Thermoacoustic imaging (TAI) is a new non-invasive, non-ionization and nondestructive modality capable of high microwave contrast and high ultrasound resolution, and it has attracted extensive attention in recent years. This review introduces the technical principle, imaging system and imaging characteristics of TAI, and then introduces the application of TAI for breast cancer detection as an example. This review introduces the advantages of TAI in solving corresponding clinical problems in view of its high resolution and high contrast. In addition, it also explains the roles of TAI in medical diagnosis and treatment. Finally, the potential applications of TAI in medical diagnosis is introduced from many aspects and multiple perspectives. The future development of TAI in the challenges of current medical diagnosis is also prospected.
Acoustics ; Breast Neoplasms ; diagnostic imaging ; Diagnostic Imaging ; methods ; Humans ; Microwaves

Bone and Bones/diagnostic imaging* ; Breast/diagnostic imaging* ; Breast Neoplasms/diagnostic imaging* ; Female ; Humans

Objective To compare the values of dynamic enhanced magnetic resonance imaging(DCE-MRI),digital breast tomosynthesis(DBT),and digital mammography(DM)in the early detection and diagnosis of breast cancer.Methods We retrospectively analyzed the clinical and imaging data of 65 cases with early breast cancer confirmed by surgical pathology from June 2017 to December 2018.All patients underwent breast DCE-MRI,DM and DBT before surgery.The receiver operating characteristic(ROC)curves were drawn,with the pathological results as the gold standard,to evaluate the diagnostic performance of different examination methods.The areas under ROC curves(AUCs)were compared using test.The differences among DCE-MRI,DBT and DM in detecting early breast cancer were compared using chi-square test in terms of positive rates,accuracy,sensitivity,and specificity.Pearson correlation analysis was performed to assess the accuracy of these imaging methods in detecting the size of early breast cancer.Results The AUCs of DCE-MRI,DBT,and DM based on the BI-RADS classification for early diagnosis of breast cancer were 0.910,0.832,and 0.700,respectively(=2.132,=0.001);the sensitivity of DCE-MRI,DBT,and DM for early breast cancer was 92.3%,70.8%,and 52.5%,the specificity was 65.0%,85.0%,and 79.3%,and the accuracy was 83.1%,70.8%,and 50.8%,indicating that DCE-MRI(=15.330,=0.0001) and DBT(=5.450,=0.020) had significantly higher diagnostic accuracy than DM.The measurement results of DM,DBT,and DCE-MRI were positively correlated with the pathological measurements(=0.781,=0.847,=0.946;all <0.01). Conclusions DCE-MRI and DBT have higher positive rates and accuracies than DM in detecting early breast cancer.Medical institutions where DCE-MRI is still not available can use DBT to improve the early detection of breast cancer.
Breast ; diagnostic imaging ; Breast Neoplasms ; diagnostic imaging ; Female ; Humans ; Magnetic Resonance Imaging ; Mammography ; methods ; Retrospective Studies

Breast-Specific Gamma Imaging (BSGI) is an improved and optimizing nuclear medicine breast imaging technique on the basis of traditional gamma camera. It uses a high resolution, small field-of-view scintilla detector. The detector is designed with 3 073 individual detector crystals and 48 position-sensitive photomultiplier tubes. The FOV of detector is 15 cm x 20 cm, and optimal system resolution for breast imaging is 3 mm, can detect the diameter of only 2-3 mm small lesions. BSGI has better sensitivity in detecting subcentimetre or nonpalpable breast cancer. The sensitivity for the diagnosis of breast cancer is high, not influenced by the density of the breast tissue, implants, architectural distortion-or scars from prior surgery or radiation. So it is called a high resolution, small field-of-view breast-specific gamma camera.
Breast ; Breast Neoplasms ; diagnosis ; Diagnostic Imaging ; Female ; Gamma Cameras ; Humans

OBJECTIVES: Accurate breast lesion surface localization can guarantee accurate biopsy and local treatment. But there is no guideline to regular equipment and methods for the localization of breast lesions. The conventional non-invasive localization method is marker-based localization. The advantages of this method are simple and efficient. The disadvantages are that markers disappear easily under coupling agents; the positioning length of markers cannot last long on skin; and healthcare associated infection due to many patients using the same marker pen is potentially unavoidable. Breast lesion sticker (called sticker for short) is a new-type localization medical instrument in 2020. Our study aims to explore the clinical value of a new lesion stickers in breast lesion surface localization via comparison of the sticker and marker pen localization methods. METHODS: This was a prospective cohort study. It was conducted in 67 patients who needed breast lesion surface localization before biopsy. The patients were randomly assigned into 2 groups. One group of patients used marker pen to mark breast lesion surface location by ultrasonography. The other group of patients used stickers. Patients labeled with markers on skin were swabbed agents before marking. Then the markers were checked by ultrasound scan. If the surface positions of breast lesion were not correct, the above procedure was repeated. In the sticker group, the stickers were released synchronously after the lesions were detected by ultrasound scan. Then locations were checked via scanning hole. If the surface positions of breast lesion were not correct, the above procedure was repeated. The accuracy of positioning, the length of positioning time and satisfaction of patients between the 2 groups were compared. The length of positioning time was calculated from the time when ultrasound detected the lesion to the time when the surface position of breast lesion was confirmed. The total score of patients' satisfaction was 5 points according to Service Quality Evaluation of SERVQUAL Scale, including sonographers' service attitude and their technical proficiency, other medical staffs' service attitude and their technical proficiency, hospital service procedures, positioning comfort, and positioning effects. RESULTS: All 67 patients were females, aged 18-66 (39.73±13.10). There were 35 patients in the marker pen group and 32 patients in the sticker group. The time length of group used marker pen to localization was 22-88 (52.20±2.90) s, and the sticker group was 3-15 (9.22±0.58) s in length. The length of positioning time for the stickers was significantly shorter than that of the marker (P<0.01). Both methods were accurate in the surface localization of lesions before operation. The total scores of patients' satisfaction was 4-5 (4.92±0.02) in the stickers group, and 1-5 (3.35±0.10) in the marker pen group. The patients' satisfaction scores with the sticker were significantly higher than those with the marker pen (P<0.01). The length of positioning time and patients' satisfication scores for sonographer with 20 years' working experience were shorter and higher than those of sonographer with 10 years' working experience, respectively (both P<0.05). CONCLUSIONS The new breast lesion positioning stickers have more advantages than the marker pen in localization efficiency. It could reduce the workload of medical workers and increase patients' satisfaction to some extent. The stickers can be used not only in the breast lesions surface localization, but also in the skin location of pleural effusion and ascites, the skin location of surface masses, the skin location of thyroid nodule, and many other clinical marker areas, to further expand the scope of clinical application and value of the stickers.
Breast/diagnostic imaging* ; Breast Neoplasms/diagnostic imaging* ; Female ; Humans ; Male ; Prospective Studies ; Skin

To evaluate the value of automatic breast volume scanner (ABVS) and mammography (MG) in differential diagnosis for small breast lesions with breast imaging reporting and data system ultrasound (BI-RADS-US) 4.
 Methods: ABVS and MG were performed for 103 patients with 109 breast lesions, which were classified as BI-RADS-US 4 by conventional ultrasound (US). Postoperative pathological diagnosis served as gold standard. The diagnostic efficacy for US, US combined with MG, US combined with ABVS and the combination of three methods were compared.
 Results: The sensitivity of US, US combined with MG, US combined with ABVS and the combination of three methods were 85.5%, 86.8%, 94.7% and 96.0%, respectively. The specificity for them were 66.7%, 69.7%, 81.8% and 84.9%, respectively. The accuracy for them were 79.8%, 81.6%, 90.8% and 92.7%, respectively. The area under the receiver operating characteristic (ROC) curve (AUC) for them were 0.76, 0.78, 0.88 and 0.90, respectively. The accuracy and AUC for US combined with ABVS in differential diagnosis of BI-RADS-US 4 small breast lesions were significantly higher than those of US and US combined with MG (P<0.05). There was no significant difference in sensitivity and specificity among these 3 groups (P>0.05). No significant difference was found in sensitivity, specificity, accuracy, and AUC between US combined with ABVS and the combination of three methods (P>0.05).
 Conclusion: Combination of US with ABVS can improve the diagnostic efficacy of conventional US in differential diagnosis for BI-RADS-US 4 small breast lesions, and it is superior to US combined with MG.
Breast ; diagnostic imaging ; Breast Neoplasms ; diagnostic imaging ; Female ; Humans ; Mammography ; Reproducibility of Results ; Sensitivity and Specificity ; Ultrasonography, Mammary

In order to preprocess mammograms for diagnosing the early cases of breast cancer and improving the computational efficiency in the computer-aided detection of micro-calcifications in mammograms, we have advanced a novel processing technique for the extraction of micro-calcification region of interest (MROI). The proposed method is based on a three-step procedure: (1) the mammogram is divided into sub-images of the same size; (2) the wavelet multi-resolution method is conducted on the sub-images, and the parameters related to wavelet transform and threshold T are discussed according to rho; (3) the classification of sub-images is determined by T. It is tested with 20 mammograms and the results show that the method can achieve a true positive rate as high as 89.7% with a false positive rate as low as 2.1%.
Breast Diseases ; diagnostic imaging ; pathology ; Breast Neoplasms ; diagnostic imaging ; pathology ; Calcinosis ; diagnostic imaging ; Diagnosis, Computer-Assisted ; Humans ; Mammography

To explore the values of minimal apparent diffusion coefficient(ADC),difference between ratios of apparent diffusion coefficients(ADC),and dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)in the treatment of breast ductal carcinoma in situ with microinvasion(DCIS-Mi). Totally 27 patients with DCIS-Mi and 31 patients with breast ductal carcinoma in situ(DCIS)were collected in our hospital from October,2016 to June,2018.Philips Ingenia 3.0T superconducting magnetic resonance scanner and dedicated phase-controlled array surface coil were used for breast examinations.ADC and maximum apparent diffusion coefficient(ADC)were selected from multiple regions of interest(ROI)in the apparent diffusion coefficients(ADC)figure,and ADC was calculated.In addition,DCE-MRI characteristics were analyzed. The ADC of DCIS-Mi was significantly lower than that of DCIS[(1.15±0.03)×10 mm /s .(1.34±0.04)×10 mm /s,=-7.192,=0.002],the ADC was significantly higher than that of DCIS[(0.32±0.03)×10 mm /s .(0.18±0.08)×10 mm /s,=-10.228,<0.001],and the early enhancement rate of DCIS-Mi was higher than that of DCIS[159.71(157.82,162.49)% .147.29(143.59,160.22)%,=-3.578,=0.007].The background parenchymal enhancement of DCIS-Mi was moderate,severe,and non-lump-like,mainly segmental,and the internal enhancement was heterogeneous or clustered circular.Multivariate Logistic regression analysis showed that non-internal characteristics of the mass,the edge of the mass,internal enhancement characteristics of the mass,time-intensity curve,early enhancement rate,ADC and ADC were the optimal variables for the diagnosis of DCIS-Mi,and the optimal variables were shown by receiver operating characteristic(ROC)curve analysis:the area under curve,sensitivity and specificity of ADC,ADC,non-tumor internal enhancement,and tumor internal enhancement were higher,with the critical values being 1.12×10 mm /s,0.31×10 mm /s,1.50,and 1.50,respectively. DCE-MRI combined with ADC value(especially ADC,ADC,non-mass internal enhancement,and mass internal enhancement)is helpful in differentiating breast DCIS-Mi and DCIS.
Breast ; Breast Neoplasms ; diagnostic imaging ; Carcinoma, Intraductal, Noninfiltrating ; diagnostic imaging ; Diffusion Magnetic Resonance Imaging ; Humans ; Magnetic Resonance Imaging

Breast Neoplasms ; diagnosis ; Diagnostic Imaging ; methods ; standards ; Female ; Humans

OBJECTIVE: Feature extraction of breast tumors is very important in the breast tumor detection (benign and malignant) in ultrasound image. The traditional quantitative description of breast tumors has some shortcomings, such as inaccuracy. A simple and accurate feature extraction method has been studied. METHODS: In this paper, a new method of boundary feature extraction was proposed. Firstly, the shape histogram of ultrasound breast tumors was constructed. Secondly, the relevant boundary feature factors were calculated from a local point of view, including sum of maximum curvature, sum of maximum curvature and peak, sum of maximum curvature and standard deviation. Based on the boundary features, shape features and texture features, the linear support vector machine classifiers for benign and malignant breast tumor recognition was constructed. RESULTS: The accuracy of boundary features in the benign and malignant breast tumors classification was 82.69%. The accuracy of shape features was 73.08%. The accuracy of texture features was 63.46%. The classification accuracy of the three fusion features was 86.54%. CONCLUSIONS The classification accuracy of boundary features was higher than that of texture features and shape features. The classification method based on multi-features has the highest accuracy and it describes the benign and malignant tumors from different angles. The research results have practical value.
Algorithms ; Breast Neoplasms ; diagnostic imaging ; Humans ; Support Vector Machine ; Ultrasonography