Magnetic resonance imaging findings of radiation-induced breast angiosarcoma:A case report

BACKGROUND Breast conservation surgery(BCS)with adjuvant radiotherapy has become a gold standard in the treatment of early-stage breast cancer,significantly reducing the risk of tumor recurrence.However,this treatment is associated with adverse effects,including the rare but aggressive radiation-induced angiosarcoma(RIAS).Despite its rarity and nonspecific initial presentation,RIAS presents a challenging diagnosis,emphasizing the importance of imaging techniques for early detection and accurate diagnosis.CASE SUMMARY We present a case of a 48-year-old post-menopausal woman who developed skin ecchymosis on the right breast seven years after receiving BCS and adjuvant radiotherapy for breast cancer.Initial mammography and ultrasound were inconclusive,showing post-treatment changes but failing to identify the underlying angiosarcoma.Contrast-enhanced breast magnetic resonance imaging(MRI)revealed diffuse skin thickening and nodularity with distinctive enhan-cement kinetics,leading to the diagnosis of RIAS.This case highlights the crucial role of MRI in diagnosing and determining the extent of RIAS,facilitating timely and appropriate surgical intervention.CONCLUSION Breast MRI is crucial for detecting RIAS,especially when mammography and ultrasound are inconclusive.

Magnetic resonance imaging techniques for lithium-ion batteries:Principles and applications

Operando monitoring of internal and local electrochemical processes within lithium-ion batteries(LIBs)is crucial,necessitating a range of non-invasive,real-time imaging characterization techniques including nuclear magnetic resonance(NMR)techniques.This review provides a comprehensive overview of the recent applications and advancements of non-invasive magnetic resonance imaging(MRI)techniques in LIBs.It initially introduces the principles and hardware of MRI,followed by a detailed summary and comparison of MRI techniques used for characterizing liquid/solid electrolytes,electrodes and commercial batteries.This encompasses the determination of electrolytes'transport properties,acquisition of ion distribution profile,and diagnosis of battery defects.By focusing on experimental parameters and optimization strategies,our goal is to explore MRI methods suitable to a variety of research subjects,aiming to enhance imaging quality across diverse scenarios and offer critical physical/chemical insights into the ongoing operation processes of LIBs.

Value of Magnetic Resonance Imaging Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors

Objective To investigate the difference in texture features on diffusion weighted imaging(DWI) images between breast benign and malignant tumors.Methods Patients including 56 with mass-like breast cancer, 16 with breast fibroadenoma, and 4 with intraductal papilloma of breast treated in the Hainan Hospital of Chinese PLA General Hospital were retrospectively enrolled in this study, and allocated to the benign group(20 patients) and the malignant group(56 patients) according to the post-surgically pathological results. Texture analysis was performed on axial DWI images, and five characteristic parameters including Angular Second Moment(ASM), Contrast, Correlation, Inverse Difference Moment(IDM), and Entropy were calculated. Independent sample t-test and Mann-Whitney U test were performed for intergroup comparison. Regression model was established by using Binary Logistic regression analysis, and receiver operating characteristic curve(ROC) analysis was carried out to evaluate the diagnostic efficiency. Results The texture features ASM, Contrast, Correlation and Entropy showed significant differences between the benign and malignant breast tumor groups(PASM= 0.014, Pcontrast= 0.019, Pcorrelation= 0.010, Pentropy= 0.007). The area under the ROC curve was 0.685, 0.681, 0.754, and 0.683 respectively for the positive texture variables mentioned above, and that for the combined variables(ASM, Contrast, and Entropy) was 0.802 in the model of Logistic regression. Binary Logistic regression analysis demonstrated that ASM, Contrast and Entropy were considered as thespecific imaging variables for the differential diagnosis of breast benign and malignant tumors.Conclusion The texture analysis of DWI may be a simple and effective tool in the differential diagnosis between breast benign and malignant tumors.

Magnetic resonance imaging in breast cancer:A literature review and future perspectives

Early detection and diagnosis of breast cancer are essential for successful treatment. Currently mammography and ultrasound are the basic imaging techniques for the detection and localization of breast tumors. The low sensitivity and specificity of these imaging tools resulted in a demand for new imaging modalities and breast magnetic resonance imaging(MRI) has become increasingly important in the detection and delineation of breast cancer in daily practice. However, the clinical benefits of the use of pre-operative MRI in women with newly diagnosed breast cancer is still a matter of debate. The main additional diagnostic value of MRI relies on specific situations such as detecting multifocal, multicentric or contralateral disease unrecognized on conventional assessment(particularly in patients diagnosed with invasive lobular carcinoma), assessing the response to neoadjuvant chemotherapy, detection of cancer in dense breast tissue, recognition of an occult primary breast cancer in patients presenting with cancer metastasis in axillary lymph nodes, among others. Nevertheless, the development of new MRI technolo-gies such as diffusion-weighted imaging, proton spectroscopy and higher field strength 7.0 T imaging offer a new perspective in providing additional information in breast abnormalities. We conducted an expert literature review on the value of breast MRI in diagnosing and staging breast cancer, as well as the future potentials of new MRI technologies.

How to use magnetic resonance imaging following neoadjuvant chemotherapy in locally advanced breast cancer

Magnetic resonance imaging(MRI) is highly sensitive in identifying residual breast cancer following neoadjuvant chemotherapy(NAC), and consequently is a commonly used imaging modality in locally advanced breast cancer patients. In these patients, tumor response is an important prognostic indicator. However, discrepancies between MRI findings and surgical pathology are well documented. Overestimation of residual disease by MRI may result in greater surgery than is actually required while underestimation may result in insufficient surgery. Thus, it is important to understand when MRI findings are reliable and when they are less accurate. MRI most accurately predicts pathology in triple negative, Her2 positive and hormone receptor negative tumors, especially if they are of a solid imaging phenotype. In these cases, post-NAC MRI is highly reliable for surgical planning. Hormone receptor positive cancers and those demonstrating non mass enhancement show lower concordance with surgical pathology, making surgical guidance more nebulous in these cases. Radiologists and surgeons must assess MRI response to NAC in the context of tumor subtype. Indiscriminate interpretations will prevent MRI from achieving its maximum potential in the pre-operative setting.

Combined molybdenum target X-ray and magnetic resonance imaging examinations improve breast cancer diagnostic efficacy

BACKGROUND Early-stage breast cancer patients often lack specific clinical manifestations,making diagnosis difficult.Molybdenum target X-ray and magnetic resonance imaging(MRI)examinations both have their own advantages.Thus,a combined examination methodology may improve early breast cancer diagnoses.AIM To explore the combined diagnostic efficacy of molybdenum target X-ray and MRI examinations in breast cancer.METHODS Patients diagnosed with breast cancer at our hospital from March 2019 to April 2021 were recruited,as were the same number of patients during the same period with benign breast tumors.Both groups underwent molybdenum target X-ray and MRI examinations,and diagnoses were given based on each exam.The single(i.e.,X-ray or MRI)and combined(i.e.,using both methods)diagnoses were counted,and the MRI-related examination parameters(e.g.,T-wave peak,peak and early enhancement rates,and apparent diffusion coefficient)were compared between the groups.RESULTS In total,63 breast cancer patients and 63 benign breast tumor patients were recruited.MRI detected 53 breast cancer cases and 61 benign breast tumor cases.Molybdenum target X-ray detected 50 breast cancer cases and 60 benign breast tumor cases.The combined methodology detected 61 breast cancer cases and 61 benign breast tumor cases.The sensitivity(96.83%)and accuracy(96.83%)of the combined methodology were higher than single-method MRI(84.13%and 90.48%,respectively)and molybdenum target X-ray(79.37%and 87.30%,respectively)(P<0.05).The combined methodology specificity(96.83%)did not differ from singlemethod MRI(96.83%)or molybdenum target X-ray(95.24%)(P>0.05).The Twave peak(169.43±32.05)and apparent diffusion coefficient(1.01±0.23)were lower in the breast cancer group than in the benign tumor group(228.86±46.51 and 1.41±0.35,respectively).However,the peak enhancement rate(1.08±0.24)and early enhancement rate(1.07±0.26)were significantly higher in the breast cancer group than in the benign tumor group(0.83±0.19 and 0.75±0.19,respectively)(P<0.05).CONCLUSION Combined molybdenum target X-ray and MRI examinations for diagnosing breast cancer improved the diagnostic sensitivity and accuracy,minimizing the missedand misdiagnoses risks and promoting timely treatment intervention.

Breast Tumor Computer-Aided Detection System Based on Magnetic Resonance Imaging Using Convolutional Neural Network

Background:The main cause of breast cancer is the deterioration of malignant tumor cells in breast tissue.Early diagnosis of tumors has become the most effective way to prevent breast cancer.Method:For distinguishing between tumor and non-tumor in MRI,a new type of computer-aided detection CAD system for breast tumors is designed in this paper.The CAD system was constructed using three networks,namely,the VGG16,Inception V3,and ResNet50.Then,the influence of the convolutional neural network second migration on the experimental results was further explored in the VGG16 system.Result:CAD system built based on VGG16,Inception V3,and ResNet50 has higher performance than mainstream CAD systems.Among them,the system built based on VGG16 and ResNet50 has outstanding performance.We further explore the impact of the secondary migration on the experimental results in the VGG16 system,and these results show that the migration can improve system performance of the proposed framework.Conclusion:The accuracy of CNN represented by VGG16 is as high as 91.25%,which is more accurate than traditional machine learningmodels.The F1 score of the three basic networks that join the secondary migration is close to 1.0,and the performance of the VGG16-based breast tumor CAD system is higher than Inception V3,and ResNet50.

3.0 Tesla vs 1.5 Tesla breast magnetic resonance imaging in newly diagnosed breast cancer patients

AIM:To compare 3.0 Tesla(T) vs 1.5T magnetic resonance(MR) imaging systems in newly diagnosed breast cancer patients.METHODS:Upon Institutional Review Board approval,a Health Insurance Portability and Accountability Actcompliant retrospective review of 147 consecutive 3.0T MR examinations and 98 consecutive 1.5T MR examinations in patients with newly diagnosed breast cancer between 7/2009 and 5/2010 was performed.Eleven patients who underwent neoadjuvant chemotherapy in the 3.0T group were excluded.Mammographically occult suspicious lesions(BIRADS Code 4 and 5) additional to the index cancer in the ipsilateral and contralateral breast were identified.Lesion characteristics and pathologic diagnoses were recorded,and results achieved with both systems compared.Statistical significance was analyzed using Fisher’s exact test.RESULTS:In the 3.0T group,206 suspicious lesions were identified in 55%(75/136) of patients and 96%(198/206) of these lesions were biopsied.In the 1.5T group,98 suspicious lesions were identified in 53%(52/98) of patients and 90%(88/98) of these lesions were biopsied.Biopsy results yielded additional malignancies in 24% of patients in the 3.0T group vs 14% of patients in the 1.5T group(33/136 vs 14/98,P = 0.07).Average size and histology of the additional cancers was comparable.Of patients who had a suspicious MR imaging study,additional cancers were found in 44% of patients in the 3.0T group vs 27% in the 1.5T group(33/75 vs 14/52,P = 0.06),yielding a higher positive predictive value(PPV) for biopsies performed with the 3.0T system.CONCLUSION:3.0T MR imaging detected more additional malignancies in patients with newly diagnosed breast cancer and yielded a higher PPV for biopsies performed with the 3.0T system.

Application of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)combined with magnetic resonance spectroscopy(MRS)in prostate cancer diagnosis

Objective The aim of the study was to investigate the application of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)combined with magnetic resonance spectroscopy(MRS)in prostate cancer diagnosis.Methods In the outpatient department of our hospital(Sichuan Cancer Hospital,Chengdu,China),60 patients diagnosed with prostate disease were selected randomly and included in a prostate cancer group,60 patients with benign prostatic hyperplasia were included in a proliferation group,and 60 healthy subjects were included in a control group,from January 2013 to January 2017.Using Siemens Avanto 1.5 T high-field superconducting MRI for DCE-MRI and MRS scans,after the MRS scan was completed,we used the workstation spectroscopy tab spectral analysis,and eventually obtained the crest lines of the prostate metabolites choline(Cho),creatine(Cr),citrate(Cit),and the values of Cho/Cit,and(Cho+Cr)/Cit.Results Participants who had undergone 21-s,1-min,and 2-min dynamic contrast-enhanced MR revealed significant variations among the three groups.The spectral analysis of the three groups revealed a significant variation as well.DCE-MRI and MRS combined had a sensitivity of 89.67%,specificity of 95.78%,and accuracy of 94.34%.Conclusion DCE-MRI combined with MRS is of great value in the diagnosis of prostate cancer.

Generalized Nonconvex Low-Rank Algorithm for Magnetic Resonance Imaging (MRI) Reconstruction

In recent years,utilizing the low-rank prior information to construct a signal from a small amount of measures has attracted much attention.In this paper,a generalized nonconvex low-rank(GNLR) algorithm for magnetic resonance imaging(MRI)reconstruction is proposed,which reconstructs the image from highly under-sampled k-space data.In the algorithm,the nonconvex surrogate function replacing the conventional nuclear norm is utilized to enhance the low-rank property inherent in the reconstructed image.An alternative direction multiplier method(ADMM) is applied to solving the resulting non-convex model.Extensive experimental results have demonstrated that the proposed method can consistently recover MRIs efficiently,and outperforms the current state-of-the-art approaches in terms of higher peak signal-to-noise ratio(PSNR) and lower high-frequency error norm(HFEN) values.

Value of magnetic resonance diffusion combined with perfusion imaging techniques for diagnosing potentially malignant breast lesions

BACKGROUND Lesions of breast imaging reporting and data system(BI-RADS)4 at mammography vary from benign to malignant,leading to difficulties for clinicians to distinguish between them.The specificity of magnetic resonance imaging(MRI)in detecting breast is relatively low,leading to many false-positive results and high rates of re-examination or biopsy.Diffusion-weighted imaging(DWI),combined with perfusion-weighted imaging(PWI),might help to distinguish between benign and malignant BI-RADS 4 breast lesions at mammography.AIM To evaluate the value of DWI and PWI in diagnosing BI-RADS 4 breast lesions.METHODS This is a retrospective study which included patients who underwent breast MRI between May 2017 and May 2019 in the hospital.The lesions were divided into benign and malignant groups according to the classification of histopathological results.The diagnostic efficacy of DWI and PWI were analyzed respectively and combinedly.The 95 lesions were divided according to histopathological diagnosis,with 46 benign and 49 malignant.The main statistical methods used included the Student t-test,the Mann-Whitney U-test,the chi-square test or Fisher’s exact test.RESULTS The mean apparent diffusion coefficient(ADC)values in the parenchyma and lesion area of the normal mammary gland were 1.82±0.22×10^(-3)mm^(2)/s and 1.24±0.16×10^(-3)mm^(2)/s,respectively(P=0.021).The mean ADC value of the malignant group was 1.09±0.23×10^(-3)mm^(2)/s,which was lower than that of the benign group(1.42±0.68×10^(-3)mm^(2)/s)(P=0.016).The volume transfer constant(Ktrans)and rate constant(Kep)values were higher in malignant lesions than in benign ones(all P<0.001),but there were no significant statistical differences regarding volume fraction(V_(e))(P=0.866).The sensitivity and specificity of PWI combined with DWI(91.7%and 89.3%,respectively)were higher than that of PWI or DWI alone.The accuracy of PWI combined with DWI in predicting pathological results was significantly higher than that predicted by PWI or DWI alone.CONCLUSION DWI,combined with PWI,might possibly distinguish between benign and malignant BI-RADS 4 breast lesions at mammography.

The accuracy of magnetic resonance imaging and ultrasound in evaluating the size of early-stage breast neoplasms

Objective Breast cancer is the most frequently diagnosed cancer in women. Accurate evaluation of the size and extent of the tumor is crucial in selecting a suitable surgical method for patients with breast cancer. Both overestimation and underestimation have important adverse effects on patient care. This study aimed to evaluate the accuracy of breast magnetic resonance imaging(MRI) and ultrasound(US) examination for measuring the size and extent of early-stage breast neoplasms.Methods The longest diameter of breast tumors in patients with T_(1–2)N_(0–1)M_0 invasive breast cancer preparing for breast-conserving surgery(BCS) was measured preoperatively by using both MRI and US and their accuracy was compared with that of postoperative pathologic examination. If the diameter difference was within 2 mm, it was considered to be consistent with pathologic examination.Results A total of 36 patients were imaged using both MRI and US. The mean longest diameter of the tumors on MRI, US, and postoperative pathologic examination was 20.86 mm ± 4.09 mm(range: 11–27 mm), 16.14 mm ± 4.91 mm(range: 6–26 mm), and 18.36 mm ± 3.88 mm(range: 9–24 mm). US examination underestimated the size of the tumor compared to that determined using pathologic examination(t = 3.49, P < 0.01), while MRI overestimated it(t =-6.35, P < 0.01). The linear correlation coefficients between the image measurements and pathologic tumor size were r = 0.826(P < 0.01) for MRI and r = 0.645(P < 0.01) for US. The rate of consistency of MRI and US compared to that with pathologic examination was 88.89% and 80.65%, respectively, and there was no statistically significant difference between them(χ~2 = 0.80, P > 0.05).Conclusion MRI and US are both effective methods to assess the size of breast tumors, and they maintain good consistency with pathologic examination. MRI has a better correlation with pathology. However, we should be careful about the risk of inaccurate size estimation.

Obstacles Facing the Implementation of Functional Magnetic Resonance Imaging （fMRI） of Brain in Jeddah City

fMRI （Functional Magnetic Resonance Imaging） is a relatively new technique that uses MRI （Magnetic Resonance Imaging） to measure the hemodynamic response （change in blood flow） related to neural activity in the brain. This paper aims to explore and identify the obstacles facing the implementation and applications of IMRI in radiology departments within Jeddah city by analyzing related data received by direct questionnaires and interviews with all the people working in MRI units in Jeddah city and finds that the major obstacle is lacking of awareness of fMRI among medical professionals and their training.

Progresses of Functional Magnetic Resonance Imaging Diagnosis in Breast Cancer

Breast cancer is the most common malignant tumor that threatens women’s health. Breast magnetic resonance imaging (MRI) is a commonly used method recommended for the diagnosis of breast cancer. Diffusion weighted imaging (DWI) and dynamic enhanced magnetic resonance imaging (DCE-MRI) are now widely used. At present, with the continuous advancement of magnetic resonance technology, Magnetic resonance spectroscopy (MRS), Perfusion weighted imaging (PWI), Positron emission tomography-magnetic resonance imaging (PET-MRI) and so on are gradually being used in clinical practice. Mammography imaging and imaging genomics are hot topics. This article will briefly introduce several functional magnetic resonance techniques and their latest applications.

Breast dynamic contrast-enhanced-magnetic resonance imaging and radiomics:State of art

Breast cancer represents the most common malignancy in women,being one of the most frequent cause of cancer-related mortality.Ultrasound,mammography,and magnetic resonance imaging(MRI)play a pivotal role in the diagnosis of breast lesions,with different levels of accuracy.Particularly,dynamic contrastenhanced MRI has shown high diagnostic value in detecting multifocal,multicentric,or contralateral breast cancers.Radiomics is emerging as a promising tool for quantitative tumor evaluation,allowing the extraction of additional quantitative data from radiological imaging acquired with different modalities.Radiomics analysis may provide novel information through the quantification of lesions heterogeneity,that may be relevant in clinical practice for the characterization of breast lesions,prediction of tumor response to systemic therapies and evaluation of prognosis in patients with breast cancers.Several published studies have explored the value of radiomics with good-to-excellent diagnostic and prognostic performances for the evaluation of breast lesions.Particularly,the integrations of radiomics data with other clinical and histopathological parameters have demonstrated to improve the prediction of tumor aggressiveness with high accuracy and provided precise models that will help to guide clinical decisions and patients management.The purpose of this article in to describe the current application of radiomics in breast dynamic contrast-enhanced MRI.

Current and future applications of magnetic resonance imaging and spectroscopy of the brain in hepatic encepha-lopathy

Hepatic encephalopathy （HE） is a common neuropsychiatric abnormality, which complicates the course of patients with liver disease and results from hepatocellular failure and/or portosystemic shunting. The manifestations of HE are widely variable and involve a spectrum from mild subclinical disturbance to deep coma. Research interest has focused on the role of circulating gut-derived toxins, particularly ammonia, the development of brain swelling and changes in cerebral neurotransmitter systems that lead to global CNS depression and disordered function. Until recently the direct investigation of cerebral function has been difficult in man. However, new magnetic resonance imaging （MRI） techniques provide a non-invasive means of assessment of changes in brain volume （coregistered MRI） and impaired brain function （fMRI）, while proton magnetic resonance spectroscopy （^1H MRS） detects changes in brain biochemistry, including direct measurement of cerebral osmolytes, such as myoinositol, glutamate and glutamine which govern processes intrinsic to cellular homeostasis, including the accumulation of intracellular water. The concentrations of these intracellular osmolytes alter with hyperammonaemia. MRS-detected metabolite abnormalities correlate with the severity of neuropsychiatric impairment and since MR spectra return towards normal after treatment, the technique may be of use in objective patient monitoring and in assessing the effectiveness of various treatment regimens.

Targeted prostate biopsy： value of multiparametric magnetic resonance imaging in detection of localized cancer

Prostate cancer is the second most common cancer in men, with 1.1 million new cases worldwide reported by the World Health Organization in one recent year. Transrectal ultrasound （TRUS）-guided biopsy has been used for the diagnosis of prostate cancer for over 2 decades, but the technique is usually blind to cancer location. Moreover, the false negative rate of TRUS biopsy has been reported to be as high as 47%. Multiparametric magnetic resonance imaging （mp-MRI） includes T1- and T2-weighted imaging as well as dynamic contrast-enhanced （DCE） and diffusion-weighted imaging （DWI）. mp-MRI is a major advance in the imaging of prostate cancer, enabling targeted biopsy of suspicious lesions. Evolving targeted biopsy techniquesmincluding direct in-bore biopsy, cognitive fusion and software-based MRI-ultrasound （MRI-US） fusion--have led to a several-fold improvement in cancer detection compared to the earlier method. Importantly, the detection of clinically significant cancers has been greatly facilitated by targeting, compared to systematic biopsy alone. Targeted biopsy via MRI-US fusion may dramatically alter the way prostate cancer is diagnosed and managed.

Magnetic resonance imaging for prostate cancer clinical application

As prostate cancer is a biologically heterogeneous disease for which a variety of treatment options are available, the major objective of prostate cancer imaging is to achieve more precise disease characterization. In clinical practice, magnetic resonance imaging （MRI） is one of the imaging tools for the evaluation of prostate cancer, the fusion of MRI or dynamic contrast-enhanced MRI （DCE-MRI） with magnetic resonance spectroscopic imaging （MRSI） is improving the evaluation of cancer locafon, size, and extent, while providing an indication of tumor aggressiveness. This review summarizes the role of MRI in the application of prostate cancer and describes molecular MRI techniques （including MRSI and DCE-MRI） for aiding prostate cancer management.

Nasopharyngeal adenoid cystic carcinoma: magnetic resonance imaging features in ten cases

Nasopharyngeal adenoid cystic carcinoma (NACC) is a rare malignancy with high local invasiveness. To date, there is no consensus on the imaging characteristics of NACC. To address this, we retrospectively reviewed 10 cases of NACC and summarized the magnetic resonance imaging (MRI) features. MR images of 10 patients with histologically validated NACC were reviewed by two experienced radiologists. The location, shape, margin, signal intensity, lesion texture, contrast enhancement patterns, local invasion, and cervical lymphadenopathy of all tumors were evaluated. Clinical and pathologic records were also reviewed. No patients were positive for antibodies against Epstein-Barr virus (EBV). The imaging patterns of primary tumors were classified into two types as determined by location, shape, and margin. Of all patients, 7 had tumors with a type 1 imaging pattern and 3 had tumors with a type 2 imaging pattern. The 4 tubular NACCs were all homogeneous tumors, whereas 3 (60%) of 5 cribriform NACCs and the sole solid NACC were heterogeneous tumors with separations or central necrosis on MR images. Five patients had perineural infiltration and intracranial involvement, and only 2 had cervical lymphadenopathy. Based on these results, we conclude that NACC is a local, aggressive neoplasm that is often negative for EBV infection and associated with a low incidence of cervical lymphadenopathy. Furthermore, MRI features of NACC vary in locations and histological subtypes.

Magnetic resonance image-guided versus ultrasound-guided high-intensity focused ultrasound in the treatment of breast cancer

Image-guided high-intensity focused ultrasound (HIFU) has been used for more than ten years, primarily in the treatment of liver and prostate cancers. HIFU has the advantages of precise cancer ablation and excellent protection of healthy tissue. Breast cancer is a common cancer in women. HIFU therapy, in combination with other therapies, has the potential to improve both oncologic and cosmetic outcomes for breast cancer patients by providing a curative therapy that conserves mammary shape. Currently, HIFU therapy is not commonly used in breast cancer treatment, and efforts to promote the application of HIFU is expected. In this article, we compare different image-guided models for HIFU and reviewed the status, drawbacks, and potential of HIFU therapy for breast cancer.