Quantitative Analysis Of Diffusion-weighted Imaging Research Articles

Characterization of Primary Mucinous Ovarian Cancer by Diffusion-Weighted and Dynamic Contrast Enhancement MRI in Comparison with Serous Ovarian Cancer

(1) Background. The purpose of this study is to evaluate the diagnostic accuracy of a quantitative analysis of diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI of mucinous ovarian cancer (MOC). It also aims to differentiate between low grade serous carcinoma (LGSC), high-grade serous carcinoma (HGSC) and MOC in primary tumors. (2) Materials and Methods. Sixty-six patients with histologically confirmed primary epithelial ovarian cancer (EOC) were included in the study. Patients were divided into three groups: MOC, LGSC and HGSC. In the preoperative DWI and DCE MRI, selected parameters were measured: apparent diffusion coefficients (ADC), time to peak (TTP), and perfusion maximum enhancement (Perf. Max. En.). ROI comprised a small circle placed in the solid part of the primary tumor. The Shapiro-Wilk test was used to test whether the variable had a normal distribution. The Kruskal-Wallis ANOVA test was used to determine the p-value needed to compare the median values of interval variables. (3) Results. The highest median ADC values were found in MOC, followed by LGSC, and the lowest in HGSC. All differences were statistically significant (p < 0.000001). This was also confirmed by the ROC curve analysis for MOC and HGSC, showing that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC (p < 0.001). In the type I EOCs, i.e., MOC and LGSC, ADC has less differential value (p = 0.032), and TTP can be considered the most valuable parameter for diagnostic accuracy (p < 0.001). (4) Conclusions. DWI and DCE appear to be very good diagnostic tools in differentiating between serous carcinomas (LGSC, HGSC) and MOC. Significant differences in median ADC values between MOC and LGSC compared with those between MOC and HGSC indicate the usefulness of DWI in differentiating between less and more aggressive types of EOC, not only among the most common serous carcinomas. ROC curve analysis showed that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC. In contrast, TTP showed the greatest value for differentiating between LGSC and MOC.

Adjunct value of qualitative and quantitative analysis of diffusion-weighted imaging in musculoskeletal tumors

Adjunct value of qualitative and quantitative analysis of diffusion-weighted imaging in musculoskeletal tumors

Quantitative analysis of diffusion-weighted imaging and signal-to-noise ratio on the efficacy of albendazole liposome in the treatment of cerebral alveolar echinococcosis

OBJECTIVE: To investigate the feasibility of diffusion-weighted imaging (DWI) and signal-to-noise ratio (SNR) of lesions in evaluating the efficacy of albendazole liposomes in the treatment of cerebral alveolar echinococcosis (CAE).MATERIALS AND METHODS: Sixteen patients with CAE who met the inclusion criteria from April 2017 to December 2020 were enrolled. All patients underwent routine magnetic resonance sequence examination and DWI examination. The b-value were 1000 s/mm2 and 3000 s/mm2. The apparent diffusion coefficient (ADC) value and SNR of lesions before and after treatment were compared. The data of each group were statistically analyzed by Wilcoxon signed-rank sum test.RESULTS: After 1 year of treatment with albendazole liposomes, the SNR of lesions on T2WI sequence increased. There was a significant difference between the SNR of the same lesion before and after follow-up (P < 0.05). The ADC values of lesion parenchyma and edema area before and after treatment were compared. The difference between them was statistically significant in the both b values (ADC of parenchyma, P < 0.05; ADC of edema area, P < 0.001). Through binary linear classification, it was found that under the same b value, the effect of drugs on the edema area was more obvious than that on the parenchyma area; under different b values, the higher the b value, the higher the ability to evaluate the curative effect of drug therapy.CONCLUSION: Albendazole liposome is effective in the treatment of CAE, and long-term imaging follow-up of patients with CAE treated with albendazole liposome is necessary. When the change in conventional images is inapparent, the quantitative analysis of ADC value and SNR of lesions on T2WI can provide an objective basis for the evaluation of the curative effect of drug treatment in CAE.

3D quantitative analysis of diffusion-weighted imaging for predicting the malignant potential of intraductal papillary mucinous neoplasms of the pancreas.

PurposeTo investigate the predictors of intraductal papillary mucinous neoplasms of the pancreas (IPMNs) with high-grade dysplasia, using 2-dimensional (2D) analysis and 3-dimensional (3D) volume-of-interest-based apparent diffusion coefficient (ADC) histogram analysis.Material and methodsThe data of 45 patients with histopathologically confirmed IPMNs with high-grade or low-grade dysplasia were retrospectively assessed. The 2D analysis included lesion-to-spinal cord signal intensity ratio (LSR), minimum ADC value (ADCmin), and mean ADC value (ADCmean). The 3D analysis included the overall mean (ADCoverall mean), mean of the bottom 10th percentile (ADCmean0-10), mean of the bottom 10-25th percentile (ADCmean10-25), mean of the bottom 25-50th percentile (ADCmean25-50), skewness (ADCskewness), kurtosis (ADCkurtosis), and entropy (ADCentropy). Diagnostic performance was compared by analysing the area under the receiver operating characteristic curve (AUC). Inter-rater reliability was assessed by blinded evaluation using the intraclass correlation coefficient.ResultsThere were 16 and 29 IPMNs with high- and low-grade dysplasia, respectively. The LSR, ADCoverall mean, ADCmean0-10, ADCmean10-25, ADCmean25-50, and ADCentropy showed significant between-group differences (AUC = 72-93%; p < 0.05). Inter-rater reliability assessment showed almost perfect agreement for LSR and substantial agreement for ADCoverall mean and ADCentropy. Multivariate logistic regression showed that ADCoverall mean and ADCentropy were significant independent predictors of malignancy (p < 0.05), with diagnostic accuracies of 80% and 73%, respectively.ConclusionADCoverall mean and ADCentropy from 3D analysis may assist in predicting IPMNs with high-grade dysplasia.

Characterization of pediatric head and neck masses with quantitative analysis of diffusion-weighted imaging and measurement of apparent diffusion coefficients

Purpose:Our objective was to investigate the accuracy of quantitative diffusion-weighted imaging (DWI) to determine the histopathologic diagnosis of pediatric head and neck lesions.Materials and Methods:This retrospective study included 100 pediatric patients recently diagnosed with head and neck tumors. All patients underwent preoperative conventional magnetic resonance imaging (MRI) and DWI. Each lesion was evaluated according to signal characteristics, enhancement pattern, and diffusivity. The average apparent diffusion coefficient (ADC) obtained from each tumor was compared to the histological diagnosis of benign, locally malignant, or malignant categories.Results:Our retrospective study showed a significant negative correlation between average ADC and tumor histopathologic diagnosis (P < 0.001, r = -0.54). The mean ADC values of benign, locally malignant lesions, and malignant tumors were 1.65 ± 0.58 × 10–3, 1.43 ± 0.17 × 10–3, and 0.83 ± 0.23 × 10–3 mm2 s-1, respectively. The ADC values of benign and locally malignant lesions were overlapped. We found a cut-off value of ≥1.19 × 10–3 mm2s-1 to differentiate benign from malignant pediatric head and neck masses with a sensitivity of 97.3%, specificity of 80.0%, positive predictive value of 94.7%, and negative predictive value of 88.9%.Conclusion:Diffusion-weighted MRI study is an accurate, fast, noninvasive, and nonenhanced technique that can be used to characterize head and neck lesions. DWI helps to differentiate malignant from benign lesions based on calculated ADC values. Additionally, DWI is helpful to guide biopsy target sites and decrease the rate of unnecessary invasive procedures.

MRI findings, including diffusion-weighted imaging, in seven cats with nasal lymphoma and two cats with nasal adenocarcinoma.

Primary nasal tumours in cats are rare, with lymphoma being the most common feline nasal tumour, followed by adenocarcinoma. Although CT can reliably detect feline nasal tumours, there are no specific CT features that identify each tumour type. To our knowledge, there have been no reports describing MRI findings, including diffusion-weighted imaging (DWI), for nasal lymphomas and adenocarcinomas in cats. Therefore, this retrospective study aimed to evaluate the MRI findings of nasal lymphoma and adenocarcinoma, including qualitative and quantitative analysis of DWI. MRI examination was performed on seven cats with histologically confirmed lymphoma and on two with adenocarcinoma. The MRI protocol included T2-weighted imaging (T2WI), T1-weighted imaging (T1WI) and DWI. Apparent diffusion coefficient (ADC) values were measured using DWI. Contrast agent was not used in one cat with lymphoma. Of the cats with lymphoma, three (43%) were iso- and hyperintense on T2WI, seven (100%) were isointense on T1WI, five (83%) exhibited mild heterogeneous enhancement, including a prominent region of non-enhancement on post-contrast T1WI, and seven (100%) cats exhibited hyperintensity on DWI. The median ADC values were 0.45 × 10-3 mm2/s (range 0.37-0.53 × 10-3 mm2/s). For adenocarcinoma, two (100%) were iso- and hyperintense on T2WI, two (100%) were isointense on T1WI, two (100%) exhibited marked heterogeneous enhancement on post-contrast T1WI and two (100%) were isointense on DWI. The median ADC values were 1.08 × 10-3 mm2/s (range 0.88-1.27 × 10-3 mm2/s). The median ADC values of lymphoma tended to be lower than adenocarcinoma (P = 0.056). Determining ADC value and tumours with a large area of non-enhancement may be helpful in differentiating nasal lymphoma from nasal adenocarcinoma.

Quantitative analysis of diffusion-weighted imaging in high-risk patients and newly diagnosed breast cancer patients; a systematic review

Quantitative analysis of diffusion-weighted imaging in high-risk patients and newly diagnosed breast cancer patients; a systematic review

Qualitative and quantitative analysis of diffusion-weighted imaging of gestational trophoblastic disease: Can it predict progression of molar pregnancy to persistent form of disease?

PurposeTo describe the diffusion-weighted imaging (DWI) appearance of gestational trophoblastic disease (GTD) and to determine its apparent diffusion coefficient (ADC) values. To evaluate the feasibility of DWI to predict progression of hydatidiform mole (HM) to persistent disease. MethodsDuring a period of 6 months, women with preliminary diagnosis of GTD, based on ultrasound and ßhCG levels, underwent 1.5T MRI (T2 high-resolution and DWI; b values 50, 400, 800; sagittal and perpendicular to the endometrium; and T1, T2 Turbo Spin Echo [TSE] axial images). Patients were followed for 6–12 months to monitor progression to persistent form of the disease. ADC values and image characteristics were compared between HM and persistent neoplasia and between GTD and non-molar pregnancy using Mann–Whitney U and Fisher’s exact tests, respectively. ResultsAmong the 23 studied patients, 19 (83%) were classified as molar and 4 (17%) as non-molar, based on pathology reports. After 6–12 months of follow-up, 5 (26%) cases progressed to persistent disease and 14 (74%) cases were benign HM. There was no significant difference between ADC values for HM (1.93±0.33×10−3mm2/s) and persistent neoplasia (2.03±0.28×10−3mm2/s) (P=0.69). The ADC of non-molar pregnancies was (0.96±0.46×10−3mm2/s), which was significantly different from GTD (1.96 ±0.32×10−3mm2/s) (P=0.001). Heterogeneous snowstorm appearance, focal intratumoral hemorrhage, myometrial contraction, and prominent myometrial vascularity were more common in GTD compared to non-molar pregnancy (P<0.05). ConclusionHeterogeneous snowstorm appearance, focal intratumoral hemorrhage, myometrial contraction, and prominent myometrial vascularity are among the imaging characteristics of GTD. We cannot use ADC values to predict progression to persistent disease.

Differentiating recurrent tumours from post-treatment changes in head and neck cancers: does diffusion-weighted MRI solve the eternal dilemma?

To evaluate the utility of diffusion-weighted imaging (DWI) in differentiating post-treatment changes from tumour recurrence in head and neck cancers and to establish a threshold apparent diffusion coefficient (ADC) value to differentiate the two conditions. This was a prospective study of 80 treated head and neck cancer patients. The patient cohort consisted of a wide spectrum of head and neck sites, including the oral cavity, oropharynx, larynx, hypopharynx, paranasal sinuses, orbits, salivary glands, and infra-temporal fossa. Qualitative analysis of the diffusion images and quantitative analysis of the corresponding ADC maps was performed and the data were correlated with histopathological findings and clinical examinations. The mean ADC value of recurrent tumours in the present cohort was 0.932±0.19×10-3 mm2/s and the mean ADC value of lesions representing post-treatment changes was 1.394±0.32×10-3 mm2/s. A threshold ADC value of 1.2×10-3mm2/s used to differentiate post-treatment changes from recurrent head and neck cancers showed the highest combined sensitivity of 90.13%, specificity of 82.5%, accuracy of 86.4%, positive predictive value of 84.4%, negative predictive value of 88.9%, and mean kappa measurement of agreement of 72.8. Combined qualitative and quantitative analysis of DWI is a useful non-invasive technique to differentiate recurrent head and neck malignancies from post-treatment changes using a threshold ADC value.

Value of diffusion-weighted MRI and apparent diffusion coefficient measurements for predicting the response of locally advanced rectal cancer to neoadjuvant chemoradiotherapy.

The aim of our study was to assess the performance value of magnetic resonance imaging (MRI) in the restaging of locally advanced rectal cancer after neoadjuvant chemoradiotherapy (CRT) and in the identification of good vs. poor responders to neoadjuvant therapy. A total of 34 patients with locally advanced rectal cancer underwent MRI prior to and after CRT. T stage and tumor regression grade (TRG) on post-CRT MRI was compared with the pathological staging ypT and TRG. Tumor volume and the apparent diffusion coefficient (ADC) were measured using diffusion-weighted imaging (DWI) before and after neoadjuvant CRT; the percentage of tumor volume reduction and the change of ADC (ΔADC) was also calculated. ADC parameters and the percentage of tumor volume reduction were correlated to histopathological results. The diagnostic performance of ADC and volume reduction to assess tumor response was evaluated by calculating the area under the ROC curve and the optimal cut-off values. A significant correlation between the T stage and the TRG defined in DW-MRI after CRT and the ypT and the TRG observed on the surgical specimens was found (p=0.001; p<0.001). The mean post-CRT ADC and ΔADC in responder patients was significantly higher compared to non-responder ones (p=0.001; p=0.01). Furthermore, the mean post-CRT ADC values were significantly higher in tumors with T-downstage (p=0.01). DW-MRI may have a significant role in the restaging and in the evaluation of post-CRT response of locally advanced rectal cancer. Quantitative analysis of DWI through ADC map may result in a promising noninvasive tool to evaluate the response to therapy.

Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) Is Able to Distinguish Diffuse from Normal MRI Pattern of Marrow Involvement in Patients with Multiple Myeloma

▪Diffuse MRI pattern of marrow involvement correlates with poor prognosis in patients with multiple myeloma (MM) both in the conventional chemotherapy and novel agent era. Sometimes the differentiation of diffuse from normal MRI marrow involvement in MM patients is difficult, particularly in cases of anemia and of low plasma cell marrow infiltration. Diffusion-Weighted Imaging (DWI) is an MRI technique which is based on differences in the diffusivity of water molecules in the respective tissue. Quantitative analysis of DWI can be achieved by calculating the Apparent Diffusion Coefficient (ADC) values from images with two or more different diffusion weightings. There are very limited data in the literature regarding ADC values in MM patients and almost no data for the ADC values in patients with different MRI patterns of marrow involvement. Thus our objective was to calculate and compare ADC values in newly diagnosed patients with MM, to identify possible differences among diffuse, focal, and normal MM MRI patterns and to establish, if possible, a threshold value which might distinguish diffuse from normal MRI patterns.We evaluated 44 patients (18M/26F, median age 66 years; range: 37-89 years) with newly diagnosed, untreated, MM patients and 16 healthy, gender and age-matched controls, with MRI of the lumbosacral spine, using a 1.5 Tesla unit. Conventional MR images were obtained according to bone marrow MRI protocols; MRI patterns of involvement were normal in 22, focal in 11 and diffuse in 11 patients. DWI was obtained with an Echo Planar Imaging sequence using 5 b-values (0, 150, 250, 500, 750 sec/mm2). In MM patients with a normal or a diffuse pattern, as well as in healthy controls, region of interest (ROI) measurements were obtained from each of the five lumbar vertebral bodies avoiding the region of the basivertebral vessels and any focal non-myelomatous lesion and the mean ADC value was calculated. In MM patients with a focal pattern, ROIs were placed on several focal lesions and the highest ADC value was recorded; in these patients an additional ROI was placed on an uninvolved vertebra in order to record the ADC value of apparently normal marrow.Mean ADC values (±SD, x10-3 mm2/sec) were: 0.346±0.107 (range: 0.186-0.544) for the normal MM pattern, 1.188±0.359 (range: 0.715-2.015) for the focal MM pattern and 0.821±0.149 (range: 0.642-1.017) for the diffuse MM pattern [Figure]. Mean ADC value of apparently normal marrow in patients with a focal pattern was 0.403±0.142 (range: 0.113-0.589), while that of healthy controls was 0.325±0.135 (range: 0.152-0.542). One way analysis of variance (ANOVA) showed a significant difference in ADC values within the groups of the study (p<0.0001). Further analysis using t-test revealed significant differences of ADC values between diffuse and focal MM pattern (p=0.003), diffuse and normal MM pattern (p<0.0001), focal and normal MM pattern (p<0.0001), diffuse MM pattern and healthy volunteers (p<0.0001), focal MM pattern and healthy volunteers (p<0.0001), diffuse MM pattern and apparently normal marrow in focal MM pattern (p<0.0001) and finally between focal MM pattern and apparently normal marrow in focal MM pattern (p<0.0001) [Figure]. No significant differences were found between normal MM pattern and healthy volunteers (p=0.442), normal MM pattern and apparently normal marrow in focal MM pattern (p= 0.141), and between apparently normal marrow in focal MM pattern and healthy volunteers (p= 0.175). The 95% confidence intervals of the ADC values for each group were calculated and a receiver operating characteristic (ROC) analysis was performed to determine the cut-off value with the highest accuracy to distinguish a diffuse myeloma pattern from normal patterns (normal MM pattern, apparently normal marrow in focal MM pattern, normal marrow in healthy controls). An ADC value above 0.593x10-3 mm2/sec was found to be diagnostic of diffuse myelomatous infiltration of the bone marrow with a sensitivity and specificity of 100%.We conclude that normal, focal and diffuse MRI patterns of marrow involvement in patients with MM have distinct ranges of ADC values on DWI. An ADC value above 0.593×10-3 mm2/sec is diagnostic of diffuse myelomatous infiltration of the bone marrow with extremely high accuracy and can be used in cases where diffuse pattern cannot be differentiated from normal pattern in conventional MRI. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.