

The median age of the patients was 59 years (range, 25-86 years), and lung cancer (63.4%) was the most common malignancy. Median initial (pre-GKRS) target volume of the lesions was 5.4 cc (range, 0.135-45.6 cc), and median GKRS dose was 18.0 Gy. Surgical resection or biopsy was performed at a median of 176 days after GKRS. Two variables were statistically significant predictors of predominate RN (75%-100%) in the surgical specimen: 1) ADC of the lesion on the preresection magnetic resonance imaging (MRI) and 2) initial pre-GKRS target volume. ADC >1.5 × 10^-3 mm²/s within the lesion on MRI predicted significant RN on pathologic evaluation of the lesion (P < 0.05). Similarly, when the target volume before GKRS was large (>10 cc), the risk of identifying significant necrosis in the pathologic specimen was elevated (P < 0.05).

CONCLUSIONS

Our data suggest that the combination of lesion ADC on MRI prior to surgical intervention and the initial target volume can predict RN with reasonable accuracy.

Radiomics-based classification of hepatocellular carcinoma and hepatic haemangioma on precontrast magnetic resonance images

Background

To evaluate the feasibility of using radiomics with precontrast magnetic resonance imaging for classifying hepatocellular carcinoma (HCC) and hepatic haemangioma (HH).

Methods

This study enrolled 369 consecutive patients with 446 lesions (a total of 222 HCCs and 224 HHs). A training set was constituted by randomly selecting 80% of the samples and the remaining samples were used to test. On magnetic resonance (MR) images of HCC and HH obtained with in-phase, out-phase, T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) sequences, we outlined the target lesions and extracted 1029 radiomics features, which were classified as first-, second-, higher-order statistics and shape features. Then, the variance threshold, select k best, and least absolute shrinkage and selection operator algorithms were explored for dimensionality reduction of the features. We used four classifiers (decision tree, random forest, K nearest neighbours, and logistic regression) to identify HCC and HH on the basis of radiomics features. Two abdominal radiologists also performed the conventional qualitative analysis for classification of HCC and HH. Diagnostic performances of radiomics and radiologists were evaluated by receiver operating characteristic (ROC) analysis.

Results

Valuable radiomics features for building a radiomics signature were extracted from in-phase (n = 22), out-phase (n = 24), T2WI (n = 34) and DWI (n = 24) sequences. In comparison, the logistic regression classifier showed better predictive ability by combining four sequences. In the training set, the area under the ROC curve (AUC) was 0.86 (sensitivity: 0.76; specificity: 0.78), and in the testing set, the AUC was 0.89 (sensitivity: 0.822; specificity: 0.714). The diagnostic performance for the optimal radiomics-based combined model was significantly higher than that for the less experienced radiologist (2-years experience) (AUC = 0.702, p < 0.05), and had no statistic difference with the experienced radiologist (10-years experience) (AUC = 0.908, p>0.05).

Conclusions

We developed and validated a radiomics signature as an adjunct tool to distinguish HCC and HH by combining in-phase, out-phase, T2W, and DW MR images, which outperformed the less experienced radiologist (2-years experience), and was nearly equal to the experienced radiologist (10-years experience).

Diagnostic value of high b-value (2000 s/mm2) DWI for thyroid micronodules

The aim of the study was to assess the diagnostic value of high b-value (2000 s/mm) diffusion-weighted imaging (DWI) in differentiating malignant from benign thyroid micronodules.Consecutive patients with thyroid micronodules scheduled for Ultrasound (US)-guided fine-needle aspiration biopsy (FNAB) or surgery were underwent high b-value DWI with 3 b-values: 0, 800, and 2000 s/mm. Signal intensity ratios (SIRs) of thyroid micronodules to adjacent normal thyroid tissue on DWI were measured as SIRb0, SIRb800 and SIRb2000. Apparent diffusion coefficients (ADCs) according to the three different b-values were acquired as: ADCb0-800, ADCb0-2000 and ADCb0-800-2000. The 6 diagnostic indicators were evaluated by receiver operating characteristic (ROC) and diagnostic ability was compared between the high b-value DWI and US.Sixty-two malignant thyroid micronodules (48 patients, 13 men and 35 women, aged 44.8 ± 11.7 years) and 57 benign thyroid micronodules (40 patients, 6 men and 34 women, aged 49.6 ± 12.5 years) were enrolled into the final statistical analysis. Among the alone diagnostic indicators, SIRb2000 had the highest diagnostic ability in differentiating malignant from benign thyroid micronodules with area under curve (AUC) of 0.975, sensitivity of 90.32% and specificity of 96.49%. Compared to US, SIRb2000 had a significantly better diagnostic ability US for thyroid micronodules (P < .001) with dramatically raised positive predict value (96.6% vs 78.9%) and reduced false-positive rate (3.51% vs 26.32%).High b-value (2000 s/mm) DWI can contribute to differentiating malignant from benign thyroid micronodules.

Diagnostic performance of diffusion-weighted (DWI) and dynamic contrast-enhanced (DCE) MRI for the differentiation of benign from malignant soft-tissue tumors

BACKGROUND

A wide range of specificity values for the differentiation of benign and malignant soft-tissue tumors show the limitations of conventional MRI features. The data obtained by quantitative analysis of diffusion-weighted image (DWI) and dynamic contrast-enhanced (DCE) MRIs would provide more objective results, especially in terms of cellularity and perfusion.

PURPOSE

To evaluate the diagnostic efficacies of DWI and DCE MRI for the differentiation of malignant and benign soft-tissue tumors.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 136 patients (68 females, 68 males; age range 18-86 years, mean age 57.2 years) with soft-tissue tumors.

FIELD STRENGTH/SEQUENCE

3 T, DWI, DCE.

ASSESSMENT

Tumor sizes, margins, locations, the presence of involvement in bone or neurovascular bundle, peritumoral edema, heterogeneity, and tumor necrosis were investigated on conventional MR images. On DWIs, visual signal drops were assessed and ADC (apparent diffusion coefficient) values were measured. K^trans , K_ep , V_e , and iAUC values, and time-concentration curve (TCC) types were determined using DCE images.

STATISTICAL TESTS

The data were statistically analyzed to determine the abilities to differentiate benign and malignant tumors using the chi-square test, two-sample t-test, and receiver operating characteristic (ROC) analysis.

RESULTS

Seventy-three cases were malignant and 63 benign. Age (mean ages of benign/malignant tumors, 51.75/61.86 years; P = 0.0002) and gender (F:M = 40:23 [benign], F:M = 28:45 [malignant], P = 0.003) influenced the distinction between benign and malignant. Sizes, margins, neurovascular bundle involvement, peritumoral edema, and heterogeneity of the tumors on conventional MR images and DCE parameters (K^trans , K_ep , V_e , and iAUC, and TCC plots) obtained from focal region of interest within a narrow volume of interest significantly differentiated benign and malignant lesions (all P < 0.0001, except V_e [P = 0.0004]). For DWI with ADC mapping, all ADC values and visually signal drops were also significant (P < 0.0001).

DATA CONCLUSION

DWI and DCE-MRI and derived variables were significantly helpful in discriminating benign and malignant soft-tissue tumors complementary to conventional MRI.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:798-809.

A comparison of conventional and diffusion-weighted magnetic resonance imaging in the diagnosis of sialadenitis and pleomorphic adenoma

OBJECTIVES

The aim of this study was to compare the efficacy of conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) in correctly identifying the presence of disease in the major salivary glands and correctly distinguish sialadenitis from pleomorphic adenoma.

STUDY DESIGN

Twenty-one patients diagnosed with unilateral sialadenitis or pleomorphic adenoma were selected. The nonaffected contralateral glands were also analyzed. T1- and T2-weighted MRI and DWI were obtained using spin-echo pulse sequences with a 1.5 Tesla MRI device. The diagnostic performance of 3 observers was evaluated for detection of salivary gland alterations and differentiation between sialadenitis and pleomorphic adenoma based on evaluation of MRI in comparison with DWI.

RESULTS

Intra-and interobserver reliability ranged from 0.86 to 0.94. DWI demonstrated greater sensitivity and accuracy values compared with MRI for both detection of disease and differentiation of sialadenitis from pleomorphic adenoma, with specificity values that were greater than or equal to those of MRI. DWI yielded significantly higher diagnostic odds ratios compared with MRI for both identification of disease and differentiation between lesions.

CONCLUSIONS

DWI demonstrated better diagnostic performance in the detection of alterations in the salivary glands and in differentiating between sialadenitis and pleomorphic adenoma compared with conventional T1 and T2-weighted MRI.

The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest

OBJECTIVES

The preoperative prediction of the WHO grade of a meningioma is important for further treatment plans. This study aimed to assess whether texture analysis (TA) based on apparent diffusion coefficient (ADC) maps could non-invasively classify meningiomas accurately using tree classifiers.

METHODS

A pathology database was reviewed to identify meningioma patients who underwent tumour resection in our hospital with preoperative routine MRI scanning and diffusion-weighted imaging (DWI) between January 2011 and August 2017. A total of 152 meningioma patients with 421 preoperative ADC maps were included. Four categories of features, namely, clinical features, morphological features, average ADC values and texture features, were extracted. Three machine learning classifiers, namely, classic decision tree, conditional inference tree and decision forest, were built on these features from the training dataset. Then the performance of each classifier was evaluated and compared with the diagnosis made by two neuro-radiologists.

RESULTS

The ADC value alone was unable to distinguish three WHO grades of meningiomas. The machine learning classifiers based on clinical, morphological features and ADC value could achieve equivalent diagnostic performance (accuracy = 62.96%) compared to two experienced neuro-radiologists (accuracy = 61.11% and 62.04%). Upon analysis, the decision forest that was built with 23 selected texture features and the ADC value from the training dataset achieved the best diagnostic performance in the testing dataset (kappa = 0.64, accuracy = 79.51%).

CONCLUSIONS

Decision forest with the ADC value and ADC map-based texture features is a promising multiclass classifier that could potentially provide more precise diagnosis and aid diagnosis in the near future.

KEY POINTS

• A precise preoperative prediction of the WHO grade of a meningioma brings benefits to further treatment plans. • Machine learning models based on clinical, morphological features and ADC value could achieve equivalent diagnostic performance compared to experienced neuroradiologists. • The decision forest model built with 23 selected texture features and the ADC value achieved the best diagnostic performance (kappa = 0.64, accuracy = 79.51%).

Utility of high b-value (2000 sec/mm2) DWI with RESOLVE in differentiating papillary thyroid carcinomas and papillary thyroid microcarcinomas from benign thyroid nodules

Purpose

The aim of the study was to evaluate the role of high b-value (2000 sec/mm²) diffusion-weighted imaging (DWI) by using Readout Segmentation of Long Variable Echo-trains (RESOLVE) in differentiating papillary thyroid carcinomas (PTCs) and papillary thyroid microcarcinomas (PTMCs) from benign thyroid nodules.

Materials and methods

Consecutive patients with thyroid nodules scheduled for surgery underwent high b-value DWI with 3 b-values: 0, 800 and 2000 sec/mm². Signal intensity ratios (SIRs) of thyroid nodules to adjacent normal thyroid tissue on DWI were measured as: SIR_b0, SIR_b800 and SIR_b2000. Apparent diffusion coefficient (ADC) values based on the 3 different b-values were acquired as: ADC_b0-800, ADC_b0-2000, and ADC_b0-800-2000. The 6 diagnostic indicators were evaluated by receiver operating characteristic (ROC) and diagnostic ability was compared between high b-value DWI and Ultrasound (US).

Results

A total of 52 PTCs including 33 PTMCs (38 patients, 8 men and 30 women, aged 45.68 ± 11.93 years) and 62 benign thyroid nodules (46 patients, 7 men and 39 women, aged 48.73 ± 11.98 years) were enrolled into the final statistical analysis. ADC_b0-800-2000 had the highest diagnostic ability in differentiating PTCs from benign thyroid nodules with area under curve (AUC) of 0.944, sensitivity of 96.15% and specificity of 85.48%, and PTMCs from benign thyroid nodules with AUC of 0.940, sensitivity of 93.94% and specificity of 85.48%. On the strength of lower false-positive rates than US (14.52% vs. 32.26% for PTCs and 14.52% vs. 32.26% for PTMCs), ADC_b0-800-2000 had significantly better diagnostic ability in PTCs (P = 0.002) and PTMCs (P = 0.005).

Conclusion

High b-value (2000 sec/mm²) DWI can contribute to differentiating PTCs and PTMCs from benign thyroid nodules and can be potentially used as an active surveillance imaging method for PTMCs.

Evaluation and validation of the diagnostic value of the apparent diffusion coefficient for differentiating early-stage endometrial carcinomas from benign mimickers at 3T MRI

Previous researchers obtained various apparent diffusion coefficient (ADC) cutoff values to differentiate endometrial carcinoma from benign mimickers with 1.5T magnetic resonance imaging (MRI). Few studies have used 3T MRI or validated the effectiveness of these cutoff ADC values prospectively. This study was designed in two stages to obtain a cutoff ADC value at 3T MRI and to validate prospectively the role of the ADC value. First, we conducted a retrospective study of 60 patients to evaluate the diagnostic value of ADC by obtain a theoretical cutoff ADC value for differentiating between benign and malignant endometrial lesions. Student's t test revealed that ADC values for stage I endometrial carcinomas were significantly lower than those for benign lesions. The area under the curve value of the receiver operating characteristic curve was 0.993, and the cutoff ADC value was 0.98 × 10-3 mm2/s. The sensitivity, specificity, and overall accuracy of diagnosing stage I endometrial carcinoma were 100%, 97.1%, and 98.3%, respectively. Second, we conducted a prospective study of 26 patients to validate the use of the cutoff ADC value obtained in the study's first stage. The sensitivity, specificity, and overall accuracy for differentiating malignant from benign endometrial lesions based on the cutoff ADC value obtained earlier were as follows: radiologist 1 attained 86.67%, 100.0%, and 92.31%, respectively; radiologist 2 attained 86.67%, 91.0%, and 88.5%, respectively. Our results suggest that ADC values could be a potential biomarker for use as a quantitative and qualitative tool for differentiating between early-stage endometrial carcinomas and benign mimickers.

Diffusion-weighted imaging of the kidneys in haemolytic uraemic syndrome

OBJECTIVES

To evaluate the kidneys of patients with haemolytic uraemic syndrome (HUS) using diffusion-weighted imaging (DWI) and Doppler ultrasound (US) compared with healthy controls.

MATERIALS AND METHODS

Fifteen patients (mean age 33.3 years; three male; 12 female) with diarrhoea-positive HUS and 15 healthy volunteers were prospectively evaluated with DWI and Doppler US. A total apparent diffusion coefficient (ADC_TOT), and ADCs predominantly reflecting microperfusion (ADC_LOW) and diffusion (ADC_HIGH) were calculated. Doppler US evaluated renal vascularity and flow.

RESULTS

When compared with controls, kidneys affected by HUS showed reduced cortical ADC values (ADC_TOT 1.79±0.22 vs. 2.04±0.1x10^-3 mm²/s, P 0.001), resulting in either low corticomedullary differences (11/15 patients) or an inverted corticomedullary pattern (4/15 patients). Reduction of cortical ADC values was associated with a decrease of cortical vascularity on Doppler US (ADC_TOT, P<0.001; ADC_LOW, P 0.047). Kidneys with complete absence of the cortical vasculature on Doppler US (four patients) also demonstrated limited diffusion (ADC_HIGH, P 0.002). Low glomerular filtration rate, requirement for haemodialysis during hospitalization, and longer duration of haemodialysis were associated with decreased cortical diffusivity (ADC_TOT: P 0.04, 0.007, and <0.001, respectively).

CONCLUSION

DWI shows qualitative and quantitative abnormalities in kidneys affected by HUS, thereby extending the non-invasive assessment of renal parenchymal damage.

KEY POINTS

• In HUS, DWI is feasible for functional characterization of kidney involvement. • Kidneys affected by HUS showed reduced cortical diffusivity. • Decreased cortical diffusivity was associated with lower kidney function. • Requirement and duration of haemodialysis was linked to degree of cortical alterations.

Apparent diffusion coefficient of normal adrenal glands

Objective

To assess the feasibility and reliability of apparent diffusion coefficient (ADC) measurements of normal adrenal glands.

Materials and methods

This was a retrospective study involving 32 healthy subjects, divided into two groups: prepubertal (PreP, n = 12), aged from 2 months to 12.5 years (4 males; 8 females); and postpubertal (PostP, n = 20), aged from 11.9 to 61 years (5 males; 15 females). Diffusion-weighted magnetic resonance imaging (DW-MRI) sequences were acquired at a 1.5 T scanner using b values of 0, 20, 500, and 1000 s/mm². Two radiologists evaluated the images. ADC values were measured pixel-by-pixel on DW-MRI scans, and automatic co-registration with the ADC map was obtained.

Results

Mean ADC values for the right adrenal glands were 1.44 × 10^-3 mm²/s for the PreP group and 1.23 × 10^-3 mm²/s for the PostP group, whereas they were 1.58 × 10^-3 mm²/s and 1.32 × 10^-3 mm²/s, respectively, for the left glands. ADC values were higher in the PreP group than in the PostP group (p < 0.05). Agreement between readers was almost perfect (intraclass correlation coefficient, 0.84-0.94; p < 0.05).

Conclusion

Our results demonstrate the feasibility and reliability of performing DW-MRI measurements of normal adrenal glands. They could also support the feasibility of ADC measurements of small structures.

Region of interest demarcation for quantification of the apparent diffusion coefficient in breast lesions and its interobserver variability

PURPOSE

We aimed to compare two different methods of region of interest (ROI) demarcation and determine interobserver variability on apparent diffusion coefficient (ADC) in breast lesions.

METHODS

Thirty-two patients with 39 lesions were evaluated with a 3.0 Tesla scanner using a diffusion-weighted sequence with several b-values. Two observers independently performed the ADC measurements using: 1) a small fixed area of 10 mm2 ROI within the area with highest restriction; 2) a large ROI so as to include the whole lesion. Differences were assessed using the Wilcoxon-rank test. Bland-Altman method and Spearman coefficient were applied for interobserver variability and correlation analysis.

RESULTS

ADC values measured using the two ROI demarcation methods were significantly different for both observers (P = 0.026; P = 0.033). There was no interobserver variability in ADC values using either method (large ROI, P = 0.21; small ROI, P = 0.64). ADC values of malignant lesions were significantly different between the two methods (P < 0.001). Variability in ADC was ≤0.008×10-3 mm2/s for both methods. When using the same method, ADC values were significantly correlated between the observers (small ROI: r=0.990, P < 0.001; large ROI: r=0.985, P < 0.001).

CONCLUSION

The choice of ROI demarcation method influences ADC measurements. Small ROIs show less overlap in ADC values and higher ADC reproducibility, suggesting that this method may improve lesion discrimination. Interobserver variability was low for both methods.

Contribution of IVIM to Conventional Dynamic Contrast-Enhanced and Diffusion-Weighted MRI in Differentiating Benign from Malignant Breast Masses

BACKGROUND

The aim of this study was to determine whether the indicators obtained from intravoxel incoherent motion (IVIM) imaging can improve the characterization of benign and malignant breast masses compared with conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI).

PATIENTS AND METHODS

This study included 23 benign and 31 malignant breast masses of 48 patients. Main indicators were initial enhancement ratio (IER), time-signal intensity curve (TIC), apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudodiffusivity (D*), and perfusion fraction (f). The discriminative abilities of the different models were compared by means of receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) analysis.

RESULTS

D had the highest AUC (0.980), sensitivity (93.55%), specificity (100%), and diagnostic accuracy (96.36%). Both D and TIC could provide the independent predicted features for malignant breast masses. The combination of D and TIC had an AUC of up to 0.990.

CONCLUSION

D of IVIM can effectively complement existing conventional DCE-MRI and DW-MRI in differentiating malignant from benign breast masses. IVIM combined with DCE-MRI is a robust means of evaluating breast masses.

Short-term follow-up MRI after unplanned resection of malignant soft-tissue tumours; quantitative measurements on dynamic contrast enhanced and diffusion-weighted MR images

OBJECTIVE

To determine the diagnostic availability of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MR images for evaluating residual tumours at short-term follow-up after unplanned excision of malignant soft-tissue tumours.

METHODS

From January 2013 to September 2014, 38 patients underwent first follow-up MRI, including DCE and DW imaging (DWI), within 3 months of unplanned malignant soft-tissue tumour excision. The presence or absence of definite nodule formation, focal fluid/haematoma collection, oedema and fascial thickening around or at tumour beds were evaluated using conventional MR images. The volume transfer constant between blood plasma and extracellular/extravascular space (EES) (Ktrans), rate constant between EES and blood plasma (Kep), volume of EES space per unit volume of tissue and initial area under the concentration curve (iAUC) values with time-concentration curve (TCC) plots were obtained on DCE images, and apparent diffusion coefficient (ADC) values were measured on ADC maps. All data were statistically analyzed.

RESULTS

Of the 21 patients who underwent re-excision, 12 patients had a residual tumor and 9 did not. All conventional MRI variables, except definite nodule formation, were insignificantly related to the presence of residual tumour. However, ADC values were found to be significantly associated with the presence of residual tumour, as were the DCE MRI variables, Ktrans, Kep and iAUC. In particular, TCC pattern and Kep were most significantly associated with residual tumour.

CONCLUSION

Additional DCE images may be useful for determining the presence of residual tumours in tumour beds during short-term follow-up after inadequate malignant soft-tissue tumour excision.

ADVANCES IN KNOWLEDGE

The addition of DCE MRI and quantitative analysis of the images obtained might be useful for determining the presence of residual tumour in a tumour bed during short-term follow-up after inadequate excision of a malignant soft-tissue tumour, although DWI was also found to be helpful.

Diffusion-weighted magnetic resonance imaging for the initial characterization of non-fatty soft tissue tumors: correlation between T2 signal intensity and ADC values

OBJECTIVE

To evaluate the performance of quantitative diffusion-weighted imaging (DWI) correlated with T2 signal in differentiating non-fatty benign from malignant tumors.

MATERIAL AND METHODS

A total of 76 patients with a histologically confirmed non-fatty soft tissue tumors (46 benign and 30 malignant) were prospectively included in this ethics committee approved study. All patients signed an informed consent and underwent MRI with DWI with two b values (0 and 600). ADC values from the solid components of these tumors were obtained and were correlated with the lesion's signal intensity on T2-weighted fat-saturated sequences. ADC values were obtained from adjacent normal muscle to allow calculation of tumor/muscle ADC ratios.

RESULTS

There were 58 hyperintense and 18 iso or hypointense lesions. All hypointense lesions were benign. The mean ADC values for benign and malignant tumors were 1.47 ± 0.54 × 10(-3) and 1.17 ± 0.38 × 10(-3) mm(2)/s respectively (p < 0.005). The mean ADC ratio in benign iso or hypointense tumors was significantly lower than that of hyperintense ones (0.76 ± 0.21 versus 1.58 ± 0.82 - p < 0.0001). An ADC ratio lower than 0.915 was highly specific for malignancy (96.4 %), whereas an ADC ratio higher than 1.32 was highly sensitive for benign lesions (90 %).

CONCLUSION

ADC analysis can be useful in the initial characterization of T2 hyperintense non-fatty soft tissue masses, although this technique alone is not likely to change patient management.

Diffusion-weighted MRI in differentiating malignant from benign thyroid nodules: a meta-analysis

OBJECTIVES

To perform a meta-analysis to evaluate the diagnostic efficacy of diffusion-weighted imaging (DWI) in differentiating malignant from benign thyroid nodules.

DESIGN

A meta-analysis.

DATA SOURCES AND STUDY SELECTION

Medical and scientific literature databases were searched for original articles published up to August 2015. Studies were selected if they (1) included diagnostic DWI for differentiating malignant from benign thyroid lesions, (2) included patients who later underwent biopsy and (3) presented sufficient data to enable the construction of contingency tables.

DATA SYNTHESIS

For each study, the true-positive, false-positive, true-negative and false-negative values were extracted or derived, and 2×2 contingency tables were constructed. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) instrument. The heterogeneity test, threshold effect test, subgroup analyses and publication bias analyses were performed.

RESULTS

From the 113 identified search results, 15 studies, representing a total of 765 lesions, were included in the meta-analysis. We detected heterogeneity between studies but found no evidence of publication bias. The methodological quality was moderate. The pooled weighted sensitivity was 0.90 (95% CI 0.85 to 0.93); the specificity was 0.95 (95% CI 0.88 to 0.98); the positive likelihood ratio was 16.49 (95% CI 7.37 to 36.86); the negative likelihood ratio was 0.11 (95% CI 0.08 to 0.16); and the diagnostic OR was 150.73 (95% CI 64.96 to 349.75). The area under the receiver operator characteristic curve was 0.95 (95% CI 0.93 to 0.97).

CONCLUSIONS

Quantitative DWI may be a non-invasive, non-radiative and accurate method of distinguishing malignant from benign thyroid nodules. Nevertheless, large-scale trials are necessary to assess its clinical value and to establish standards regarding b values and cut-off values for DWI-based diagnosis.

Diagnosed chest lesion on diffusion-weighted magnetic resonance images using apparent diffusion coefficients

PURPOSE

A novel diagnostic method using the standard deviation (SD) value of apparent diffusion coefficient (ADC) by diffusion-weighted (DWI) magnetic resonance imaging (MRI) is applied for differential diagnosis of primary chest cancers, metastatic tumors and benign tumors.

MATERIALS AND METHODS

This retrospective study enrolled 27 patients (20 males, 7 female; age, 15-85; mean age, 68) who had thoracic mass lesions in the last three years and underwent an MRI chest examination at our institution. In total, 29 mass lesions were analyzed using SD of ADC and DWI. Lesions were divided into five groups: Primary lung cancers (N = 10); esophageal cancers (N = 5); metastatic tumors (N = 8); benign tumors (N = 3); and inflammatory lesions (N = 3). Quantitative assessment of MRI parameters of mass lesions was performed. The ADC value was acquired based on the average of the entire tumor area. The error-plot, t-test and the area under receiver operating characteristic (AUC) were applied for statistical analysis.

RESULTS

The SD of ADC value (mean±SD) was (4.867±1.359)×10-4 mm2/sec in primary lung cancers, and (3.598±0.350)×10-4 mm2/sec in metastatic tumors. The SD of ADC values of primary lung cancers and metastatic tumors (P <  0.05) were significantly different and the AUC was 0.800 (P <  0.05). The means of SD of ADC values was 4.532±1.406×10-4 mm2/sec and 2.973±0.364×10-4 mm2/sec for malignant tumors (including primary lung cancers, esophageal cancers) and benign tumors with respectively. The mean of SD of ADC values between malignant chest tumors and benign chest tumors was shown significant difference (P <  0.01). The values of AUC was 0.967 between malignant chest tumors and benign chest tumors (P <  0.05). The ADC values for primary lung cancers, metastatic tumors and benign tumors were not significantly difference (P >  0.05).

CONCLUSIONS

The mean of SD of ADC value by DWI can be used for differential diagnosis of chest lesions.

Clinical applications of diffusion-weighted magnetic resonance imaging in diagnosis of renal lesions - a systematic review

Diffusion-weighted magnetic resonance imaging (DW-MRI) is an established technique to detect the changes of the diffusion of water in biological tissues and reflect the pathophysiological process on the molecular level. It is a promising non-invasive imaging modality in detection of microstructural and functional changes in pathologies of kidney. To systematically review the research advancement of the DW-MRI in diagnosis of renal lesions, a systematic literature search was performed up to 8 October 2014 using the MEDLINE/PubMed and Embase databases for articles reporting on DW-MRI in diagnosis of renal lesions. Only articles with full data about DW-MRI application with potential implication in solving usually encountered clinical challenges about renal lesions were finally examined. The clinical application of DW-MRI allows a better understanding of some pathologic conditions of the kidney including renal insufficiency, renal artery stenosis, ureteral obstruction, foetal kidney disease, hydronephrosis and pyonephrosis. In addition, DW-MRI can also provide clinicians with the information of function evaluation of renal allograft and curative effect assessment of renal tumour. In summary, performance of renal DW-MRI, presuming that measurements are high quality, will further boost this modality, particularly for early detection of diffusion renal conditions, as well as more accurate characterization of renal lesions.

Childhood extracranial neoplasms: the role of imaging in drug development and clinical trials

Cancer is the leading cause of death in children older than 1 year of age and new drugs are necessary to improve outcomes. Imaging is crucial to the drug development process and assessment of therapeutic response. In adults, tumours are often assessed with CT using size criteria. Unfortunately, techniques established in adults are not necessarily applicable in children due to differing pathophysiology, ability to cooperate and increased susceptibility to ionising radiation. MRI, in particular quantitative MRI, has to date not been fully utilised in children with extracranial neoplasms. The specific challenges of imaging in children, the potential for functional imaging techniques to inform upon and their inclusion in clinical trials are discussed.

Diffusion characteristics of pediatric pineal tumors

BACKGROUND

Diffusion weighted imaging (DWI) has been shown to be helpful in characterizing tumor cellularity, and predicting histology. Several works have evaluated this technique for pineal tumors; however studies to date have not focused on pediatric pineal tumors.

OBJECTIVE

We evaluated the diffusion characteristics of pediatric pineal tumors to confirm if patterns seen in studies using mixed pediatric and adult populations remain valid.

MATERIALS AND METHODS

This retrospective study was performed after Institutional Review Board approval. We retrospectively evaluated all patients 18 years of age and younger with pineal tumors from a single institution where preoperative diffusion weighted imaging as well as histologic characterization was available.

RESULTS

Twenty patients (13 male, 7 female) with pineal tumors were identified: seven with pineoblastoma, four with Primitive Neuroectodermal Tumor (PNET), two with other pineal tumors, and seven with germ cell tumors including two germinomas, three teratomas, and one mixed germinoma-teratoma. The mean apparent diffusion coefficient (ADC) values in pineoblastoma (544 ± 65 × 10⁻⁶ mm²/s) and pineoblastoma/PNET (595 ± 144 × 10⁻⁶ mm²/s) was lower than that of the germ cell tumors (1284 ± 334 × 10⁻⁶ mm²/s; p < 0.0001 vs pineoblastoma). One highly cellular germinoma had an ADC value of 694 × 10⁻⁶ mm²/s.

CONCLUSION

ADC values can aid in differentiation of pineoblastoma/PNET from germ cell tumors in a population of children with pineal masses.

Breast DWI at 3 T: influence of the fat-suppression technique on image quality and diagnostic performance

AIM

To evaluate two fat-suppression techniques: short tau inversion recovery (STIR) and spectral adiabatic inversion recovery (SPAIR) regarding image quality and diagnostic performance in diffusion-weighted imaging (DWI) of breast lesions at 3 T.

MATERIALS AND METHODS

Ninety-two women (mean age 48 ± 12.1 years; range 21-78 years) underwent breast MRI. Two DWI pulse sequences, with b-values (50 and 1000 s/mm(2)) were performed with STIR and SPAIR. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), suppression homogeneity, and apparent diffusion coefficient (ADC) values were quantitatively assessed for each technique. Values were compared between techniques and lesion type. Receiver operating characteristics (ROC) analysis was used to evaluate lesion discrimination.

RESULTS

One hundred and fourteen lesions were analysed (40 benign and 74 malignant). SNR and CNR were significantly higher for DWI-SPAIR; fat-suppression uniformity was better for DWI-STIR (p < 1 × 10(-4)). ADC values for benign and malignant lesions and normal tissue were 1.92 × 10(-3), 1.18 × 10(-3), 1.86 × 10(-3) s/mm(2) for DWI-STIR and 1.80 × 10(-3), 1.11 × 10(-3), 1.79 × 10(-3) s/mm(2) for SPAIR, respectively. Comparison between fat-suppression techniques showed significant differences in mean ADC values for benign (p = 0.013) and malignant lesions (p = 0.001). DWI-STIR and -SPAIR ADC cut-offs were 1.42 × 10(-3) and 1.46 × 10(-3) s/mm(2), respectively. Diagnostic performance for DWI-STIR versus SPAIR was: accuracy (81.6 versus 83.3%), area under curve (87.7 versus 89.2%), sensitivity (79.7 versus 85.1%), and specificity (85 versus 80%). Positive predictive value was similar.

CONCLUSION

The fat-saturation technique used in the present study may influence image quality and ADC quantification. Nevertheless, STIR and SPAIR techniques showed similar diagnostic performances, and therefore, both are suitable for use in clinical practice.

ADC values in diffusion-weighted MRI and their relationship with age, gender and BMI in healthy people's pancreases

OBJECTIVE

The aim of this study is to use diffusion-weighted MRI to assess the apparent diffusion coefficient (ADC) values in head, body and tail sections of the pancreas in healthy subjects and the relationships between these values and age, gender and body mass index (BMI) of these cases.

METHODS

This study was conducted on 82 participants who were referred to the Tabesh Medical Imaging Center, Tabriz, Islamic Republic of Iran, during 2013. Echo-planar diffusion-weighted imaging of the pancreas was carried out with b-values of 50, 400 and 800 s mm(-2), and ADC values were assessed for the head, body and tail sections of the pancreas.

RESULTS

The ADC values for the head, body and tail sections of the pancreas in female participants were significantly greater than those in male subjects (p < 0.05). ADC values for these parts among subjects with different BMI differed significantly (p < 0.05). Regarding age, there were no statistically meaningful differences among the ADC values for the three parts (p > 0.05).

CONCLUSION

Gender and BMI effect the ADC values of the three sections of the pancreas. Thus, knowledge of the basic values based on gender and BMI can improve diagnostics. Having looked at age factor, it seems that the ADC values were not significantly different.

ADVANCES IN KNOWLEDGE

According to the results pancreatic ADC values appear to be influenced by gender and BMI but not by age.

Diffusion-weighted imaging: determination of the best pair of b-values to discriminate breast lesions

OBJECTIVE

In breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0 T.

METHODS

152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000 s mm(-2). ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types.

RESULTS

Considering the cut-off values 1.46 and 1.49 × 10(3)mm(2) s(-1), the pairs 50, 1000 and 200, 800 s mm(-2) showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000 s mm(-2) with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86 ± 0.46, 1.77 ± 0.37 and 1.15 ± 0.46 × 10(-3) mm(2) s(-1) for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCall (ADC calculated from the full set of b - values) [difference = 0.0075 × 10(-3) mm(2) s(-1); confidence interval 95%: (-0.0036; 0.0186); p = 0.18].

CONCLUSION

The diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000 s mm(-2).

ADVANCES IN KNOWLEDGE

The best b-value pair for lesion discrimination and characterization through ADC quantification was 50, 1000 s mm(-2).

Whole-body MRI for initial staging of paediatric lymphoma: prospective comparison to an FDG-PET/CT-based reference standard

OBJECTIVE

To compare whole-body MRI, including diffusion-weighted imaging (whole-body MRI-DWI), with FDG-PET/CT for staging newly diagnosed paediatric lymphoma.

METHODS

A total of 36 children with newly diagnosed lymphoma prospectively underwent both whole-body MRI-DWI and FDG-PET/CT. Whole-body MRI-DWI was successfully performed in 33 patients (mean age 13.9 years). Whole-body MRI-DWI was independently evaluated by two blinded observers. After consensus reading, an unblinded expert panel evaluated the discrepant findings between whole-body MRI-DWI and FDG-PET/CT and used bone marrow biopsy, other imaging data and clinical information to derive an FDG-PET/CT-based reference standard.

RESULTS

Interobserver agreement of whole-body MRI-DWI was good [all nodal sites together (κ = 0.79); all extranodal sites together (κ = 0.69)]. There was very good agreement between the consensus whole-body MRI-DWI- and FDG-PET/CT-based reference standard for nodal (κ = 0.91) and extranodal (κ = 0.94) staging. The sensitivity and specificity of consensus whole-body MRI-DWI were 93 % and 98 % for nodal staging and 89 % and 100 % for extranodal staging, respectively. Following removal of MRI reader errors, the disease stage according to whole-body MRI-DWI agreed with the reference standard in 28 of 33 patients.

CONCLUSIONS

Our results indicate that whole-body MRI-DWI is feasible for staging paediatric lymphoma and could potentially serve as a good radiation-free alternative to FDG-PET/CT.

KEYPOINTS

• Accurate staging is important for treatment planning and assessing prognosis • Whole-body MRI-DWI could be a good radiation-free alternative to FDG-PET/CT • Interobserver agreement of whole-body MRI-DWI is good • Agreement between whole-body MRI and the FDG-PET/CT reference standard is good • Most discrepancies were caused by suboptimal accuracy of size measurements on MRI.

Diffusion weighted MRI in chronic viral hepatitis: correlation between ADC values and histopathological scores

Objective

To investigate the utility of apparent diffusion coefficient (ADC) measurement in the diagnosis of chronic viral hepatitis (CVH) and correlation between ADC values and histopathologic severity of CVH.

Materials and methods

The ADC values of liver parenchyma on diffusion-weighted magnetic resonance imaging (DWMRI) were measured in 50 patients with a history of CVH and 51 healthy subjects at b 100, b 600 and b 1,000 gradients. Comparison between mean ADC values of the CVH and control groups and correlation results between ADC values and necroinflammation and fibrosis scores in CVH were obtained.

Results

Mean ADC values of CVH patients were significantly lower than mean ADC values of the control group at b 100 and b 600 gradients (P < 0.05). There was no significant difference between the CVH and control groups at the b 1,000 gradient (P > 0.05). No significant correlation was found between ADC values and histopathologic scores of CVH (P > 0.05).

Conclusion

ADC values obtained at the b 100 and b 600 gradients can be used to distinguish between the liver parenchyma of CVH and healthy subjects. ADC measurement was not found to be useful for estimation of the degree of necroinflammation and fibrosis in CVH.

Teaching Points

• In chronic viral hepatitis apparent coefficient values are decreased in the liver

• There is no correlation between ADC values and histopathologic severity of CVH

• DW images obtained at low b values have more ability to demonstrate an ADC decrease in viral hepatitis

Characterization of focal pancreatic lesions using normalized apparent diffusion coefficient at 1.5-Tesla: preliminary experience

PURPOSE

To compare the capabilities of apparent diffusion coefficient (ADC) and normalized ADC using the pancreatic parenchyma as reference organ in the characterization of focal pancreatic lesions.

PATIENTS AND METHODS

Thirty-six patients with focal pancreatic lesions (malignant, n=18; benign tumors, n=10; focal pancreatitis, n=8) underwent diffusion-weighted MR imaging (DWI) at 1.5-Tesla using 3 b values (b=0, 400, 800 s/mm(2)). Lesion ADC and normalized lesion ADC (defined as the ratio of lesion ADC to apparently normal adjacent pancreas) were compared between lesion types using nonparametric tests.

RESULTS

Significant differences in ADC values were found between malignant (1.150 × 10(-3)mm(2)/s) and benign tumors (2.493 × 10(-3)mm(2)/s) (P=0.004) and between benign tumors and mass-forming pancreatitis (1.160 × 10(-3)mm(2)/s) (P=0.0005) but not between malignant tumors and mass-forming pancreatitis (P=0.1092). Using normalized ADC, significant differences were found between malignant tumors (0.933 × 10(-3)mm(2)/s), benign tumors (1.807 × 10(-3)mm(2)/s) and mass-forming pancreatitis (0.839 × 10(-3)mm(2)/s) (P<0.0001).

CONCLUSION

Our preliminary results suggest that normalizing ADC of focal pancreatic lesions with ADC of apparently normal adjacent pancreatic parenchyma provides higher degrees of characterization of focal pancreatic lesions than the conventional ADC does.