Initial experience of 3 tesla apparent diffusion coefficient values in differentiating benign and malignant thyroid nodules

Purpose:

To evaluate the role of diffusion‐weighted magnetic resonance imaging (DWMRI) in differentiating benign and malignant thyroid nodules using a 3 Tesla (T) MRI scanner.

Materials and Methods:

Twenty‐eight nodules in 25 patients and 14 healthy control cases were included in the study. DWMRI was acquired with 6 b values with a 3T MRI scanner. The apparent diffusion coefficient (ADC) values of the nodules were calculated from reconstructed ADC map images and were compared with the final histopathological diagnoses.

Results:

The mean ADC value of the benign nodules was 1548 ± 353.4 (×10^?6 mm²/s), and the mean ADC of the malignant nodules was 814 ± 177.12 (×10^?6 mm²/s). The normal thyroid tissue had a mean ADC value of 1323.43 ± 210.35 × 10^?6 mm²/s (958–1689 × 10^?6 mm²/s) in the healthy control group. The ADC values were significantly different among the three groups (P = 0.001). An ADC value of 905 × 10^?6 mm²/s was determined to be the cutoff value for differentiating benign and malignant nodules, with 90% (55.5–98.3) sensitivity and 100% (81.3–100.0) specificity.

Conclusion:

This study suggests that the ADC values of nodules measured with a 3T MRI scanner could help in differentiating benign thyroid nodules from malignant nodules. J. Magn. Reson. Imaging 2013;37:1077–1082. © 2012 Wiley Periodicals, Inc.

     

Diffusion‐weighted images differentiate benign from malignant thyroid nodules

Purpose:

To reveal the possible role of diffusion‐weighted images (DWI) in the differential diagnosis of benign and malignant thyroid nodules by comparing the results of fine‐needle aspiration cytology (FNAC).

Materials and Methods:

In an 18‐month period (December 2005 to May 2007), 27 cases with benign thyroid nodules with a total of 52 benign nodules, nine cases with thyroid gland malignancy, and 24 healthy control cases were included in the study. Cases that were indicated to undergo to FNAC examination and sent by a clinician for biopsy to the radiology unit were included in the study to assess the cytopathologic confirmation of the clinic, ultrasonographic, and magnetic resonance imaging (MRI) findings.

Results:

The mean apparent diffusion coefficient (ADC) values of thyroid nodules were 2745.3 ± 601.1 × 10^?6 mm²/s (1605–3899 × 10^?6mm²/s) in the benign group and 695.2 ± 312.5 × 10^?6mm²/s (165–1330 × 10^?6mm²/s) in the malignant group. Normal thyroid tissues had mean ADC values of 1344.1 ± 276.4 × 10^?6 mm²/s (1015–1764 × 10^?6mm²/s). The ADC values of three subgroups were significantly different (P = 0.0001). A reduced ADC was observed in most types of malignant tumors due to the consequent decrease of the extracellular extravascular space.

Conclusion:

Our preliminary results showed that ADC values of nodules may provide useful data about the nature of a thyroid nodule. J. Magn. Reson. Imaging 2010;31:94–100. © 2009 Wiley‐Liss, Inc.

     

Role of diffusion-weighted imaging with ADC mapping and in vivo H-MR spectroscopy in thyroid nodules

Purpose

To evaluate the role of the combined techniques of apparent diffusion coefficient (ADC) generated from diffusion-weighted magnetic resonance (MR) imaging (DWI) and metabolite spectrum acquired by magnetic resonance spectroscopy (MRS) in differentiating benign from malignant thyroid nodules.

Materials and methods

Thirty-seven patients with 56 thyroid nodules were evaluated with conventional MRI (T1- & T2-WI), DWI (b value 0.500 s/mm²; ADC values were calculated for the thyroid nodules), and MRS (for the presence or absence of choline peak). The ADC values and MRS findings were correlated with the histopathological results.

Results

The mean ADC of the malignant thyroid nodules (0.89 ± 0.27 × 10⁻³ mm²/s) was significantly lower than that of the mean ADC of the benign thyroid nodules (1.85 ± 0.24 × 10⁻³ mm²/s) (p value <0.0001). ADC value of 1.5 × 10⁻³ mm²/s was used as a cut-off value for differentiation benign from malignant thyroid nodules. The sensitivity, specificity, PPV&NPV of DWI in differentiating benign from malignant thyroid nodules were 94%, 95%, 94% & 95%, respectively (Kappa test 0.84, p value <0.0001), whereas they were 94.7%, 89.2%, 81.8% & 97.1% (Kappa test 0.8, p value <0.0001) with MRS, and 96%, 100%, 100% & 97% (Kappa test 0.96, p value <0.0001) with both DWI and MRS.

Conclusion

Both DWI and MRS are useful diagnostic modalities for characterization and differentiation between benign and malignant thyroid nodules. Our preliminary results showed that combination of DWI with calculated ADC values and metabolite spectrum acquired by MRS add more information to MRI and should be considered as an additional and complementary tool to conventional MRI for differentiating benign from malignant thyroid nodules.     

Role of diffusion-weighted MR imaging in assessing malignant versus benign skull-base lesions

Purpose

This study was done to assess the role of diffusion-weighted magnetic resonance (MR) imaging in assessing malignant versus benign skull lesions.

Materials and methods

A retrospective analysis was undertaken of 45 patients (26 male, 19 female; age range 14?C68 years, mean age 39 years) with skull-base lesions. Diffusion-weighted MR images were acquired with a bfactor of 500 and 1,000 s/mm² using single-shot echoplanar imaging. Apparent diffusion coefficient (ADC) maps were reconstructed, and the ADC value of the lesion was calculated.

Results

The mean ADC value of malignant tumours was (1.002±0.21)×10^?3 mm²/s and that of benign tumours was (1.63±0.29)×10^?3 mm²/s. There was a statistically significant difference (p=0.001) in the ADC value of malignant skull-base tumours versus benign lesions. Selection of (1.3)×10^?3mm²/s as a threshold value of ADC for differentiating benign from malignant tumours yielded the best result, with an accuracy of 94%, sensitivity of 94%, specificity of 93%, positive predictive value of 93%, negative predictive value of 94% and area under the curve of 0.932.

Conclusions

We conclude that diffusion-weighted MR imaging is a promising, noninvasive approach that can be used to characterise skull-base lesions in that it can help differentiate malignant tumours from benign lesions and evaluate the pathological grading of malignant tumours.     

Assessment of soft tissue tumours of the extremities with diffusion echoplanar MR imaging

Purpose

This study assessed soft tissue tumours of the extremities with diffusion echo-planar magnetic resonance (MR) imaging.

Materials and methods

We carried out a retrospective study of 37 patients (22 male, 15 female; age range 4?C68 years; mean age 41 years) with a soft tissue mass. Diffusion-weighted magnetic resonance (MR) imaging was done using echo-planar imaging (EPI) with b factor of 0.500 and 1,000 mm2/s. The apparent diffusion coefficient (ADC) map was reconstructed with calculation of the ADC values of the mass.

Results

The mean ADC value of the malignant tumours was 1.02±0.03×10^?3mm²/s and that of benign masses 1.54±0.03×10^?3mm²/s. There was a significant difference in the ADC values between malignant soft tissue tumours and benign masses (p<0.001) and within different grades of malignancy (p<0.02). Selection of 1.34×10^?3 mm²/s as a threshold ADC value for differentiating malignant soft tissue tumours from benign masses resulted in an accuracy of 91%, sensitivity of 94%, specificity of 88% and area under the curve of 0.869. There was a significant difference in the ADC value between well- and poorly differentiated malignancies (p=0.001).

Conclusions

Diffusion-weighted echo-planar MR imaging is a promising noninvasive modality that may be helpful in differentiating malignant soft tissue tumours from benign masses as well as in grading malignancy.     

Role of diffusion-weighted imaging in prediction of nipple-areolar complex invasion by breast cancer

The aim of this workThe aim of this work was to estimate the role of diffusion-weighted imaging (DWI) in predicting malignant invasion of the nipple-areolar complex (NAC) by underlying breast cancer.Material and methodsThis prospective study included 70 female patients with breast cancer with a mean age of 45.8 years (range: 28–68). DWI of the breast was done for all patients. Apparent diffusion coefficient (ADC) maps were automatically constructed. The mean ADC values of NAC were independently measured by two observers who are experts in breast imaging and correlated with the results of histopathological examinations.ResultsBoth observers found a significantly lower ADC value of malignant NAC invasion (n = 18) when compared with free NAC (n = 52), with mean ADC value for malignant NAC invasion was 0.86 ± 0.35 × 10⁻³ mm²/s and 0.84 ± 0.08 × 10⁻³ mm²/s for observer one and two respectively versus mean ADC value of 1.34 ± 0.25 × 10⁻³ mm²/s and 1.4 ± 0.26 × 10⁻³ mm²/s for free NAC by observer one and two respectively (P-value =0.001). Observer one found that a cutoff ADC value of 1.05 × 0⁻³ mm²/s can predict malignant NAC invasion with 0.975 AUC, 92.8% accuracy, 94.4% sensitivity, and 92.3% specificity. Observer two found that a cutoff ADC value of 0.95 × 10⁻³ mm²/s can predict malignant NAC invasion with 0.992 AUC, 95.7% accuracy, 88.9% sensitivity, and 98.1% specificity.ConclusionDWI can predict malignant NAC invasion in patients with breast cancer.     

Diffusion-weighted imaging of focal renal lesions: a meta-analysis

Objectives

Contrast-enhanced MRI can only distinguish to a limited extent between malignant and benign focal renal lesions. The aim of this meta-analysis is to review renal diffusion-weighted imaging (DWI) to compare apparent diffusion coefficient (ADC) values for different renal lesions that can be applied in clinical practice.

Methods

A PubMed search was performed to identify relevant articles published 2004–2011 on renal DWI of focal renal lesions. ADC values were extracted by lesion type to determine whether benign or malignant. The data table was finalised in a consensus read. ADC values were evaluated statistically using meta-regression based on a linear mixed model. Two-sided P value <5 % indicated statistical significance.

Results

The meta-analysis is based on 17 studies with 764 patients. Renal cell carcinomas have significant lower ADC values than benign tissue (1.61?±?0.08?×?10^-3 mm²/s vs 2.10?±?0.09?×?10^-3 mm²/s; P?<?0.0001). Uroepithelial malignancies can be differentiated by lowest ADC values (1.30?±?0.11?×?10^-3 mm²/s). There is a significant difference between ADC values of renal cell carcinomas and oncocytomas (1.61?±?0.08?×?10^-3 mm²/s vs 2.00?±?0.08?×?10^-3 mm²/s; P?<?0.0001).

Conclusions

Evaluation of ADC values can help to determine between benign and malignant lesions in general but also seems able to differentiate oncocytomas from malignant tumours, hence potentially reducing the number of unnecessarily performed nephrectomies.

Key Points

? This meta-analysis assesses the role of diffusion-weighted MRI in renal lesions. ? ADC values obtained by DW MRI have been compared for different renal lesions. ? ADC values can help distinguish between benign and malignant tumours. ? Differentiating oncocytomas from malignant tumours can potentially reduce inappropriate nephrectomies.     

Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging for Differentiation Between Parotid Neoplasms

PurposeThis study was designed to evaluate the role of multiparametric magnetic resonance imaging (MRI) for differentiation of parotid gland neoplasms.MethodsProspective study was conducted upon 52 consecutive patients (30 men, 22 women; aged 24–78 years; mean, 51 years) with parotid tumours that underwent multiparametric MRI using combined static MRI, dynamic contrast enhanced (DCE) MRI, and diffusion-weighted imaging (DWI). The static MRI parameter, time signal intensity curves (TIC) derived from DCE-MRI, and apparent diffusion coefficient (ADC) values of parotid tumours were correlated with histopathological findings.ResultsStatic MRI revealed a significant difference between both benign and malignant lesions in regards to margin definition (P < .001) and T2 hypointensity (P < .013), with a diagnostic accuracy 95% and 78.33% respectively. Study of the TIC type on DCE-MRI revealed statistically significant difference between benign and malignant lesions (P < .001) and diagnostic accuracy 96.55%. There was no statistically significant difference (P = .181) between the ADC values of benign and malignant lesions. ROC curve analysis revealed that by using ADC cut-off value of 1 × 10^?3 mm²/s had accuracy of 84.62% respectively for differentiating Warthin from malignant tumours that could be modified to higher value (94.28%) by excluding lymphoma from malignant lesions. By using cutoff value of 1.3 × 10^?3 mm²/s to differentiate pleomorphic adenoma from malignancy, ROC curve analysis had high accuracy of 97.06%.ConclusionMultiparametric MRI can be used for differentiation of malignant from benign parotid tumours and characterization of some benign parotid tumours.     

Respiratory gated diffusion-weighted imaging of the liver: value of apparent diffusion coefficient measurements in the differentiation between most commonly encountered benign and malignant focal liver lesions

The purpose of this study was to measure apparent diffusion coefficient values of normal liver parenchyma and focal liver lesions utilizing a respiratory gated diffusion sequence with multiple b-values and to investigate whether apparent diffusion coefficient (ADC) measurements may be utilized to characterize and differentiate between malignant and benign focal hepatic lesions. Thirty-eight consecutive patients underwent MRI of the liver including diffusion-weighted imaging (DWI). A single-shot echo planar imaging sequence was applied in coronal orientation with multiple b-values (0, 50, 500, 1,000 s/mm²) and respiratory gating. ADC values were recorded on corresponding maps utilizing region of interest measurements in patients with benign (group A), malignant (group B) focal lesions and liver parenchyma (group C). Statistical analysis was applied to check whether differences in mean ADC values were significant (p<0.05). No focal lesions were detected in 11 patients, with a mean ADC value (CI 95%) of liver parenchyma 1.25×10⁻³ mm²/s (1.21×10⁻³ mm²/s−1.29×10⁻³ mm²/s). Differences in mean ADC of liver parenchyma between group A and B were not significant (p=0.054, 1.30×10⁻³ mm²/s and 1.31×10⁻³ mm²/s, respectively). Mean ADC value (95% CI) of 22 benign lesions found in 18 patients was 2.55×10⁻³ mm²/s (2.35×10⁻³ mm²/s−2.74×10⁻³ mm²/s), while the mean ADC value (95% CI) of 16 malignant lesions recorded in 9 patients was 1.04×10⁻³ mm²/s (0.9×10⁻³ mm²/s−1.17×10⁻³ mm²/s). The difference between mean ADC values of benign and malignant focal lesions was statistically significant (p<0.0001). Respiratory gated diffusion-weighted imaging in the liver is technically feasible. Apparent diffusion coefficient measurements can be useful in differentiating malignant from benign focal liver lesions.     

Role of quantitative diffusion-weighted MRI and H MR spectroscopy in distinguishing between benign and malignant thyroid nodules

Background and purpose

The imaging characterization of thyroid nodules is mandatory to exclude malignancy. The purpose of this study is to evaluate the role of quantitative diffusion MRI and ¹H MR spectroscopy in differentiation between benign and malignant Thyroid nodules.

Methods

From February 2012 to May 2013, prospective study was conducted on 25 patients with 41 thyroid nodules (11 males, 14 females, age range, 16–74 years with mean 45.3 years) collected from wards and clinics of Internal Medicine and General Surgery Departments, 20 healthy individuals as control cases were included in the study. 1.5-T ¹H-MR spectroscopy (at echo-times (TE) 144 and 35 ms) and diffusion-weighted imaging (b value 0, 250 and 1000 s/mm²) were performed and the results were correlated with histopathological results.

Results

The mean ADC of the malignant thyroid nodules (13 nodules) was 0.59 ± 0.24 × 10⁻³ mm²/s while that of the benign thyroid nodules (28 nodules) was 1.78 ± 0.21 × 10⁻³ mm²/s (p value <0.0001).Choline is present in all malignant nodules (13 nodules) and two benign nodules (mild elevation) while absent in 26 other benign nodules. Choline/creatine ratio in malignant nodules ranged from 1.3 to 5.4, while in two benign nodules it was 0.9 and 1.1.The sensitivity, specificity, PPV, NPV and overall accuracy of diffusion and MRS in differentiating benign from malignant thyroid nodules were 100%, 93%, 96%, 100% and 79%, respectively.

Conclusion

MRS and diffusion WI are useful noninvasive diagnostic modalities in differentiation between benign and malignant thyroid nodules.     

Role of diffusion-weighted MR imaging in cervical lymphadenopathy

The role of diffusion-weighted magnetic resonance imaging (MRI) for differentiation between various causes of cervical lymphadenopathy was evaluated. In a prospective study, 31 untreated patients (22 males and nine females, aged 5–70 years) with 87 cervical lymph nodes underwent diffusion-weighted MRI before performance of neck dissection (n=14), surgical biopsy (n=9) or core biopsy (n=8). Diffusion-weighted MR images were acquired with a b factor of 0 and 1,000 s/mm² using single-shot echo-planar sequence. Apparent diffusion coefficient (ADC) maps were reconstructed for all patients. The signal intensity of the lymph nodes was assessed on images obtained at b=0 or 1,000 s/mm² and from the ADC maps. The ADC value of lymph nodes was also calculated. On the ADC map, malignant nodes showed either low (n=52) or mixed (n=20) signal intensity and benign nodes revealed high (n=13) or low (n=2) signal intensity. The mean ADC value of metastatic (1.09±0.11×10⁻³ mm²/s) and lymphomatous (0.97±0.27×10⁻³ mm²/s) lymph nodes was significantly lower than that of benign (1.64±0.16×10⁻³ mm²/s) cervical lymph nodes (P<0.04). When an ADC value of 1.38×10⁻³ mm²/s was used as a threshold value for differentiating malignant from benign lymph nodes, the best results were obtained with an accuracy of 96%, sensitivity of 98%, specificity of 88%, positive predictive value of 98.5% and negative predictive value of 83.7%. The smallest detected lymph node was 0.9 cm. In conclusion, diffusion-weighted MRI with ADC mapping is a new promising technique that can differentiate malignant from benign lymph nodes and delineate the solid viable part of the lymph node for biopsy. This technique provides additional useful physiological and functional information regarding characterization of cervical lymph nodes.     

The added value of qualitative and quantitative diffusion-weighted magnetic resonance imaging (DW-MRI) in differentiating benign from malignant breast lesions

Objective

To evaluate the role of diffusion-weighted magnetic resonance imaging (DW-MRI) with calculation of the apparent diffusion coefficient (ADC) value in characterizing benign and malignant breast lesions.

Application of the diffusion kurtosis model for the study of breast lesions

Objectives

To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions.

Methods

Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000 s/mm²). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined.

Results

Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p?=?0.017; MD, p?=?0.028; MK, p?=?0.017). ADC and MD were higher for benign (1.96?±?0.41?×?10^?3 and 2.17?±?0.42?×?10^?3 mm²/s, respectively) than for malignant lesions (1.33?±?0.18?×?10^?3 and 1.52?±?0.50?×?10^?3 mm²/s). MK was higher for malignant (0.61?±?0.27) than benign lesions (0.37?±?0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): p?=?0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p?=?0.016).

Conclusions

Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed.

Key Points

? The diffusion kurtosis model provides new information regarding breast lesions ? MD and MK are valid parameters to characterise tissue microstructure ? MK enables improved lesion differentiation ? MK is able to differentiate lesions that display similar ADC values     

Diagnostic accuracy of the apparent diffusion coefficient in differentiating benign from malignant uterine endometrial cavity lesions: initial results

Our purpose is to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC) measurement in differentiating malignant from benign uterine endometrial cavity lesions. We retrospectively evaluated 25 uterine endometrial cavity lesions in 25 female patients: endometrial carcinoma (n = 11), carcinosarcoma (n = 2), submucosal leiomyoma (n = 8), and endometrial polyp (n = 4). Diffusion-weighted images were performed at 1.5 T with b factors of 0–1,000/mm². The region of interest was defined within the tumor on T2-weighted EPI image and then manually copied to an ADC map. Thereby, the ADC value was obtained. We compared ADC values between malignant and benign lesions using Student’s t-test. The mean and standard deviation of ADC values (×10⁻³ mm²/s) were as follows: endometrial carcinoma, 0.98±0.21; carcinosarcoma, 0.97±0.02; submucosal leiomyoma, 1.37±0.28; and endometrial polyp, 1.58±0.45. The ADC values differed significantly between malignant (0.98±0.19) and benign lesions (1.44±0.34) (P < 0.01). We defined malignant tumors as cases with an ADC value less than 1.15 × 10⁻³ mm²/s for obtaining the highest accuracy. Sensitivity, specificity, and accuracy were 84.6%, 100%, and 92%, respectively. ADC measurement can provide useful information in differentiating malignant from benign uterine endometrial cavity lesions.     

Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion

The role of diffusion-weighted magnetic resonance imaging (DWI) to differentiate breast lesions in vivo was evaluated. Sixty women (mean age, 53 years) with 81 breast lesions were enrolled. A coronal echo planar imaging (EPI) sequence sensitised to diffusion (b value=1,000 s/mm²) was added to standard MR. The mean diffusivity (MD) was calculated. Differences in MD among cysts, benign lesions and malignant lesions were evaluated, and the sensitivity and specificity of DWI to diagnose malignant and benign lesions were calculated. The diagnosis was 18 cysts, 21 benign and 42 malignant nodules. MD values (mean±SD ×10⁻³ mm²/s) were (1.48±0.37) for benign lesions, (0.95±0.18) for malignant lesions and (2.25±0.26) for cysts. Different MD values characterized different malignant breast lesion types. A MD threshold value of 1.1×10⁻³ mm²/s discriminated malignant breast lesions from benign lesions with a specificity of 81% and sensitivity of 80%. Choosing a cut-off of 1.31×10⁻³ mm²/s (MD of malignant lesions -2 SD), the specificity would be 67% with a sensitivity of 100%. Thus, MD values, related to tumor cellularity, provide reliable information to differentiate malignant breast lesions from benign ones. Quantitative DWI is not time-consuming and can be easily inserted into standard clinical breast MR imaging protocols.     

Assessment of mediastinal tumors with diffusion‐weighted single‐shot echo‐planar MRI

Purpose

To assess the role of diffusion‐weighted single‐shot echo‐planar magnetic resonance imaging (MRI) in patients with mediastinal tumors.

Methods

Prospective study was conducted on 45 consecutive patients (29 male, 16 female, age 22–66 years, mean 41 years) with mediastinal tumor. They underwent diffusion‐weighted single‐shot echo‐planar MRI of the mediastinum with a b‐factor of 0, 300, and 600 sec/mm². The apparent diffusion coefficient (ADC) value of the mediastinal tumor was correlated with the histopathological findings.

Results

The mean ADC value of malignant mediastinal tumors was 1.09 ± 0.25 × 10^?3 mm²/sec, and of benign tumors was 2.38 ± 0.56 × 10^?3 mm²/sec. There was a significant difference in the mean ADC value between malignant and benign tumors (P = 0.001) and within different grades of malignancy (0.001). When an ADC value of 1.56 × 10^?3 mm²/sec was used as a threshold value for differentiating malignant from benign tumor, the best results were obtained with an accuracy of 95%, sensitivity of 96%, specificity of 94%, positive predictive value of 94%, negative predictive value of 96%, and area under the curve of 0.938.

Conclusion

The ADC value is a noninvasive parameter that can be used for differentiation of malignant from benign mediastinal tumors and grading of mediastinal malignancy. J. Magn. Reson. Imaging 2009. © 2009 Wiley‐Liss, Inc.

     

The efficiency of apparent diffusion coefficient quantification in diagnosis of acute cholecystitis and in differentiation of cholecystitis from extrinsic benign gallbladder wall thickening

Purpose

The aim of the current study was to assess the efficiency of the apparent diffusion coefficient (ADC) measurement in diagnosis of acute cholecystitis and in differentiation of cholecystitis from extrinsic benign gallbladder wall thickening.

Methods

Forty patients who were diagnosed to have acute cholecystitis by ultrasonographic examination were included in this study. The control group consisted of 18 patients without symptoms of gallstones and cholecystitis whose gallbladder walls were thickened due to cirrhotic ascites. Both groups were examined using diffusion weighted imaging, and the mean ADC values were compared using Student’s t-test.

Results

The diagnoses of the 40 patients were proven by histopathological examination. The mean ADC values of patients diagnosed with cholecystitis (1.68 ± 0.36 × 10^?3 mm²/s) were significantly lower than the mean ADC values of the control group (2.35 ± 0.24 × 10^?3 mm²/s) (p < 0.05). Receiver operating characteristics curve analysis based on ADC revealed a cut-off value of 2.04 × 10^?3 mm²/s for the diagnosis of cholecystitis, with a sensitivity of 94 % and a specificity of 89.7 %.

Conclusion

ADC value quantification may be an efficient method for making a diagnosis of cholecystitis and in differential diagnosis of cholecystitis from the extrinsic benign gallbladder wall thickening that can be seen during the course of cirrhotic ascites.     

3.0T MR扩散加权成像在甲状腺良恶性结节鉴别诊断中的价值

目的:探讨3.0T磁共振扩散加权成像(DWI)的表观扩散系数(ADC)在甲状腺良恶性结节鉴别诊断中的价值。方法:采用3.0T磁共振成像仪完成DWI成像,扩散敏感系数(b值)选用0、1000s/mm^2。测量经病理证实的13个甲状腺恶性结节、27个甲状腺良性结节以及20例正常甲状腺的ADC值,比较甲状腺良、恶性结节,正常腺体之间ADC值差异的统计学意义。结果:甲状腺良、恶性结节和正常腺体之间存在统计学意义上的差异(one-wayANOVA,F=26.664,P=0.000)。甲状腺良性结节平均ADC值为(2.43±0.54)×10^-3mm^2/s,恶性结节平均ADC值为(1.49±0.35)×10^-3mm^2/s,正常甲状腺平均ADC值为(1.84±0.20)×10^-3mm^2/s。甲状腺良、恶性结节ADC值之间的差异具有统计学意义(t=5.817,P=0.000)。将ADC值2.04×10^-3mm^2/s确定为甲状腺良恶性结节鉴别的阈值,其95%置信区间为0.84~1.01,诊断敏感性为85.2%,特异性为100%。结论:3.0T磁共振DWI成像的ADC值可以鉴别诊断甲状腺良恶性结节。     

Diagnostic performance of quantitative diffusion tensor imaging for the differentiation of breast lesions at 3 T MRI

BackgroundConventional breast magnetic resonance imaging (MRI), including dynamic contrast-enhanced MR mammography, may lead to ambiguous diagnosis and unnecessary biopsies.PurposeTo investigate the contribution of quantitative diffusion tensor imaging (DTI) in the discrimination between benign and malignant breast lesions at 3 T MRI.Material and methodsThe study included a total of 86 lesions (44 benign and 42 malignant) in 58 women (34 with malignant lesions, 23 with benign lesions and 1 with both types of lesions). All patients were examined on a 3 T MRI scanner. Fractional Anisotropy (FA), Mean Diffusivity (MD), Apparent Diffusion Coefficient (ADC), as well as eigenvalues (λ₁, λ₂, λ₃) were calculated and compared between benign and malignant lesions using two different software packages (GE Functool and ExploreDTI).ResultsMalignant lesions exhibited significantly lower ADC values compared to benign ones (ADC_mal = 1.06 × 10⁻³ mm²/s, ADC_ben = 1.54 × 10⁻³ mm²/s, p-value < 0.0001). FA measurements in carcinomas indicated slightly higher values than those in benign lesions (FA_mal = 0.20 ± 0.07, FA_ben = 0.15 ± 0.05, p-value = 0.0003). Eigenvalues λ₁, λ₂, λ₃, showed significantly lower values in malignant tumors compared to benign lesions and normal breast tissue. ROC curve analysis of ADC and DTI metrics demonstrated that ADC provides high diagnostic performance (AUC = 0.944) while, MD and λ₁ showed best discriminative results (AUC = 0.906) for the differentiation of malignant and benign lesions in contrast to other DTI parameters.ConclusionThe addition of eigenvalue analysis improves DTI's ability to differentiate between benign and malignant breast lesions.     

Diagnostic performance of diffusion-weighted MR imaging in differentiation of diabetic osteoarthropathy and osteomyelitis in diabetic foot

PurposeTo study the diagnostic performance of diffusion weighted MR imaging in differentiation of diabetic osteoarthropathy and osteomyelitis in diabetic foot.Patients and methodsThis prospective study was carried out on 41 patients with diabetic foot, 22 males and 19 females with mean age of 51 years. They underwent diffusion-weighted MR imaging of the foot. The apparent diffusion coefficient (ADC) values of the bony lesions were calculated by two reviewers and correlated with the surgical findings or biopsy. The kappa statistic (k) was used to estimate the proportion of inter-observer agreement of two reviewers.ResultsThe mean ADC of acute diabetic osteoarthropathy was 1.27 ± 0.19 × 10⁻³ mm²/s for reviewer 1 and 1.26 ± 0.21 × 10⁻³ mm²/s for reviewer 2. The mean ADC value in diabetic osteomyelitis was 0.86 ± 0.11 × 10⁻³ mm²/s for reviewer 1 and 0.85 ± 0.12 × 10⁻³ mm²/s for reviewer 2. There was excellent inter-observer agreement of ADC value of bony lesions in diabetic foot by both reviewers (K = 0.93). There was statistically significant difference in the ADC values of both groups (P = 0.001). The cut-off point of ADC value of both reviewers used in differentiating acute diabetic osteoarthropathy and osteomyelitis were 0.98 × 10⁻³ mm²/s and 1.04 × 10⁻³ mm²/s with an accuracy of 94% and 93% and area under the curve of 0.94 and 0.93 respectively.ConclusionWe conclude that the ADC value is a non-invasive imaging parameter that can help in differentiation of diabetic osteoarthropathy from osteomyelitis with excellent inter-observer agreement.