Search Results (126)

Objective: This study aims to engineer a novel nanoparticle formulation for combined tumor therapy, designated as PDA@Mn-siSur-c-NPs, which comprises a polydopamine/manganese dioxide (PDA@MnO₂) core alongside survivin-targeting siRNA and cyclo(RGD-DPhe-K)-targeting moiety. Methods: The PDA@Mn-siSur-c-NPs were constructed and subjected to detailed characterization. Inductively coupled plasma optical emission spectroscopy (ICP-OES) was employed to quantify manganese content. To assess siRNA stability within the system, samples were incubated with 50% fetal bovine serum (FBS) before agarose gel electrophoresis analysis. Additionally, cellular internalization by 4T1 cells and in vitro photothermal conversion efficiency of the formulation were evaluated. ICP-OES was further utilized to investigate the in vivo pharmacokinetics and tissue distribution of manganese. Animal model studies were conducted to assess the anti-breast cancer efficacy of PDA@Mn-siSur-c-NPs in combination with infrared irradiation. Results: The newly developed PDA@Mn-siSur-c-NPs demonstrated superior siRNA protection, reduced toxicity, and high photothermal conversion capacity. When combined with photothermal therapy (PTT), these nanoparticles exerted enhanced synergistic anti-tumor effects. Delivery of survivin siRNA resulted in a significant downregulation of survivin protein expression in tumor tissues. Moreover, magnetic resonance imaging (MRI) confirmed that the nanoparticles possess favorable imaging properties. Conclusions: This research demonstrates that the integration of PDA@Mn-siSur-c-NPs with PTT holds considerable therapeutic promise for improved breast cancer treatment. Full article

Background: With the rising incidence of cancer, there is a growing need for improved preclinical models to test new therapies. While patient-derived xenografts (PDX) in immunodeficient mice are the gold standard, they are costly and result in a complete absence of a functional immune system, limiting their utility for studying tumor–immune interactions. This study characterizes a pharmacological partial immunosuppression protocol in immunocompetent mice as a promising alternative, evaluating its impact on the immune system and demonstrating its efficacy for growing human tumor xenografts. Methods: Mice received a regimen of cyclosporine (20 mg/kg, i.p., every 48 h for 12 days), cyclophosphamide (60 mg/kg, i.p., every 48 h for 8 days), and ketoconazole (10 mg/kg, p.o., for 12 days). The dynamics of CD3⁺, CD4⁺, CD8⁺, and CD19⁺ lymphocyte subpopulations and the CD4/CD8 index were monitored via flow cytometry on days 1, 5, 8, 12, 16, and 21. The protocol’s utility was tested by orthotopic transplantation of human glioma and lung cancer cells, and subcutaneous transplantation of breast cancer cells (MCF7). Tumor engraftment and growth were assessed using in vivo microscopy, MRI, and histology. Results: The immunosuppressive protocol induced a significant but partial reduction in CD3⁺ T-cells and CD19⁺ B-cells by day 8 (p = 0.0277). A profound and progressive decrease in the CD4/CD8 index was observed, indicating a shift towards immunosuppression. Crucially, CD8⁺ and CD4⁺ T-cells populations recovered rapidly post-therapy, demonstrating that the protocol creates a temporary and modifiable immune window rather than inducing complete ablation. The protocol enabled successful engraftment and growth of all three tested tumors in a residual immune microenvironment, confirmed by in vivo imaging and histopathological analysis. Conclusions: This drug-induced partial immunosuppression protocol effectively creates a reproducible state of transient immunodeficiency in outbred mice, suitable for various human tumor xenograft models. It represents a cost-effective and flexible alternative to genetic models, with the distinct advantage of preserving a residual immune microenvironment, making it particularly valuable for preclinical studies that require a partially intact host immune system. Full article

Background/Objectives: To identify preoperative MRI features using computer-assisted diagnosis (CAD) that are associated with invasive disease-free survival (IDFS) and distant metastasis-free survival (DDFS) in patients with primarily operable triple-negative breast cancer (TNBC). Methods: This retrospective study was approved by the institutional review board with informed consent was waived. Between January 2012 and December 2014, 74 consecutive women with primary TNBC (mean age, 51 years; range, 29–77 years) who underwent preoperative MRI were included and followed until August 2021. Dynamic contrast-enhanced and T2-weighted images were obtained using 3T scanners. Peritumoral edema and central necrosis were evaluated retrospectively. CAD was used to extract 3D diameters, angiovolume, and kinetic parameters, and kinetic heterogeneity was calculated. Cox proportional hazards models were used to assess associations between MRI features and IDFS and DDFS, adjusting for clinicopathologic factors. Results: During a median follow-up of 80.9 months, 12 patients developed invasive disease, and 8 developed distant metastasis. In multivariable analysis, peak enhancement (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.06–1.84; p = 0.019) and angiovolume (HR, 2.86; 95% CI, 1.26–6.47; p = 0.012) were independently associated with IDFS, whereas angiovolume (HR, 2.47; 95% CI: 1.28–4.78; p = 0.007) was independently associated with DDFS. Conclusions: Preoperative CAD-derived MRI features, particularly peak enhancement and angiovolume, were associated with IDFS in TNBC patients whereas angiovolume alone was associated with DDFS. Full article

Background/Objectives: Segmental non-mass enhancement (NME) is the breast MRI distribution pattern with the highest positive predictive value (PPV) for malignancy. Despite its diagnostic relevance, its imaging characteristics have rarely been examined in isolation, leaving uncertainty in clinical practice. This multicenter retrospective cohort study aimed to evaluate multiparametric MRI features—including internal enhancement pattern, dynamic contrast-enhanced (DCE) kinetics, and diffusion restriction—in segmental NME to identify malignancy predictors. Methods: This retrospective cohort review included 14,834 breast MRI reports from five institutions (September 2017–February 2024), identifying 103 women (mean age, 44.4 ± 9.9 years) with segmental NME (70 malignant, 33 benign). MRI was performed at 1.5 T or 3 T using standardized protocols. Two breast radiologists, blinded to pathology, assessed internal enhancement, DCE kinetics, diffusion restriction, and short tau inversion recovery (STIR) features according to BI-RADS. Statistical analyses included chi-square/Fisher’s tests and logistic regression. Results: Clustered ring enhancement (CRE) was significantly associated with malignancy (p = 0.004). Fast initial-phase enhancement (p < 0.001) and delayed-phase washout (p = 0.011) also correlated with malignancy. On multivariate analysis, fast initial-phase enhancement remained an independent predictor (odds ratio [OR] = 5.133, p = 0.031), whereas slow enhancement predicted benignity (OR = 0.194, p = 0.020). Histologies included ductal carcinoma in situ, invasive ductal carcinoma, granulomatous mastitis, and benign hyperplastic lesions. Conclusions: This study, focusing exclusively on segmental NME, identifies CRE, fast initial-phase enhancement, and washout kinetics as reliable imaging biomarkers. Incorporating these features into breast MRI interpretation may improve diagnostic accuracy, risk stratification, and management decisions. Full article

Background: Preoperative breast MRI is widely used in surgical planning because of its high sensitivity. However, discrepancies with histopathology remain common and can affect tumor size assessment and treatment decisions. In addition, recent comparative studies have highlighted the growing role of contrast-enhanced mammography (CEM) and multiparametric MRI (mpMRI), both of which may improve specificity and accessibility compared to conventional MRI. Methods: A structured literature review was conducted in PubMed (2000–2025) according to PRISMA guidelines. Studies included if they evaluated preoperative breast MRI with histopathological correlation and reported sensitivity, specificity, or concordance outcomes. Data extraction focused on study design, patient and tumor characteristics, imaging methods, and clinical impact. Results: MRI demonstrates high sensitivity, particularly in detecting IDC and ILC. However, overestimation of tumor size remains a concern, particularly in ILC and high-grade DCIS, while underestimation is frequently observed after neoadjuvant therapy, especially in Luminal A tumors. Tumor size and stage significantly affect concordance, with advanced-stage tumors (T2–T3) showing better MRI-histopathology concordance than early-stage lesions (T0–T1). Specificity remains limited, particularly in DCIS and multifocal disease. Emerging evidence suggests that contrast-enhanced mammography (CEM) achieves comparable sensitivity with higher specificity, while multiparametric MRI (mpMRI) incorporating diffusion-weighted imaging (DWI) improves lesion characterization and prediction of treatment response. Conclusions: While MRI remains a valuable diagnostic tool for breast cancer, histopathological validation is essential to guide treatment decisions. Future research should focus on AI-enhanced imaging techniques, CEM and multiparametric MRI to improve concordance rates, reduce overdiagnosis and translate imaging advances into meaningful clinical outcomes. Full article

Background: Neoadjuvant systemic therapy (NST), whose primary purposes include response assessment and treatment individualization, is a key strategy in the treatment of HER2-positive breast cancer. This study investigated the predictive value of the magnetic resonance imaging (MRI)-derived tumor volume reduction rate (δV1) for the early identification of pathological complete response (pCR) during NST and established clinically applicable δV1 thresholds for patient stratification. Methods: HER2-positive breast cancer patients who received THP (taxane, trastuzumab, pertuzumab) followed by epirubicin/cyclophosphamide (EC) were enrolled. MRI was performed at baseline, after THP, and after EC. Tumor volumes were manually segmented using 3D Slicer, and δV1/δV2 were calculated via Python (version3.13). Longest diameter reduction rates (δL1/δL2) were recorded. pCR (ypT0/is ypN0) was the primary endpoint. Receiver operating characteristic (ROC) analysis determined predictive accuracy, and logistic regression identified independent predictors. Thresholds for δV1 were explored, and subgroup analyses were conducted by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. Results: Overall, 59.3% of patients achieved pCR. δV1 demonstrated superior predictive accuracy compared with longest diameter reduction (δL1), with an AUC of 0.745 (95% CI: 0.642–0.847) vs. 0.634 (95% CI: 0.512–0.757). A δV1 cutoff of 0.85 discriminated responders (68.4% vs. 41.4%, p = 0.016), while one of 0.91 represented the optimal predictive threshold. In multivariate analysis, δV1 was independently associated with pCR (OR = 1227.1, 95% CI: 6.86–219,562; p = 0.007), along with HER2 3+ expression (OR = 4.24, 95% CI: 1.26–14.31; p = 0.020). Among HR-positive patients, δV1 < 0.93 identified a subgroup with significantly lower pCR rates (19.0% vs. 81.0%, p < 0.001). Conclusions: δV1 is a reliable and early MRI-based imaging biomarker for predicting pCR in HER2-positive breast cancer. Defining thresholds such as 0.85 and 0.91 supports early therapeutic stratification and may help identify patients who could benefit from anthracycline-containing regimens. Full article

Background/Objectives: This study aimed to investigate the preoperative clinicopathologic and imaging features associated with subsequent breast cancer events detected on postoperative abbreviated MRI in early-stage breast cancer patients following breast and axillary surgery. Methods: A retrospective analysis was conducted on 1171 patients (median age, 53 years; range, 24–90 years) diagnosed with clinical stage I or II breast cancer between January 2013 and December 2017. Logistic regression analysis was used to evaluate preoperative imaging features—including breast density assessed on mammography and MRI descriptors—along with clinicopathologic characteristics, to identify factors independently associated with subsequent breast cancer events during abbreviated MRI screening. Results: Among the patients, 57 (4.9%) experienced subsequent breast cancer events at a median follow-up of 74 months. In the multivariable analysis, high nuclear grade (odds ratio [OR] = 2.821; 95% confidence interval [CI], 1.427–5.577; p = 0.003), dense breast tissue on mammography (OR = 4.680; 95% CI, 1.113–19.684; p = 0.035), and absence of heterogeneous internal enhancement on preoperative MRI (OR = 0.429; 95% CI, 0.206–0.891; p = 0.023) were independently associated with subsequent breast cancer events detected using an abbreviated breast MRI protocol. Age ≥ 40 years (OR = 0.448; 95% CI, 0.193–1.039; p = 0.061) and clinical T2 stage (OR = 1.744; 95% CI, 0.969–3.139; p = 0.064) showed borderline significance. Conclusions: High nuclear grade, dense breast tissue on mammography, and absence of heterogeneous internal enhancement on preoperative MRI were associated with an increased risk of subsequent breast cancer events in patients undergoing abbreviated MRI surveillance following surgery for early-stage breast cancer. Full article

Introduction: Ductal carcinoma in situ (DCIS) is a non-invasive precursor of breast cancer, usually detected on mammography as clustered microcalcifications. Many cases, however, lack calcifications and require complementary imaging. This study aimed to describe the multimodal imaging features of DCIS and evaluate the radiology–pathology correlation. Methods: We retrospectively reviewed 75 women (aged 36–52 years) with biopsy-proven DCIS (January 2023–June 2025). All underwent mammography, targeted ultrasound, and dynamic contrast-enhanced 1.5T MRI. Imaging findings were correlated with histopathology, and logistic regression was used to explore predictors of MRI kinetics. Results: Mammography detected microcalcifications in 53.8% of patients, while 46.2% showed no calcifications. Ultrasound frequently revealed non-mass, duct-oriented hypoechoic abnormalities in non-calcified cases. MRI consistently demonstrated non-mass enhancement, with weak or persistent kinetics without washout in 69.2% and washout in 30.8%. A moderate correlation between MRI and histological extent was found (r = 0.62, p < 0.001), with MRI tending to overestimate lesion size. Oral contraceptive use was common (61.5%) but not significantly associated with kinetic pattern or grade. Conclusions: Mammography remains essential for calcified DCIS, whereas MRI enhances detection of non-calcified lesions. Persistent kinetics without washout may represent a typical imaging feature of DCIS. However, moderate radiology–pathology concordance and frequent overestimation highlight the need for careful interpretation. These findings support a multimodal diagnostic approach that can improve detection accuracy and assist in more tailored surgical planning. Full article

Background: This study aimed to explore the application value of magnetic resonance imaging (MRI)-based three-dimensional segmentation and reconstruction technology for spatial structural identification and volumetric quantification of glandular and adipose tissues in bilateral gynecomastia (GM) patients undergoing surgical treatment, hoping to provide precise imaging data to support clinical surgical decision-making. Methods: A retrospective analysis was performed on preoperative MRI images and general clinical data of 52 patients with bilateral gynecomastia at the patient level (bilateral totals, N = 52) who underwent surgical treatment in the Department of Aesthetic and Reconstructive Breast Surgery, Plastic Surgery Hospital of Chinese Academy of Medical Sciences, from March 2023 to September 2024. All images were acquired using a SIEMENS Aera 1.5 T MRI scanner with T1-weighted three-dimensional fat-suppressed sequence (t1_fl3d_tra_spair). Semi-automatic segmentation and active contour modeling (Snake model) using ITK-SNAP 4.0 software were employed to independently identify glandular and adipose tissues, reconstruct accurate three-dimensional anatomical models, and quantitatively analyze tissue volumes. Results: The MRI-based three-dimensional segmentation and reconstruction method accurately distinguished glandular and adipose tissues in male breasts, establishing precise three-dimensional anatomical models with excellent reproducibility and operational consistency. Among the 52 patients with bilateral gynecomastia, glandular tissue volume exhibited a markedly non-normal distribution, with a median of 6.11 cm³ (IQR, 3.03–12.98 cm³). Adipose tissue volume followed a normal distribution with a mean of 1348.84 ± 494.97 cm³. The total breast tissue volume also showed a normal distribution, with a mean of 1361.97 ± 496.83 cm³. The proportion of glandular tissue in total breast volume was non-normally distributed with a median of 0.50% (IQR, 0.27–1.21%), while the proportion of adipose tissue was also non-normally distributed with a median of 99.50% (IQR, 98.79–99.73%). Conclusions: MRI combined with computer-assisted three-dimensional segmentation and reconstruction technology efficiently and accurately achieves spatial identification, three-dimensional modeling, and volumetric quantification of glandular and adipose tissues in patients with bilateral gynecomastia. It objectively reveals the spatial compositional characteristics of male breast tissues. This approach provides precise, quantitative data for clinical decision-making regarding surgical treatment of gynecomastia, featuring robust standardization and strong clinical applicability. Full article

Background: Breast cancer is the most common cancer diagnosis and the second leading cause of cancer-related death in women. Breast cancer is a major health burden worldwide. Advances in breast cancer detection and treatment have contributed to improving the rate of survival, although mortality rates remain significantly high. Despite all these advances, more efficient diagnostic methods and effective treatments are necessary. Colchicine is a natural alkaloid with strong antimitotic activity, but its potential effects on extracellular matrix components in cancer remain poorly understood. Objective: This study aimed to investigate the influence of colchicine on glycosaminoglycan (GAG) concentrations and cell viability in MCF-7 breast cancer cells cultured in a three-dimensional (3D) hollow fiber bioreactor system. Methods: Magnetic resonance imaging (MRI) was applied as a non-invasive technique to quantify GAG levels through fixed charge density (FCD) and T₁ relaxation mapping. MCF-7 HER-2-overexpressing and HER-2-negative cells were treated with 1000 nM colchicine for 72 h, and cell viability was assessed in parallel with GAG measurements. Results: Colchicine significantly reduced cell viability and altered GAG concentrations. HER-2-overexpressing MCF-7 cells exhibited higher baseline GAG levels than HER-2-negative controls, and colchicine decreased the GAG content in both lines. Conclusions: Colchicine reduces viability and modifies GAG concentrations in 3D cultures of MCF-7 cells. The use of MRI provides a reproducible, non-destructive tool for monitoring extracellular matrix changes, offering a novel methodological approach for studying drug effects in physiologically relevant cancer models. Full article

Background: Response to neoadjuvant chemotherapy (NAC) is a key prognostic indicator in breast cancer, yet current assessment relies on postoperative pathology. This study investigated the use of deep features derived from pre-treatment MRI and CT scans, in conjunction with clinical variables, to predict treatment response a priori. Methods: Two response endpoints were analyzed: pathologic complete response (pCR) versus non-pCR, and responders versus non-responders, with response defined as a reduction in tumor size of at least 30%. Intratumoral and peritumoral segmentations were generated on contrast-enhanced T1-weighted (CE-T1) and T2-weighted MRI, as well as contrast-enhanced CT images of tumors. Deep features were extracted from these regions using ResNet10, ResNet18, ResNet34, and ResNet50 architectures pre-trained with MedicalNet. Handcrafted radiomic features were also extracted for comparison. Feature selection was conducted with minimum redundancy maximum relevance (mRMR) followed by recursive feature elimination (RFE), and classification was performed using XGBoost across ten independent data partitions. Results: A total of 177 patients were analyzed in this study. ResNet34-derived features achieved the highest overall classification performance under both criteria, outperforming handcrafted features and deep features from other ResNet architectures. For distinguishing pCR from non-pCR, ResNet34 achieved a balanced accuracy of 81.6%, whereas handcrafted radiomics achieved 77.9%. For distinguishing responders from non-responders, ResNet34 achieved a balanced accuracy of 73.5%, compared with 70.2% for handcrafted radiomics. Conclusions: Deep features extracted from routinely acquired MRI and CT, when combined with clinical information, improve the prediction of NAC response in breast cancer. This multimodal framework demonstrates the value of deep learning-based approaches as a complement to handcrafted radiomics and provides a basis for more individualized treatment strategies. Full article

Objective: Axillary lymph node (ALN) status in breast cancer is pivotal for guiding treatment and determining prognosis. The study aimed to explore the feasibility and efficacy of a radiomics model using voxel-wise dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) time-intensity-curve (TIC) profile maps to predict ALN metastasis in breast cancer. Methods: A total of 615 breast cancer patients who underwent preoperative DCE-MRI from October 2018 to February 2024 were retrospectively enrolled and randomly allocated into training (n = 430) and testing (n = 185) sets (7:3 ratio). Based on wash-in rate, wash-out enhancement, and wash-out stability, each voxel within manually segmented 3D lesions that were categorized into 1 of 19 TIC subtypes from the DCE-MRI images. Three feature sets were derived: composition ratio (type-19), radiomics features of TIC subtypes (type-19-radiomics), and radiomics features of third-phase DCE-MRI (phase-3-radiomics). Student’s t-test and the least absolute shrinkage and selection operator (LASSO) was used to select features. Four models (type-19, type-19-radiomics, type-19-combined, and phase-3-radiomics) were constructed by a support vector machine (SVM) to predict ALN status. Model performance was assessed using sensitivity, specificity, accuracy, F1 score, and area under the curve (AUC). Results: The type-19-combined model significantly outperformed the phase-3-radiomics model (AUC = 0.779 vs. 0.698, p < 0.001; 0.674 vs. 0.559) and the type-19 model (AUC = 0.779 vs. 0.541, p < 0.001; 0.674 vs. 0.435, p < 0.001) in cross-validation and independent testing sets. The type-19-radiomics showed significantly better performance than the phase-3-radiomics model (AUC = 0.764 vs. 0.698, p = 0.002; 0.657 vs. 0.559, p = 0.037) and type-19 model (AUC = 0. 764 vs. 0.541, p < 0.001; 0.657 vs. 0.435, p < 0.001) in cross-validation and independent testing sets. Among four models, the type-19-combined model achieved the highest AUC (0.779, 0.674) in cross-validation and testing sets. Conclusions: Radiomics analysis of voxel-wise DCE-MRI TIC profile maps, simultaneously quantifying temporal and spatial hemodynamic heterogeneity, provides an effective, noninvasive method for predicting ALN metastasis in breast cancer. Full article

Background/Objectives: Tumor growth delay is frequently used in preclinical experiments evaluating oncologic interventions. While treatment response in humans is based on imaging criteria for obvious reasons, manual caliper measurement of subcutaneous tumors is standard in animal studies. In a murine tumor model treated with immunotherapy (ImT) and radiotherapy (RT), the reliability of caliper measurements was tested by comparing normalized tumor growth delay (NTGD) rates derived from caliper- and image-based volumetrics. Methods: A 4T1 breast syngeneic murine model was used, in which thirty animals were inoculated in the right inguinal mammary fat pad and the right axilla. One RT fraction of 8 Gy was delivered to the right inguinal tumor on day 11 post-implant, and intraperitoneal ImT (PD-1 checkpoint inhibitor) injections were administered on days 11, 12, and 14. Each animal underwent three MRI scans (days 10, 17, and 20). Caliper measurements were also performed by two independent observers on the same days. The measurements were averaged and used to estimate ellipsoid tumor volumes. The acquired MRIs were used for image segmentation and volume estimation. Tumor volumes (days 17 and 20) were normalized against the baseline pre-treatment tumor volume (day 10). NTGD rates derived from hand- and image-based volumetrics were compared to assess the reliability of caliper vs. MRI estimation. Results: Caliper volumes between the two observers correlated at 0.799 (Pearson, p < 0.001). The averaged caliper volumes correlated with MRI volumes at 0.897 (Pearson, p < 0.001). Absolute volume differences between caliper and MRI increased with tumor growth. NTGD-derived rates showed no correlation, with only 15% of NTGD caliper rates falling within 10% of the MRI rates. Conclusions: NTGD rate based on caliper volumes is a suitable measure of treatment response in preclinical studies. In the experiment described herein, caliper-derived NTGD rates did not correlate with MRI ground truth. These findings suggest that more accurate tumor volumetrics, derived from stored and verifiable medical imaging sources, should be used in preclinical assessment of oncologic interventions instead of standard caliper estimates. Full article

A woman in her 40s with a history of ER/PR+, HER2-negative breast cancer presented with a seizure three years after mastectomy. Magnetic resonance imaging (MRI) revealed a right caudate head mass, which was concerning for either high-grade glioma or metastatic disease, but biopsy was deemed too high risk. Cerebrospinal fluid (CSF) tumor-derived DNA (tDNA) analysis by next-generation sequencing (NGS) was ordered, revealing a gain-of-function variant in PIK3CA, ERBB2 copy number gain, and high aneuploidy, findings consistent with breast cancer brain metastasis. Based on these results, the patient was treated with stereotactic radiosurgery (SRS) followed by trastuzumab deruxtecan, a HER2-targeted therapy. This case highlights the diagnostic and therapeutic value of CSF tDNA analysis in central nervous system (CNS) lesions when biopsy is not feasible. The report also illustrates how clonal evolution, such as acquired ERBB2 amplification, can occur in metastatic disease and influence treatment decisions. Full article

Breast cancer is one of the major health threats to women worldwide; thus, a need has arisen to reduce the number of instances and deaths through new methods of diagnostic monitoring and treatment. The present review is the synthesis of the recent clinical studies and technological advances in the application of magnetic resonance imaging (MRI) to monitor the pharmacological treatment of breast cancer. The specific focus is on high-risk groups (carriers of BRCA mutations and recipients of neoadjuvant chemotherapy) and the use of novel MRI methods (dynamic contrast-enhanced (DCE) MRI, diffusion-weighted imaging (DWI), and radiomics tools). All the reviewed studies show that MRI is more sensitive (up to 95%) and specific than conventional imaging in detecting malignancy particularly in dense breast tissue. Moreover, MRI can be used to assess the response and residual disease in a tumor early and accurately for personalized treatment, de-escalate unneeded interventions, and maximize positive outcomes. AI-based radiomics combined with deep-learning models also expand the ability to predict the therapeutic response and molecular subtypes, and can mitigate the risk of overfitting models when using complex methods of modeling. Other developments are hybrid PET/MRI, image guidance during surgery, margin assessment intraoperatively, three-dimensional surgical templates, and the utilization of MRI in surgery planning and reducing reoperation. Although economic factors will always play a role, the diagnostic and prognostic accuracy and capability to aid in targeted treatment makes MRI a key tool for modern breast cancer. The growing complement of MRI and novel curative approaches indicate that breast cancer patients may experience better survival and recuperation, fewer recurrences, and a better quality of life. Full article