We describe a new method for quantitative imaging of strain and elastic modulus distributions in soft tissues. The method is based on external tissue compression, with subsequent computation of the strain profile along the transducer axis, which is derived from cross-correlation analysis of pre- and post-compression A-line pairs. The strain profile can then be converted to an elastic modulus profile by measuring the stresses applied by the compressing device and applying certain corrections for the nonuniform stress field. We report initial results of several phantom and excised animal tissue experiments which demonstrate the ability of this technique to quantitatively image strain and elastic modulus distributions with good resolution, sensitivity and with diminished speckle. We discuss several potential clinical uses of this technique.
Early diagnosis is extremely important for treatment and prognosis of skin cancer. Reflectance confocal microscopy (RCM) is a recently developed technique used to diagnose skin cancer. This meta-analysis was carried out to assess the accuracy of RCM for the diagnosis of malignant skin tumours. We conducted a systematic literature search of EMBASE, PubMed, the Cochrane Library and Web of Science database for relevant articles in English published up to 24 December 2015. The quality of the included studies was assessed using the QUADAS-2 tool. Statistical analyses were conducted using the software Meta-Disc version 1.4 and STATA version 12.0. A total of 21 studies involving 3108 patients with a total of 3602 lesions were included in the per-lesion analysis. The corresponding pooled results for sensitivity and specificity were 93.6% (95% CI: 0.92-0.95) and 82.7% (95% CI: 0.81-0.84) respectively. Positive likelihood ratio and negative likelihood ratio were 5.84 (95% CI: 4.27-7.98) and 0.08 (95% CI: 0.07-0.10) respectively. Subgroup analysis showed that RCM had a sensitivity of 92.7% (95% CI: 0.90-0.95) and a specificity of 78.3% (95% CI: 0.76-0.81) for detecting melanoma. The pooled sensitivity and specificity of RCM for detecting basal cell carcinoma were 91.7% (95% CI: 0.87-0.95) and 91.3% (95% CI: 0.94-0.96) respectively. RCM is a valid method of identifying malignant skin tumours accurately.
Gliosarcoma demonstrates certain characteristic MR features, such as supratentorial and peripheral location, well-demarcated, abutting a dural surface, uneven and thick-walled rim-like or ring enhancement, as well as intratumoral strip enhancement. These findings, combined with patient age, can aid the differential diagnosis of gliosarcomas from more common primary brain tumors.
BACKGROUND AND PURPOSE: Accurate differentiation between glioblastoma and solitary brain metastasis is of vital importance clinically. This study aimed to investigate the potential value of the inflow-based vascular-space-occupancy MR imaging technique, which has no need for an exogenous contrast agent, in differentiating glioblastoma and solitary brain metastasis and to compare it with DSC MR imaging.
MATERIALS AND METHODS:Twenty patients with glioblastoma and 22 patients with solitary brain metastasis underwent inflowbased vascular-space-occupancy and DSC MR imaging with a 3T clinical scanner. Two neuroradiologists independently measured the maximum inflow-based vascular-space-occupancy-derived arteriolar CBV and DSC-derived CBV values in intratumoral regions and peritumoral T2-hyperintense regions, which were normalized to the contralateral white matter (relative arteriolar CBV and relative CBV, inflow-based vascular-space-occupancy relative arteriolar CBV, and DSC-relative CBV). The intraclass correlation coefficient, Student t test, or Mann-Whitney U test and receiver operating characteristic analysis were performed.RESULTS: All parameters of both regions had good or excellent interobserver reliability (0.74$0.89). In peritumoral T2-hyperintese regions, DSC-relative CBV (P , .001), inflow-based vascular-space-occupancy arteriolar CBV (P ¼ .001), and relative arteriolar CBV (P ¼ .005) were significantly higher in glioblastoma than in solitary brain metastasis, with areas under the curve of 0.94, 0.83, and 0.72 for discrimination, respectively. In the intratumoral region, both inflow-based vascular-space-occupancy arteriolar CBV and relative arteriolar CBV were significantly higher in glioblastoma than in solitary brain metastasis (both P , .001), with areas under the curve of 0.91 and 0.90, respectively. Intratumoral DSC-relative CBV showed no significant difference (P ¼ .616) between the 2 groups.CONCLUSIONS: Inflow-based vascular-space-occupancy has the potential to discriminate glioblastoma from solitary brain metastasis, especially in the intratumoral region.ABBREVIATIONS: AUC ¼ area under the curve; CBVa ¼ arteriolar CBV; GBM ¼ glioblastoma; iVASO ¼ inflow-based vascular-space-occupancy; rCBV ¼ relative CBV; rCBVa ¼ relative arteriolar CBV; PTH ¼ peritumoral T2-hyperintesity region; SBM ¼ solitary brain metastasis G lioblastoma (GBM) accounts for 40%$50% of all primary malignant brain tumors in adults. Brain metastases are the most common complication of systemic cancer, and half of them are solitary at diagnosis. 1 It is clinically important to distinguish GBM from solitary brain metastasis (SBM) because of the vast differences in these 2 entities with regard to tumor staging, treatment approach, and clinical outcomes. 2-4 Structural gadoliniumenhanced MR imaging is the preferred imaging examination for brain tumors, but with a limited capacity to differentiate GBM and SBM. They share similar imaging features, such as extensive
KH902 could improve retinal electrophysiological function and inhibit the breakdown of iBRB by inhibiting the expression of VEGFR2, PlGF and PI3K, and the activation of SRC, AKT and ERK.
Abstract. Deformable image registration (DIR) is a critical technic in adaptive radiotherapy (ART) to propagate contours between planning computerized tomography (CT) images and treatment CT/Cone-beam CT (CBCT) image to account for organ deformation for treatment re-planning. To validate the ability and accuracy of DIR algorithms in organ at risk (OAR) contours mapping, seven intensity-based DIR strategies are tested on the planning CT and weekly CBCT images from six Head & Neck cancer patients who underwent a 6 ∼ 7 weeks intensity-modulated radiation therapy (IMRT). Three similarity metrics, i.e. the Dice similarity coefficient (DSC), the percentage error (PE) and the Hausdorff distance (HD), are employed to measure the agreement between the propagated contours and the physician delineated ground truths. It is found that the performance of all the evaluated DIR algorithms declines as the treatment proceeds. No statistically significant performance difference is observed between different DIR algorithms (p > 0.05), except for the double force demons (DFD) which yields the worst result in terms of DSC and PE. For the metric HD, all the DIR algorithms behaved unsatisfactorily with no statistically significant performance difference (p = 0.273). These findings suggested that special care should be taken when utilizing the intensitybased DIR algorithms involved in this study to deform OAR contours between CT and CBCT, especially for those organs with low contrast.
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