Soft-tissue tumors evaluated by line-scan diffusion-weighted imaging: influence of myxoid matrix on the apparent diffusion coefficient

PURPOSE: To compare the apparent diffusion coefficients (ADCs) of myxoid and nonmyxoid soft-tissue tumors using line-scan diffusion-weighted imaging (LSDWI), and to investigate the myxoid matrix influence on ADCs of soft-tissue tumors. MATERIALS AND METHODS: This study enrolled 44 patients with soft tissue tumors. They were divided into two groups: one with myxoid-containing soft-tissue tumors (N = 23) and the other with nonmyxoid soft-tissue tumors (N = 21). The 44 patients were also classified histologically into 26 with malignant soft-tissue tumors and 18 with benign soft-tissue tumors. LSDWI was performed using b values of 5 and 1000 second/mm(2). The ADCs of the tumors were calculated and compared for myxoid and nonmyxoid tumors and for benign and malignant tumors. RESULTS: The ADC (mean +/- SD) was 1.92 +/- 0.41 x 10(-3) mm(2)/second in myxoid containing tumors, whereas the ADC was 0.97 +/- 0.33 x 10(-3) mm(2)/second in nonmyxoid tumors. The ADCs of the myxoid and nonmyxoid tumors were significantly different (P < 0.01). The ADCs were 1.45 +/- 0.59 x 10(-3) mm(2)/second in malignant tumors and 1.50 +/- 0.64 x 10(-3) mm(2)/second in benign tumors. The ADCs of benign and malignant soft-tissue tumors were not significantly different. CONCLUSION: The ADCs of myxoid-containing soft-tissue tumors were significantly higher than those of nonmyxoid soft-tissue tumors. The myxoid matrix influences ADCs of both benign and malignant soft-tissue tumors.     

Quantitative diffusion imaging in breast cancer: a clinical prospective study

PURPOSE: To study the correlation between apparent diffusion coefficient (ADC) and pathology in patients with undefined breast lesion, to validate how accurately ADC is related to histology, and to define a threshold value of ADC to distinguish malignant from benign lesions. MATERIALS AND METHODS: Seventy-eight patients (110 lesions) were referred for positive or dubious findings. Three-dimensional fast low-angle shot (3D-FLASH) with contrast injection was applied. EPI diffusion-weighted imaging (DWI) with fat saturation was performed, and ROIs were selected on subtraction 3D-FLASH images before and after contrast injection, and copied on an ADC map. Inter- and intraobserver analyses were performed. RESULTS: At pathology 22 lesions were benign, 65 were malignant, and 23 were excluded. The ADCs of malignant and benign lesions were statistically different. In malignant tumors the ADC was (mean +/- SEM) 0.95 +/- 0.027 x 10(-3)mm(2)/second, and in benign tumors it was 1.51 +/- 0.068 x 10(-3)mm(2)/second. According to receiver operating characteristic (ROC) curves, we found a threshold between malignant and benign lesions for highest sensitivity and specificity (both 86%) around 1.13 +/- 0.10 x 10(-3)mm(2)/second. For a threshold of 0.95 +/- 0.10 x 10(-3)mm(2)/second, specificity was 100% but sensitivity was very low. Inter- and intraobserver studies showed good reproducibility. CONCLUSION: The ADC may help to differentiate benign and malignant lesions with good specificity, and may increase the overall specificity of breast MRI.     

Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging

PURPOSE: To evaluate the value of diffusion-weighted imaging (DWI) in distinguishing between benign and malignant breast lesions. MATERIALS AND METHODS: Fifty-two female subjects (mean age = 58 years, age range = 25-75 years) with histopathologically proven breast lesions underwent DWI of the breasts with a single-shot echo-planar imaging (EPI) sequence using large b values. The computed mean apparent diffusion coefficients (ADCs) of the breast lesions and cell density were then correlated. RESULTS: The ADCs varied substantially between benign breast lesions ((1.57 +/- 0.23) x 10(-3) mm(2)/second) and malignant breast lesions ((0.97 +/- 0.20) x 10(-3) mm(2)/second). In addition, the mean ADCs of the breast lesions correlated well with tumor cellularity (P < 0.01, r = -0.542). CONCLUSION: The ADC would be an effective parameter in distinguishing between malignant and benign breast lesions. Further, tumor cellularity has a significant influence on the ADCs obtained in both benign and malignant breast tumors.     

ADC mapping of benign and malignant breast tumors.

PURPOSE: The purpose of this study was to investigate the utility of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) value in differentiating benign and malignant breast lesions and evaluating the detection accuracy of the cancer extension. MATERIALS AND METHODS: We used DWI to obtain images of 191 benign and malignant lesions (24 benign, 167 malignant) before surgical excision. The ADC values of the benign and malignant lesions were compared, as were the values of noninvasive ductal carcinoma (NIDC) and invasive ductal carcinoma (IDC). We also evaluated the ADC map, which represents the distribution of ADC values, and compared it with the cancer extension. RESULTS: The mean ADC value of each type of lesion was as follows: malignant lesions, 1.22+/-0.31 x 10(-3) mm2/s; benign lesions, 1.67+/-0.54 x 10(-3) mm2/s; normal tissues, 2.09+/-0.27 x 10(-3) mm2/s. The mean ADC value of the malignant lesions was statistically lower than that of the benign lesions and normal breast tissues. The ADC value of IDC was statistically lower than that of NIDC. The sensitivity of the ADC value for malignant lesions with a threshold of less than 1.6 x 10(-3) mm2/s was 95% and the specificity was 46%. A full 75% of all malignant cases exhibited a near precise distribution of low ADC values on ADC maps to describe malignant lesions. The main causes of false negative and underestimation of cancer spread were susceptibility artifact because of bleeding and tumor structure. Major histologic types of false-positive lesions were intraductal papilloma and fibrocystic diseases. Fibrocystic diseases also resulted in overestimation of cancer extension. CONCLUSIONS: DWI has the potential in clinical appreciation to detect malignant breast tumors and support the evaluation of tumor extension. However, the benign proliferative change remains to be studied as it mimics the malignant phenomenon on the ADC map.     

CT and radiography of bacterial respiratory infections in AIDS patients

OBJECTIVE: Acute vertebral collapse is common, and it is sometimes difficult to determine whether the cause is benign or malignant. Recently, diffusion-weighted imaging has been reported to be useful for differentiating the two types. The purpose of this study was to evaluate diffusion abnormalities quantitatively in benign and malignant compression fractures using line scan diffusion-weighted imaging. SUBJECTS AND METHODS. Line scan diffusion-weighted imaging was prospectively performed in 17 patients with 20 acute vertebral compression fractures caused by osteoporosis or trauma, in 12 patients with 16 vertebral compression fractures caused by malignant tumors, and in 35 patients with 47 metastatic vertebrae without collapse. Images were obtained at b values of 5 and 1,000 sec/mm(2). The apparent diffusion coefficient (ADC) was measured in vertebral compression fractures and metastatic vertebrae without collapse. RESULTS: The ADC (mean +/- SD) was 1.21 +/- 0.17 x 10(-3) mm(2)/sec in benign compression fractures, 0.92 +/- 0.20 x 10(-3) mm(2)/sec in malignant compression fractures, and 0.83 +/- 0.17 x 10(-3) mm(2)/sec in metastatic vertebral lesions without collapse. The ADC was significantly higher in benign compression fractures than in malignant compression fractures (p < 0.01), although the two types showed considerable overlap. CONCLUSION: Although the quantitative assessment of vertebral diffusion provides additional information concerning compressed vertebrae, the benign and malignant compression fracture ADC values overlap considerably. Therefore, even a quantitative vertebral diffusion assessment may not always permit a clear distinction between benign and malignant compression fractures.     

Head and neck lesions: characterization with diffusion-weighted echo-planar MR imaging

PURPOSE: To evaluate whether apparent diffusion coefficients (ADCs) calculated from diffusion-weighted echo-planar magnetic resonance (MR) images can be used to characterize head and neck lesions. MATERIALS AND METHODS: Diffusion-weighted echo-planar MR imaging was performed with a 1.5-T MR unit in 97 head and neck lesions in 97 patients. Images were obtained with a diffusion-weighted factor, factor b, of 0, 500, and 1,000 sec/mm(2), and an ADC map was constructed. The ADCs of lesions, cerebrospinal fluid, and spinal cord were calculated. RESULTS: Acceptable images for ADC measurement were obtained in 81 (84%) patients. The mean ADC of malignant lymphomas, (0.66 +/- 0.17[SD]) x 10(-3) mm(2)/sec (n = 13), was significantly smaller (P <.001) than that of carcinomas. The mean ADC of carcinomas, (1.13 +/- 0.43) x 10(-3) mm(2)/sec (n = 36), was significantly smaller (P =.002) than that of benign solid tumors. The mean ADC of benign solid tumors, (1.56 +/- 0.51) x 10(-3) mm(2)/sec (n = 22), was significantly smaller (P =.035) than that of benign cystic lesions, (2.05 +/- 0.62) x 10(-3) mm(2)/sec (n = 10). No significant differences were seen in the mean ADC of cerebrospinal fluid and of spinal cord among four groups of lesions. When an ADC smaller than 1.22 x 10(-3) mm(2)/sec was used for predicting malignancy, the highest accuracy of 86%, with 84% sensitivity and 91% specificity, was obtained. CONCLUSION: Measurement of ADCs may be used to characterize head and neck lesions.     

Discrimination of metastatic cervical lymph nodes with diffusion-weighted MR imaging in patients with head and neck cancer

BACKGROUND AND PURPOSE: Metastasis to the regional cervical lymph nodes may be associated with alterations in water diffusivity and microcirculation of the node. We tested whether diffusion-weighted MR imaging could discriminate metastatic nodes. METHODS: Diffusion-weighted echo-planar and T1- and T2-weighted MR imaging sequences were performed on histologically proved metastatic cervical lymph nodes (25 nodes), benign lymphadenopathy (25 nodes), and nodal lymphomas (five nodes). The apparent diffusion coefficient (ADC) was calculated by using two b factors (500 and 1000 s/mm(2)). RESULTS: The ADC was significantly greater in metastatic lymph nodes (0.410 +/- 0.105 x 10(-3) mm(2)/s, P <.01) than in benign lymphadenopathy (0.302 +/- 0.062 x 10(-3) mm(2)/s). Nodal lymphomas showed even lower levels of the ADC (0.223 +/- 0.056 x 10(-3) mm(2)/s). ADC criteria for metastatic nodes (>/= 0.400 x 10(-3) mm(2)/s) yielded a moderate negative predictive value (71%) and high positive predictive value (93%). Receiver operating characteristic analysis demonstrated that the criteria of abnormal signal intensity on T1- or T2-weighted images (A(z) = 0.8437 +/- 0.0230) and ADC (A(z) = 0.8440 +/- 0.0538) provided similar levels of diagnostic ability in differentiating metastatic nodes. The ADC from metastatic nodes from highly or moderately differentiated cancers (0.440 +/- 0.020 x 10(-3) mm(2)/s, P <.01) was significantly greater than that from poorly differentiated cancers (0.356 +/- 0.042 x 10(-3) mm(2)/s). CONCLUSION: Diffusion-weighted imaging is useful in discriminating metastatic nodes.     

Apparent diffusion coefficient in malignant lymphoma and carcinoma involving cavernous sinus evaluated by line scan diffusion-weighted imaging

PURPOSE: To evaluate the apparent diffusion coefficient (ADC) of malignant lymphomas and carcinomas involving cavernous sinus by line scan diffusion-weighted imaging (LSDWI) and to determine the usefulness of this method for differentiating between the two tumors. MATERIALS AND METHODS: Four patients with malignant lymphomas and six patients with carcinomas were prospectively studied. LSDWI images were obtained with two different b values of 5 seconds/mm(2) and 1000 seconds/mm(2) in the coronal plane. The ADC values of the two types of tumors were calculated and compared. RESULTS: LSDWI provided diagnostic images with minimum susceptibility artifacts and enabled measurement of the ADC. The ADC value (mean +/- SD) was 0.51 +/- 0.06 x 10(-3) mm(2)/second in malignant lymphomas and 0.99 +/- 0.08 x 10(-3) mm(2)/second in carcinomas. A significant difference in ADC values was found between the two (P < 0.01). CONCLUSION: Malignant lymphomas showed significantly lower ADC value than carcinomas. ADC provides additional useful information about differentiation between these tumors.     

Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors

OBJECTIVE: Common contrast-enhancing malignant tumors of the brain are glioblastoma multiforme (GBMs), anaplastic astrocytomas (AAs), metastases, and lymphomas, all of which have sometimes similar conventional MRI findings. Our aim was to evaluate the role of perfusion MR imaging (PWI) and diffusion-weighted imaging (DWI) in the differentiation of these contrast-enhancing malignant cerebral tumors. MATERIALS AND METHODS: Forty-eight patients with contrast-enhancing and histologically proven brain tumors, 14 AAs, 17 GBMs, nine metastases, and eight lymphomas, were included in the study. All patients have undergone routine MR examination where DWI and PWI were performed in the same session. DWI was performed with b values of 0, 500, and 1000 mm(2)/s. Minimum ADC values (ADC(min)) of each tumor was later calculated from ADC map images. PWI was applied using dynamic susceptibility contrast technique and maximum relative cerebral blood volume (rCBV(max)) was calculated from each tumor, given in ratio with contralateral normal white matter. Comparisons of ADC(min) and rCBV(max) values with the histological types of the enhancing tumors were made with a one-way analysis of variance and Bonferroni test. A P value less than 0.05 indicated a statistically significant difference. RESULTS: The ADC(min) values (mean+/-S.D.) in GBMs, AAs, lymphomas, and metastases were 0.79+/-0.21 (x10(-3)mm(2)/s), 0.75+/-0.21 (x10(-3)mm(2)/s), 0.51+/-0.09 (x10(-3)mm(2)/s), and 0.68+/-0.11 (x10(-3)mm(2)/s), respectively. The difference in ADC(min) values were statistically significant between lymphomas and GBMs (P<0.05). It was also statistically significant between lymphomas and AAs (P<0.03). However, there were no differences between lymphomas and metastasis, and between GBMs, AAs, and metastasis. The rCBV(max) ratio (mean+/-S.D.) in GBMs were 6.33+/-2.03, whereas it was 3.66+/-1.79 in AAs, 2.33+/-0.68 in lymphomas, and 4.45+/-1.87 in metastases. These values were statistically different between GBMs and AAs (P<0.001), GBMs and lymphoma (P<0.0001). Although there seemed to be difference between GBMs and metastases, it was not statistically significant (P<0.083). CONCLUSION: Combination of DWI and PWI, with ADC(min) and rCBV(max) calculations, may aid routine MR imaging in the differentiation of common cerebral contrast-enhancing malignant tumors.     

Diffusion-weighted MRI in the characterization of soft-tissue tumors

PURPOSE: To explore the potential of perfusion-corrected diffusion-weighted magnetic resonance imaging (MRI) in characterizing soft-tissue tumors. METHODS AND MATERIALS: Diffusion-weighted MRI was performed in 23 histologically proven soft-tissue masses using a diffusion-weighted spin-echo sequence with diffusion gradient strengths yielding five b-values (0-701 seconds/mm(2)). True diffusion coefficients and perfusion fractions were estimated and compared with apparent diffusion coefficients (ADCs). RESULTS: ADC values of all tumors, subcutaneous fat, and muscle were significantly higher than true diffusion coefficients, indicating a contribution of perfusion to the ADC. True diffusion coefficients of malignant tumors (1.08 x 10(-3) mm(2)/second) were significantly lower than those of benign masses (1.71 x 10(-3) mm(2)/second), whereas ADC values between these groups were not significantly different. CONCLUSION: Perfusion-corrected diffusion-weighted MRI has potential in differentiating benign from malignant soft-tissue masses.     

ADC平均值及最小值在鉴别良、恶性四肢软组织肿瘤中的价值

目的:探讨ADC平均值及最小值在鉴别四肢软组织肿瘤良恶性中的价值.方法:搜集经病理证实的53例四肢软组织肿瘤患者,其中良性24例,恶性29例,53例患者均行MRI及DWI检查,分别测量病灶的ADC平均值及ADC最小值.采用独立样本t检验比较良、恶性四肢软组织肿瘤的ADC平均值及ADC最小值差异;采用受试者工作特征(RO...     

Minimum apparent diffusion coefficients in the evaluation of brain tumors

OBJECTIVE: To determine whether diffusion-weighted imaging by using minimum apparent diffusion coefficient (ADC(min)) values could differentiate various brain tumors including gliomas, metastases, and lymphomas. MATERIALS AND METHODS: We examined 65 patients with histologically or clinically diagnosed brain tumors (12 low-grade gliomas, 31 high-grade gliomas, 14 metastatic tumors, and 8 lymphomas) using a 1.5 T MR unit. On diffusion-weighted imaging, the ADC(min) values were measured within the tumors and mean values were evaluated regarding statistical differences between groups. RESULTS: The ADC(min) values of low-grade gliomas (1.09+/-0.20 x 10(-3)mm(2)/s) were significantly higher (p<.001) than those of other tumors. There were no statistical significant differences between glioblastomas (0.70+/-0.16 mm(2)/s), anaplastic astrocytomas (0.77+/-0.21 mm(2)/s), metastases (0.78+/-0.21 mm(2)/s), and lymphomas. But, lymphomas had lower mean ADC(min) values (0.54+/-0.10mm(2)/s) than high-grade gliomas and metastases. CONCLUSION: The ADC measurements may help to differentiate low-grade gliomas from high-grade gliomas, metastases, and lymphomas. Although there is no statistical difference, lymphomas seem to have marked restriction in diffusion coefficients.     

Apparent diffusion coefficient: a quantitative parameter for in vivo tumor characterization

PURPOSE: The purpose of the this study was to evaluate the potential of diffusion weighted imaging (DWI) to distinguish different tissue compartments in early, intermediate and advanced tumor stages. MATERIALS AND METHODS: Twenty-two male mice were induced with squamous cell tumor (SCCVII) and scanned with a clinical 1.5 T scanner. T1-SE, T2-FSE, diffusion weighted Line-Scan-MRI and contrast enhanced T1-SE were obtained from mice with early (tumor volume 10-100 mm(3)), intermediate (200-600 mm(3)), advanced tumors (600-1000 mm(3)) and tumor necrosis (>1500 mm(3)). The apparent diffusion coefficient (ADC) of different tumor compartments was calculated offline with a pixel-by-pixel method. The animals were sacrificed immediately after scanning and histopathologic correlation was performed. RESULTS: In early stages of tumor development, tumors appeared homogeneous on diffusion weighted images with an ADC of 0.64+/-0.06 x 10(-3) mm(2)/s. With tumor progression the ADC in the rim areas of tumor increased significantly (intermediate stage: 0.70+/-0.11 x 10(-3) mm(2)/s; advanced stage: 0.88+/-0.11 x 10(-3) mm(2)/s; tumor necrosis 1.03+/-0.06 x 10(-3) mm(2)/s), whereas the ADC in viable tumor remained constant. Histologically the areas with an increased ADC correlated well with areas of necrosis (reduced cell density). CONCLUSION: The ADC is a non-invasive technique to monitor changes in the biological structure of tumor tissue during tumor progression. Thus, DWI is a potential diagnostic tool for in-vivo tissue characterization.     

Usefulness of the calculated apparent diffusion coefficient value in the differential diagnosis of retroperitoneal masses

PURPOSE: To elucidate whether or not the apparent diffusion coefficient (ADC) values calculated from echo-planar diffusion-weighted (EPDW) MR images are useful in the differential diagnosis of retroperitoneal masses. MATERIALS AND METHODS: In 50 patients with known retroperitoneal masses, EPDW images were performed with b-factors of 0-1100 seconds/mm2. The final histologic diagnoses of these lesions were as follows: 12 malignant lymphomas, four other malignant mesenchymal neoplasms, 25 malignant epithelial neoplasms, seven benign mesenchymal neoplasms, and two nonneoplastic lesions. The ADC values obtained for the solid portion of the lesions were used to represent each lesion, and the values of the histologic groups were compared. RESULTS: The respective value of ADC for 12 malignant lymphomas, four other mesenchymal neoplasms, seven benign mesenchymal neoplasms, and two nonneoplastic lesions were as follows: 0.66 +/- 0.26, 1.26 +/- 0.50, 0.90 +/- 0.20, 1.87 +/- 0.48, 1.32 +/- 0.20 x 10(-3) mm2/second. The ADC value of the malignant lymphoma was significantly lower than that of the other malignant mesenchymal lesions, and was also lower than the ADC of the benign lesions. The ADC value of the malignant epithelial neoplasms was lower than that of the benign mesenchymal tumors. The ADC values of the malignant and benign lesions were 0.94 +/- 0.30 and 1.75 +/- 0.49 x 10(-3) mm2/second, respectively, which also demonstrated a significant difference. CONCLUSION: ADC values calculated from EPDW MR images may provide useful information in the differential diagnosis of retroperitoneal masses.     

Evaluation of liver diffusion isotropy and characterization of focal hepatic lesions with two single-shot echo-planar MR imaging sequences: prospective study in 66 patients

PURPOSE: To (a) evaluate liver diffusion isotropy, (b) compare two diffusion-weighted magnetic resonance (MR) imaging sequences for the characterization of focal hepatic lesions by using two or four b values, and (c) determine an apparent diffusion coefficient (ADC) threshold value to differentiate benign from malignant lesions. MATERIALS AND METHODS: Sixty-six patients were examined with two single-shot echo-planar diffusion-weighted MR sequences. In the first sequence, liver diffusion isotropy was evaluated by using diffusion gradients in three directions with two b values. In the second sequence, a unidirectional diffusion gradient was used with four b values. ADCs were measured in 43 patients with 52 focal hepatic lesions more than 1 cm in diameter and in 23 patients with 14 normal and nine cirrhotic livers and were compared by using nonparametric tests. RESULTS: Diffusion in the liver parenchyma was isotropic. ADCs of focal hepatic lesions were significantly different between sequences (P <.01). The mean (+/- SD) ADCs in the first sequence were 0.94 x 10(-3) mm(2)/sec +/- 0.60 for metastases, 1.33 x 10(-3) mm(2)/sec +/- 0.13 for HCCs, 1.75 x 10(-3) mm(2)/sec +/- 0.46 for benign hepatocellular lesions, 2.95 x 10(-3) mm(2)/sec +/- 0.67 for hemangiomas, and 3.63 x 10(-3) mm(2)/sec +/- 0.56 for cysts. There was a significant difference between benign (2.45 x 10(-3) mm(2)/sec +/- 0.96, isotropic value) and malignant (1.08 x 10(-3) mm(2)/sec +/- 0.50) lesions (P <.01 for both sequences). CONCLUSION: Diffusion-weighted MR imaging can help differentiate benign from malignant hepatic lesions. The use of two b values in one direction could be sufficient for the design of MR sequences in the liver.     

Usefulness of the apparent diffusion coefficient in line scan diffusion-weighted imaging for distinguishing between squamous cell carcinomas and malignant lymphomas of the head and neck

BACKGROUND AND PURPOSE: Squamous cell carcinoma (SCC) and lymphoma are common malignant tumors of the head and neck. The purpose of this study was to determine whether the apparent diffusion coefficient (ADC) in line scan diffusion-weighted imaging (LSDWI) is useful for distinguishing between SCC and lymphoma of the head and neck. METHODS: LSDWI was prospectively performed in 39 patients with SCC and in 14 patients with lymphoma. Images were obtained with a diffusion-weighted factor (b factor) of 5 and 1000 s/mm(2), and ADC maps were generated. ADC values were measured for the two types of tumor. RESULTS: Mean ADC values were 0.96 +/- 0.11 x 10(-3) mm(2)/s for SCC and 0.65 +/- 0.09 x 10(-3) mm(2)/s for lymphoma; the difference was significant (P < .001). All but one of the patients with lymphoma had ADC values lower than the lowest ADC (0.76 x 10(-3) mm(2)/s) in patients with SCC. When an ADC of 0.76 x 10(-3) mm(2)/s was used to distinguish between SCC and lymphoma, accuracy was 98% (52 of 53 lesions). CONCLUSION: ADC values appear to be useful for distinguishing between SCC and lymphoma in the head and neck.     

The role of diffusion-weighted imaging and the apparent diffusion coefficient (ADC) values for breast tumors.

OBJECTIVE: We wanted to evaluate the role of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) for detecting breast tumors, as compared with the T1- and T2-weighted images. MATERIALS AND METHODS: Forty-one female patients underwent breast MRI, and this included the T1-, T2-, DWI and dynamic contrast-enhanced images. Sixty-five enhancing lesions were detected on the dynamic contrast-enhanced images and we used this as a reference image for detecting tumor. Fifty-six breast lesions were detected on DWI and the histological diagnoses were as follows: 43 invasive ductal carcinomas, one mucinous carcinoma, one mixed infiltrative and mucinous carcinoma, seven ductal carcinomas in situ (DCIS), and four benign tumors. First, we compared the detectability of breast lesions on DWI with that of the T1- and T2-weighted images. We then compared the ADCs of the malignant and benign breast lesions to the ADCs of the normal fibroglandular tissue. RESULTS: Fifty-six lesions were detected via DWI (detectability of 86.2%). The detectabilities of breast lesions on the T1- and T2-weighted imaging were 61.5% (40/65) and 75.4% (49/65), respectively. The mean ADCs of the invasive ductal carcinoma (0.89+/-0.18 x 10(-3)mm(2)/second) and DCIS (1.17+/-0.18 x 10(-3)mm(2)/ second) are significantly lower than those of the benign lesions (1.41+/-0.56 x 10(-3)mm(2)/second) and the normal fibroglandular tissue (1.51+/-0.29 x 10(-3)mm(2)/ second). CONCLUSION: DWI has a high sensitivity for detecting breast tumors, and especially for detecting malignant breast tumors. DWI was an effective imaging technique for detecting breast lesions, as compared to using the T1- and T2-weighted images.     

Role of diffusion-weighted echo-planar MR imaging in differentiation of residual or recurrent head and neck tumors and posttreatment changes

BACKGROUND AND PURPOSE: The purpose of this work was to evaluate whether diffusion-weighted MR imaging can be used in differentiating residual or recurrent head and neck tumors from postoperative or postradiation changes. MATERIALS AND METHODS: This study included 32 patients clinically suspected for recurrent head and neck tumor after surgery (n=3), radiation therapy (n=13), or both (n=16). Diffusion-weighted MR imaging was done by using a single-shot spin-echo echo-planar sequence. The apparent diffusion coefficient (ADC) value of the suspected lesion was calculated and correlated with pathologic results. RESULTS: Adequate diffusion-weighted MR images and ADC maps were obtained in 30 patients (93.8%). The mean ADC value of residual or recurrent lesions (1.17 +/- 0.33 x 10(-3) mm(2)/s) was less than that of posttherapeutic changes (2.07 +/- 0.25 x 10(-3) mm(2)/s), and the difference was statistically significant (P<.001). When an ADC value of 1.30 x 10(-3) mm(2)/s was used as a threshold value for differentiation, the best results were obtained with an accuracy of 87%, sensitivity of 84%, specificity of 90%, positive predictive value of 94%, and negative predictive value of 76%. CONCLUSIONS: Diffusion-weighted MR imaging with ADC measurement has promising results for differentiating residual or recurrent head and neck tumors from postoperative or postradiation changes.     

Evaluation of diffusion-weighted imaging for the differential diagnosis of poorly contrast-enhanced and T2-prolonged bone masses: Initial experience

PURPOSE: To determine whether quantitative diffusion-weighted imaging (DWI) is useful for characterizing poorly contrast-enhanced and T2-prolonged bone masses. MATERIALS AND METHODS: We studied 20 bone masses that showed high signal intensity on T2-weighted images and poor enhancement on contrast-enhanced T1-weighted images. These included eight solitary bone cysts, five fibrous dysplasias, and seven chondrosarcomas. To analyze diffusion changes we calculated the apparent diffusion coefficient (ADC) for each lesion. RESULTS: The ADC values of the two types of benign lesions and chondrosarcomas were not significantly different. However, the mean ADC value of solitary bone cysts (mean +/-SD, 2.57 +/- 0.13 x 10(-3) mm(2)/second) was significantly higher than that of fibrous dysplasias and chondrosarcomas (2.0 +/- 0.21 x 10(-3) mm(2)/second and 2.29 +/- 0.14 x 10(-3) mm(2)/second, respectively, P < 0.05). None of the lesions with ADC values lower than 2.0 x 10(-3) mm(2)/second were chondrosarcomas. CONCLUSION: Although there was some overlapping in the ADC values of chondrosarcomas, solitary bone cyst, and fibrous dysplasia, quantitative DWI may aid in the differential diagnosis of poorly contrast-enhanced and T2-prolonged bone masses.     

Comparison between MRI with spin-echo echo-planar diffusion-weighted sequence (DWI) and histology in the diagnosis of soft-tissue tumours

Purpose

Our aim was to assess the usefulness of magnetic resonance imaging (MRI) with spin-echo echo-planar diffusion-weighted sequences (SE-EPI-DWI) in the study of primary and secondary soft-tissue tumours by correlating the results of imaging and histology.

Material and methods

We retrospectively studied 23 patients (14 men, 9 women; age range 25?C87 years) affected by soft-tissue lesions. The MRI study was performed with baseline and contrast-enhanced SE-T1, proton density/T2-weighted (PD/T2), fat-saturated (FATSAT) DP/T2 and single-shot SE-EPI-DWI (b value 50-400- 800s/mm2) sequences.

Results

We identified 7/23 benign lesions (three myxoid, four nonmyxoid) and 16/23 malignant tumours (four myxoid, 12 nonmyxoid) with a mean diameter between 21 mm and 20 cm. Qualitative analysis of DWI showed persistence of high signal intensity for increasing b-values in all malignant tumours. Quantitative DWI analysis of the apparent diffusion coefficient (ADC) maps showed a statistical difference between benign and malignant lesions.

Conclusions

In our experience, DWI with qualitative and quantitative analysis correlated well with histology.