Breast MRI: Clinical Indications, Recommendations, and Future Applications in Breast Cancer Diagnosis

Wekking, Demi; Porcu, Michele; Silva, Pushpamali De; Saba, Luca; Scartozzi, Mario; Solinas, Cinzia

doi:10.1007/s11912-023-01372-x

Cited by 18 publications

(4 citation statements)

References 61 publications

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“…As the most accurate non-invasive single-imaging technology, MRI is crucial for breast cancer diagnosis [ 49 ]. Herein, MRI T1 imaging of DNMF/PLGA NPs was systematically investigated.…”

Section: Resultsmentioning

confidence: 99%

Nitric oxide nano-reactor DNMF/PLGA enables tumor vascular microenvironment and chemo-hyperthermia synergetic therapy

Wang,

Cheng,

et al. 2024

J Nanobiotechnol

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Background Breast cancer ranks first among malignant tumors, of which triple-negative breast cancer (TNBC) is characterized by its highly invasive behavior and the worst prognosis. Timely diagnosis and precise treatment of TNBC are substantially challenging. Abnormal tumor vessels play a crucial role in TNBC progression and treatment. Nitric oxide (NO) regulates angiogenesis and maintains vascular homeostasis, while effective NO delivery can normalize the tumor vasculature. Accordingly, we have proposed here a tumor vascular microenvironment remodeling strategy based on NO-induced vessel normalization and extracellular matrix collagen degradation with multimodality imaging-guided nanoparticles against TNBC called DNMF/PLGA. Results Nanoparticles were synthesized using a chemotherapeutic agent doxorubicin (DOX), a NO donor L-arginine (L-Arg), ultrasmall spinel ferrites (MnFe2O4), and a poly (lactic-co-glycolic acid) (PLGA) shell. Nanoparticle distribution in the tumor was accurately monitored in real-time through highly enhanced magnetic resonance imaging and photoacoustic imaging. Near-infrared irradiation of tumor cells revealed that MnFe2O4 catalyzes the production of a large amount of reactive oxygen species (ROS) from H2O2, resulting in a cascade catalysis of L-Arg to trigger NO production in the presence of ROS. In addition, DOX activates niacinamide adenine dinucleotide phosphate oxidase to generate and supply H2O2. The generated NO improves the vascular endothelial cell integrity and pericellular contractility to promote vessel normalization and induces the activation of endogenous matrix metalloproteinases (mainly MMP-1 and MMP-2) so as to promote extravascular collagen degradation, thereby providing an auxiliary mechanism for efficient nanoparticle delivery and DOX penetration. Moreover, the chemotherapeutic effect of DOX and the photothermal effect of MnFe2O4 served as a chemo-hyperthermia synergistic therapy against TNBC. Conclusion The two therapeutic mechanisms, along with an auxiliary mechanism, were perfectly combined to enhance the therapeutic effects. Briefly, multimodality image-guided nanoparticles provide a reliable strategy for the potential application in the fight against TNBC. Graphical Abstract

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“…As the most accurate non-invasive single-imaging technology, MRI is crucial for breast cancer diagnosis [ 49 ]. Herein, MRI T1 imaging of DNMF/PLGA NPs was systematically investigated.…”

Section: Resultsmentioning

confidence: 99%

Nitric oxide nano-reactor DNMF/PLGA enables tumor vascular microenvironment and chemo-hyperthermia synergetic therapy

Wang,

Cheng,

et al. 2024

J Nanobiotechnol

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“…MRI is widely used to detect BC 17 , 18 . There is amount of evidence that MRI has a higher sensitivity in detecting breast malignancies in individuals with a high-risk of BC or an average risk of dense breast than mammography 19 , while BC with a genetic background accounts for 5–10% of all BC 20 , and it is estimated that up to 50% of women in the United States experience dense breasts in mammography 21 . A 2010 questionnaire distributed among the members of the American Society of Breast Surgeons (ASBrS) analyzed the replies from 1012 surgeons on the use of MRI in tens of thousands of BC patients.…”

Section: Discussionmentioning

confidence: 99%

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study

Lai,

Chen,

Liu

et al. 2024

International Journal of Surgery

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Background: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast cancer (BC). The aim of this study was to construct a radiogenomic multimodal model, based on machine learning (ML) and whole-transcriptome sequencing (WTS), to accurately preoperative evaluate the risk of ALN metastasis (ALNM), drug therapeutic response and avoid unnecessary axillary surgery in BC patients. Methods: In this study, we conducted a retrospective analysis of 1078 BC patients from The Cancer Genome Atlas (TCGA), The Cancer Imaging Archive (TCIA), and Foshan cohort. These patients were divided into the TCIA cohort(N=103), TCIA validation cohort(N=51), Duke cohort(N=138), Foshan cohort(N=106), and TCGA cohort(N=680). Radiological features were extracted from BC radiological images and differentially expressed gene expression was calibrated using WTS technology. A support vector machine (SVM) model was employed to screen radiological and genetic features, and a multimodal model was established based on radiogenomic and clinical pathological features to predict ALNM and stratify. The accuracy of the model predictions was assessed using the area under the curve (AUC) and the clinical benefit was measured using decision curve analysis (DCA). Risk stratification analysis of BC patients was performed by gene set enrichment analysis (GSEA), differential comparison of immune checkpoint gene expression, and drug sensitivity testing. Results: For the prediction of ALNM, rad-score was able to significantly differentiate between ALN- and ALN+ patients in both the Duke and Foshan cohorts (P<0.05). Similarly, the gene-score was able to significantly differentiate between ALN- and ALN+ patients in the TCGA cohort (P<0.05). The radiogenomic multimodal nomogram demonstrated satisfactory performance in the TCIA cohort (AUC 0.82, 95% CI: 0.74-0.91) and TCIA validation cohort (AUC 0.77, 95% CI: 0.63-0.91). In the risk sub-stratification analysis, there were significant differences in gene pathway enrichment between high and low-risk groups (P<0.05). Additionally, different risk groups may exhibit varying treatment responses to chemotherapy (including Doxorubicin, Methotrexate and Lapatinib) (P<0.05). Conclusion: Overall, the radiogenomic multimodal model employs multimodal data, including radiological images, genetic and clinicopathological typing. The radiogenomic multimodal nomogram can precisely predict ALNM and drug therapeutic response in BC patients.

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“…Magnetic resonance imaging (MRI), unlike mammography, is a highly sensitive technique that uses magnetic fields to analyze the lesions and lumps in the tissues (Wekking et al, 2023). It is not considered as the main imaging technique for breast cancer; nevertheless, it is used as a confirmation step especially in the early diagnosis.…”

Section: Molecular Imaging Techniquementioning

confidence: 99%

Advances in nanocomposites-based electrochemical biosensors for the early diagnosis of breast cancer

Gamal,

Eldin,

Refaat

et al. 2024

Front. Sens.

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Regardless of many years of research work and conducting numerous clinical studies, breast cancer (BC) continues to grow among women, threatening their lives and future. Currently, it affects more than 10% of women globally. Therefore, researchers have recently redirected their endeavors toward detecting BC at an early stage, recognizing its substantial impact on survival rates, and acknowledging its immense potential for providing effective cancer treatments at this early diagnosed disease stage. The utilization of biomarker-based diagnostic techniques significantly contributes to the advancement of early detection and precision. A wide range of biomarkers is linked to every newly diagnosed BC case. Traditionally, breast cancer was diagnosed using a variety of techniques such as mammography, molecular imaging, and ultrasonography. These techniques had several drawbacks, drawing the attention of many scientists to developing new methods and strategies. Among these strategies, electrochemical biosensors have proven to be excellent alternatives to more complex and traditional detection strategies in terms of performance, accuracy, robustness, and a tremendous range of applications. In this review, the use of conventional methods for detecting BC as well as their challenges and shortcomings have been stated. Moreover, a deep discussion was given to the newly developed nanocomposite-based electrochemical bio-sensing approaches that have been exploited for the effective detection and quantification of breast cancer biomarkers.

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Breast MRI: Clinical Indications, Recommendations, and Future Applications in Breast Cancer Diagnosis

Cited by 18 publications

References 61 publications

Nitric oxide nano-reactor DNMF/PLGA enables tumor vascular microenvironment and chemo-hyperthermia synergetic therapy

Nitric oxide nano-reactor DNMF/PLGA enables tumor vascular microenvironment and chemo-hyperthermia synergetic therapy

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study

Advances in nanocomposites-based electrochemical biosensors for the early diagnosis of breast cancer

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