Biomedical subjects

Junko Takaba

Publications and source records attributed to Junko Takaba.

4 recordsLinked to original sources

PubMed2005

Detection and differentiation of lactate and lipids by single-voxel proton MR spectroscopy.

The signals of lactate and lipids partially overlap in single-voxel proton MR spectroscopy (1HMRS), sometimes making them difficult to differentiate in clinical settings. Our aim in this study was to identify lactate and lipids by varying the echo time (TE). We expect that the accurate detection of lactate and lipids will have high diagnostic value in the diagnosis of brain tumors. Following our protocol, we obtained meaningful 1HMRS spectra from 213 patients, including 163 patients with brain tumors, between August 1999 and February 2004. 1HMRS was performed with a TE of 144 ms followed by a TE of 30 ms and/or a TE of 288 ms, if necessary. For the 213 patients, lactate level was "negative" in 47 patients, "positive" in 131 patients, and "strongly positive" in 35 patients. The lipid level was "negative" in 90 patients, "positive" in 56 patients, and "strongly positive" in 67 patients. Based on logistic discriminant analyses of neuro-epithelial tumor WHO grade and lactate and lipid levels, lactate and lipid levels were significant between WHO grades 2 and 3 (P=0.0239) and between grades 3 and 4 (P=0.0347). Lipids are a more significant factor for the discrimination between WHO grades 2 and 3 (P=0.0073) and between grades 3 and 4 (P=0.0048). With our method of varying the TE, it is possible accurately and efficiently to detect lactate and lipids in the brain. We found a significant correlation between lactate and lipid expression and WHO grade of neuro-epithelial tumors.

Aged↗

PubMed2005

Apparent diffusion coefficient of human brain tumors at MR imaging.

PURPOSE: To determine if apparent diffusion coefficient (ADC) can be used to differentiate brain tumors at magnetic resonance (MR) imaging. MATERIALS AND METHODS: Institutional review board approval or informed patient consent was not required. MR images were reviewed retrospectively in 275 patients with brain tumors: 147 males and 128 females 1-81 years old, treated between September 1997 and July 2003. Regions of interest were placed manually in tumor regions on MR images, and ADC was calculated with a five-point regression method at b values of 0, 250, 500, 750, and 1000 sec/mm2. ADC values were average values in tumor. All brain tumor subgroups were analyzed. Logistic discriminant analysis was performed by using ADC, age, and patient sex as independent variables to discriminate among tumor groups. RESULTS: A significant negative correlation existed between ADC and astrocytic tumors of World Health Organization grades 2-4 (grade 2 vs grades 3 and 4, accuracy of 91.3% [P < .01]; grade 3 vs 4, accuracy of 82.4% [P < .01]). ADC of dysembryoplastic neuroepithelial tumors (DNTs) was higher than that of astrocytic grade 2 tumors (accuracy, 100%) and other glioneuronal tumors. ADC of malignant lymphomas was lower than that of glioblastomas and metastatic tumors (accuracy, 83.6%; P < .01). ADC of primitive neuroectodermal tumors (PNETs) was lower than that of ependymomas (accuracy, 100%). ADC of meningiomas was lower than that of schwannomas (accuracy, 92.4%; P < .01). ADC of craniopharyngiomas was higher than that of pituitary adenomas (accuracy, 85.2%; P < .05). ADC of epidermoid tumors was lower than that of chordomas (accuracy, 100%). In meningiomas, ADC was not indicative of malignancy grade or histologic subtype. CONCLUSION: ADC is useful for differentiation of some human brain tumors, particularly DNT, malignant lymphomas versus glioblastomas and metastatic tumors, and ependymomas versus PNETs.

Adolescent↗

PubMed2003

[Evaluation of brain in myotonic dystrophy using diffusion tensor MR imaging].

In many cases of myotonic dystrophy, high-intensity areas are seen in the cerebral white matter on T2-weighted imaging. Brain MRI was performed in 15 patients with myotonic dystrophy using diffusion tensor imaging, which is sensitive to the detailed structure of white matter, and the results were compared with those of normal controls. FA (anisotropic diffusion) values in the cerebral white matter of myotonic dystrophy patients were significantly lower than those of normal controls (p< 0.01), even if the hyperintense lesion was not seen on T2-weighted imaging. Values of trace (isotropic diffusion) in myotonic dystrophy patients were significantly higher than those of normal controls (p< 0.05), except in the posterior limb of the internal capsule. Diffusion tensor imaging could detect pathological change of the cerebral white matter in myotonic dystrophy patients, and may be useful for quantification and detection of subtle pathological change.

Adult↗

PubMed2003

[Contrast enhanced fast fluid-attenuated inversion-recovery MR imaging for diagnosing cerebral venous angioma: report of two cases].

It has been reported that contrast-enhanced fluid-attenuated inversion-recovery (FLAIR) sequences were useful for detecting superficial abnormalities, such as meningeal disease, because they do not demonstrate contrast enhancement of cortical vessels with slow flow as do T1-weighted images. We reported the usefulness of contrast-enhanced FLAIR images to differentiate cerebral venous angioma from tumor in two patients. Case 1 was a 71-year-old man developed cortical hemorrhage. Post contrast-enhanced T1-weighted images showed an enhanced lesion around the hematoma, whereas contrast-enhanced FLAIR images showed no enhancement of the lesion, thus he was diagnosed as cortical hemorrhage from cerebral venous angioma. Case 2 was a 72-year-old woman, who was examined MR images because of the jugular foramen neurinoma. There was a T2-high-intensity lesion in the right frontal lobe, and post contrast-enhanced T1-weighted images showed an enhanced lesion in and around the T2-high-intensity lesion. Post-contrast FLAIR images showed no enhancement, and she was diagnosed as cerebral venous angioma. Contrast-enhanced fast FLAIR sequences was useful in differentiation between venous angiomas and tumors. Identification of these lesions was due to the flow-void phenomenon in vessels with slow-flowing blood such as venous angioma, which could not be differentiated from tumors on T1-weighted images.

Aged↗