Monitoring Progression of Ductal Carcinoma In Situ Using Photoacoustics and Contrast-Enhanced Ultrasound

Image Features and Diagnostic Value of Contrast-Enhanced Ultrasound for Ductal Carcinoma In Situ of the Breast: Preliminary Findings

To explore the image features and the diagnostic value of contrast-enhanced ultrasound (CEUS) for ductal carcinoma in situ (DCIS) of the breast. A total of 96 female patients with a solitary and histologically proven DCIS were analyzed retrospectively, and 100 female cases of invasive ductal carcinoma (IDC) lesions were used as the control group. The Breast Imaging Reporting and Data System (BI-RADS) category of breast lesions was assessed according to conventional ultrasound features. The DCIS lesions were classified into mass type and non-mass type. The CEUS characteristics of these breast lesions were retrospectively analyzed qualitatively and quantitatively. The final gold standard was biopsy or surgery with histo-pathological examination. Comparing the ultrasound images of DCIS with that of IDC, there were significant differences in echo pattern, calcification morphology, and calcification distribution (p < .05 for all). There was a significant difference between DCIS and IDC in enhancement intensity, perfusion defects, peripheral high enhancement, intratumoral vessels, and arrival time (AT) (p < .05 for all). In the logistic multivariate regression analysis, two indicators linked with DCIS were recognized: perfusion defects (p = .002) and peripheral high enhancement (p < .001). In forecasting DCIS, the logistic regression equation resulted in an AUC of 0.689, a specificity of 0.720, and a sensitivity of 0.563. CEUS showed differences in enhancement characteristics between DCIS and IDC, with perfusion defects and peripheral high enhancement being associated with DCIS.

Cardiolipin for Enhanced Cellular Uptake and Cytotoxicity of Thermosensitive Liposome-Encapsulated Daunorubicin toward Breast Cancer Cell Lines

Daunorubicin (DNR) and cardiolipin (CL) were co-delivered using thermosensitive liposomes (TSLs). 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), 1-myristoyl-2-stearoyl-sn-glycero-3-phosphocholine (MSPC), cholesterol, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] or DSPE-mPEG (2000) and CL were used in the formulation of liposomes at a molar ratio of 57:40:30:3:20, respectively. CL forms raft-like microdomains that may relocate and change lipid organization of the outer and inner mitochondrial membranes. Such transbilayer lipid movement eventually leads to membrane permeabilization. TSLs were prepared by thin-film hydration (drug:lipid ratio 1:5) where DNR was encapsulated within the aqueous core of the liposomes and CL acted as a component of the lipid bilayer. The liposomes exhibited high drug encapsulation efficiency (>90%), small size (~115 nm), narrow size distribution (polydispersity index ~0.12), and a rapid release profile under the influence of mild hyperthermia. The liposomes also exhibited ~4-fold higher cytotoxicity against MDA-MB-231 cells compared to DNR or liposomes similar to DaunoXome® (p < 0.001). This study provides a basis for developing a co-delivery system of DNR and CL encapsulated in liposomes for treatment of breast cancer.

An Automatic Unmixing Approach to Detect Tissue Chromophores from Multispectral Photoacoustic Imaging

Multispectral photoacoustic imaging has been widely explored as an emerging tool to visualize and quantify tissue chromophores noninvasively. This modality can capture the spectral absorption signature of prominent tissue chromophores, such as oxygenated, deoxygenated hemoglobin, and other biomarkers in the tissue by using spectral unmixing methods. Currently, most of the reported image processing algorithms use standard unmixing procedures, which include user interaction in the form of providing the expected spectral signatures. For translational research with patients, these types of supervised spectral unmixing can be challenging, as the spectral signature of the tissues can differ with respect to the disease condition. Imaging exogenous contrast agents and accessing their biodistribution can also be problematic, as some of the contrast agents are susceptible to change in spectral properties after the tissue interaction. In this work, we investigated the feasibility of an unsupervised spectral unmixing algorithm to detect and extract the tissue chromophores without any a-priori knowledge and user interaction. The algorithm has been optimized for multispectral photoacoustic imaging in the spectral range of 680-900 nm. The performance of the algorithm has been tested on simulated data, tissue-mimicking phantom, and also on the detection of exogenous contrast agents after the intravenous injection in mice. Our finding shows that the proposed automatic, unsupervised spectral unmixing method has great potential to extract and quantify the tissue chromophores, and this can be used in any wavelength range of the multispectral photoacoustic images.

Diagnostic efficacy of contrast-enhanced ultrasound for breast lesions of different sizes: a comparative study with magnetic resonance imaging

OBJECTIVE

This study aimed to compare the diagnostic performance of contrast-enhanced ultrasound (CEUS), MRI, and the combined use of the two modalities for differentiating breast lesions of different sizes.

METHODS

A total of 406 patients with 406 solid breast masses detected by conventional ultrasound underwent both CEUS and MRI scans. Histological results were used as reference standards. The lesions were categorized into three groups according to size (Group 1, ≤ 20 mm; Group 2, > 20 mm, Group 3: total lesions). Sensitivity, specificity, accuracy, and receiver operating characteristic (ROC) curve analysis were used to assess the diagnostic performance of these imaging methods for breast lesions.

RESULTS

There were 194 benign and 212 malignant breast lesions according to the histological diagnosis. Compared with MRI, CEUS demonstrated similar sensitivity in detecting breast cancer (p = 1.0000 for all) in all the three groups. With regard to specificity, accuracy, and the area under the ROC curve (Az) values, MRI showed a better performance than that shown by CEUS (p ＜0.05 for all), and the combination of the two modalities improved the diagnostic performance of CEUS alone significantly (p ＜0.05 for all) in all the three groups. However, the diagnostic specificity and accuracy of the combined method was not superior to that of MRI alone except for Group 2.

CONCLUSION

CEUS demonstrated good sensitivity in detecting breast cancer, and the combined use with MRI can optimize the diagnostic specificity and accuracy in breast cancer prediction.

ADVANCES IN KNOWLEDGE

Few studies have compared the diagnostic efficacy of CEUS and MRI, and this study is the first attempt to seek out the diagnostic values for breast lesions of variable sizes (lesions with ≤20 mm and >20 mm).