Objective To determine the value of 99m Tc-M IB I scintimmmography in diagnosing primary breast cancer and axillary lymph node metastases1Methods Independent, prospective, blinded studies were selected from the Co-chrane L ibrary, MEDL INE, Springer, Elsevier and China National Knowledge Infrastructure, Sensitivity, specificity, andaccuracy of scintimammography were estimated by comparison with the results of biop sy1 Subsequently, the characteristicsof included articles such as sensitivity, specificity of 99m Tc-M IB I scintimammorgraphy were extracted and assessed1 Differ-ent effectmodelwas chosen to calculate different pooled weighted values of sensitivity, specificity and the corresponding95% confidence intervals (95%CI). Summary receiver operating characteristic (SROC) curves was performed, then thediagnostic value was evaluated by SROC. Results The pooled ensitivity, specificity of 99m Tc-M IB I scintimammography inevaluating breastmasses, respectively were 86% (95%CI from 8-% to 89%) and 80% (95%CI from 75% to 80%). The area under the SROC (AUC) was 901-9%. For palpable breast cancer, the pooled sensitivity and specificity were86% (95%CI from 83% to 88%) and 83% (95% CI from 77% to 86%). The AUC is 94168%. For non-palpablebreast cancer, the pooled sensitivity and specificitywere 69% (95%CI from 47% to 85%) and 69% (95%CI from 5-% to8-%), respectively. The AUC was 78197%. For metastatic axillary lymph node, the pooled sensitivity and specificitywere 75% (95% CI from 66% to 81%) and 86% (95% CI from 75% to 91%) respectively. The AUC was 87164%. Conclusions 99m Tc-M IB I scintimammography has a better value in evaluating palpable breast masses when an adequatespecimen is obtained1 It has a higher specificity in evaluatingmetastatic axillary lymph node with a relativelylow sensitivi-ty. Its value for non-palpable breast cancer is limited and new methods are warranted.

ROI (region of interest) plays an important role in medical image analysis. In this paper, an efficient approach to ROI extraction based on monotonically marching curve evolution is proposed. The improvement is in two aspects: first, a new monotonically marching snake integrating ROI information is presented by minimizing the new defined ROI energy. Due to the region based speed term, the front could even propagate in low contrast and narrow thin areas. Second, a multi-initial fast marching algorithm is developed for numerical implementation, where a multi-initial scheme can perform the selective growth of the front, thus further reduce the front leaking. Furthermore, a multiscale scheme for numerical implementation is adopted, where a fast passing solution method is used for determining the initial solution on the finer scale that greatly reduces the computational cost. The validity of the proposed approach is demonstrated on the medical image ROI extraction. Experimental results show that the approach is efficient both in computational cost and segmentation quality. Low contrast and narrow thin ROI could be efficiently extracted precisely by the approach.