Sensitivity and Specificity of Computed Tomography in the Evaluation of Bone Mineral Density in Mexican Patients with Breast Cancer

Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology

PURPOSE OF REVIEW

The purpose of this review is to inform researchers and clinicians with the most recent imaging techniques that are employed (1) to opportunistically screen for osteoporosis and (2) to provide a better understanding into the disease etiology of osteoporosis.

RECENT FINDINGS

Phantomless calibration techniques for computed tomography (CT) may pave the way for better opportunistic osteoporosis screening and the retroactive analysis of imaging data. Additionally, hardware advances are enabling new applications of dual-energy CT and cone-beam CT to the study of bone. Advances in MRI sequences are also improving imaging evaluation of bone properties. Finally, the application of image registration techniques is enabling new uses of imaging to investigate soft tissue-bone interactions as well as bone turnover. While DXA remains the most prominent imaging tool for osteoporosis diagnosis, new imaging techniques are becoming more widely available and providing additional information to inform clinical decision-making.

The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions

Background

The present study aims to investigate the role of histogram analysis of intravoxel incoherent motion (IVIM) in the differential diagnosis of benign and malignant breast lesions.

Methods

The magnetic resonance imaging and clinical data of 55 patients (63 lesions) were retrospectively analyzed. The multi-b-valued diffusion-weighted imaging image was processed using the MADC software to obtain the gray-scaled maps of apparent diffusion coefficient (ADC)-slow, ADC-fast and f. The MaZda software was used to extract the histogram metrics of these maps. Combined with the conventional sequence images, the region of interest (ROI) was manually drawn along the edge of the lesion at the maximum level of the gray-scale image, and the difference of the data was analyzed between the benign and malignant breast lesions.

Results

There were 29 patients with 37 benign lesions, which included 23 fibroadenomas, 6 adenosis, 1 breast cysts, 4 intraductal papillomas, and 3 inflammations of breast. Furthermore, 26 malignant lesions in 26 patients, which included 20 non-specific invasive ductal carcinomas, 5 intraductal carcinomas and 1 patient with squamous cell carcinoma. The ADC-slow (mean and the 50th percentile) and f (minimum, mean, kurtosis, the 10th percentile and 50th percentile) of these malignant breast lesions were significantly lower than those of benign lesions (P < 0.05), while ADC-fast (kurtosis) and f (variance, skewness) of these malignant breast lesions were significantly higher than those of benign lesions (P < 0.05).

Conclusion

The histogram analysis of ADC-slow (mean and the 50th percentile), ADC-fast (kurtosis) and f (minimum, mean, kurtosis, the 10th percentile and 50th percentile. Variance, skewness) can provide a more objective and accurate basis for the differential diagnosis of benign and malignant breast lesions.