ABSTRACT
Breast cancer is the most common cancer in female population. Early detection of breast lesions and proper differentiation will directly impact on clinical treatment strategy and is related with prognosis. Breast tumors are usually rich in vascularity. Contrast-enhanced spectral mammography (CESM), based on K-edge effect of iodine, can acquire images of iodine contrast distribution in breasts through special computing and subtraction of images with both low- and high-energy X-ray exposures after intravenous induction of iodinated contrast media. It can eliminate the disturbance caused by overlapping breast tissues and demonstrate blood supply of the lesions, thus is sensitive to small lesion, more accurate in tumor delineating and able to help diagnosing. The current clinical applications and progresses of CESM were reviewed in this article.
ABSTRACT
Objective To evaluate the ability of texture analysis in early phase of enhanced MRI in predicting pathological complete response(pCR) after neoadjuvant chemotherapy(NAC) for breast cancer. Methods This retrospective study enrolled 64 breast cancers samples from 64 patients that were diagnosed by core-needle biopsy and received NAC before operation in Peking University Cancer Hospital between July and Dec 2015. MRI were conducted after NAC. Regions of interest were drawn to cover the whole enhanced areas on subtraction images of early phase to pre-enhanced phase on MRI, and were sent to an in-house developed texture-analyzing software to achieve parameters including average signal intensity (SIav), mean signal intensity (SIm), signal intensity range(SIr), skewness, kurtosis, energy and entropy. Groups of pCR (no invasive tumor) and non-pCR were separated based on pathology results. Differences of MRI parameters were compared by independent-sample t test (normal distribution) or Mann-Whitney U test (abnormal distribution) and ROC curve were drawn to evaluate the diagnostic abilities. Results Post-operation pathology found 28 pCR and 36 non-pCR. ROIs of 13 samples were not drawn because no residual enhanced areas could be found on subtraction images of post-NAC MRI. For 51 lesions (17 pCR and 34 non-pCR) that still had residual enhancement, tumor volume, SIav, SIr, energy and entropy of pCR group were all significantly lower than that of non-pCR group (P＜0.05). ROC curves were drawn, yielding AUC=0.669 for non-enhancement criterion, and the accuracy, sensitivity and specificity were 70.3%, 39.3% and 94.4%. AUCs for volume, SIav, SIr, Energy and Entropy were 0.870, 0.772, 0.810, 0.883 and 0.881 respectively. Conclusion Texture analysis on early-enhanced phase of breast MRI is able to help to improve the diagnostic ability in predicting complete response on in breast cancer after NAC.
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Objective To assess the ability of pixel-based quantitative evaluation of CT values in differentiating benign and malignant cystic-solid ovarian tumors.Methods CT images of 41 cystic-solid ovarian lesions from 39 patients were reviewed,with 27 benign and 14 malignant confirmed by post-operation pathology or follow-up.Regions of interest (ROIs) were drawn along edges of tumors on all slices of contrast-enhanced images with ImageJ software.CT values of each pixel were extracted.CT values of 20,25,30,35 and 40 HU were used respectively as the threshold to divide cystic and solid components.Solid proportion,the mean and median CT values of solid component were calculated and compared between benign and malignant groups.Results Mean CT values of solid components were all higher in malignant than in benign ovarian masses under all the threshold values (P<0.05).For median CT values, the same trend existed under the threshold of 20,25,35 and 40 HU (P<0.05).For the solid proportion,difference was found only under the 40 HU threshold, with lower value in malignant group (0.67±0.25) than in benign group (0.47±0.31).ROC curves were drawn to differentiate benign and malignant lesions.The highest AUC was obtained by using the mean CT value of solid components defined by 40 HU threshold (AUC=0.735).Conclusion Pixel-based quantitative evaluation on CT images could help to define cystic and solid components of ovarian masses, with 40 HU to be an optimal threshold.Cystic-to-solid proportion and CT value of solid components derived from whole lesion can help to differentiate benign or malignant lesions.
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OBJECTIVE To implement the automatic management of medical equipment.METHODS Based on the platform of net,three layers of C/S were applied with database technology to realize one-time importation of the basic information and current information,it made the information function of quantity evaluation,quantity determination,schedule formation,automatic alarm,apparatus distribution list,statistical inquiry,collection analysis,and information feedback coming to true.RESULTS By using one year,the application of management information system of medical equipment could meet the requirement in scientific and standardized supply,and standard,application and management of medical equipment.CONCLUSIONS It can be able to improve the system efficiency,reduce the labor and mistakes,and also achieve the aim that cannot be done by manual labor.