Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer

Integrative radiomics clustering analysis to decipher breast cancer heterogeneity and prognostic indicators through multiparametric MRI

Breast cancer diagnosis and treatment have been revolutionized by multiparametric Magnetic Resonance Imaging (mpMRI), encompassing T2-weighted imaging (T2WI), Diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced MRI (DCE-MRI). We conducted a retrospective analysis of mpMRI data from 194 breast cancer patients (September 2019 to October 2023). Using 'pyradiomics' for radiomics feature extraction and MOVICS for unsupervised clustering. Interestingly, we identified two distinct patient clusters associated with significant differences in molecular subtypes, particularly in Luminal A subtype distribution (p = 0.03), estrogen receptor (ER) (p = 0.01), progesterone receptor (PR) (p = 0.04), mean tumor size (p < 0.01), lymph node metastasis (LNM) (p = 0.01), and edema (p < 0.01). Our study emphasizes mpMRI's potential in breast cancer by using radiomics-based cluster analysis to categorize tumors, uncovering heterogeneity, and aiding in personalized treatment strategies.

Feasibility of deep learning-reconstructed thin-slice single-breath-hold HASTE for detecting pancreatic lesions: A comparison with two conventional T2-weighted imaging sequences

Objective

The objective of this study was to evaluate the clinical feasibility of deep learning reconstruction-accelerated thin-slice single-breath-hold half-Fourier single-shot turbo spin echo imaging (HASTEDL) for detecting pancreatic lesions, in comparison with two conventional T2-weighted imaging sequences: compressed-sensing HASTE (HASTECS) and BLADE.

Methods

From March 2022 to January 2023, a total of 63 patients with suspected pancreatic-related disease underwent the HASTEDL, HASTECS, and BLADE sequences were enrolled in this retrospectively study. The acquisition time, the pancreatic lesion conspicuity (LCP), respiratory motion artifact (RMA), main pancreatic duct conspicuity (MPDC), overall image quality (OIQ), signal-to-noise ratio (SNR), and contrast-noise-ratio (CNR) of the pancreatic lesions were compared among the three sequences by two readers.

Results

The acquisition time of both HASTEDL and HASTECS was 16 s, which was significantly shorter than that of 102 s for BLADE. In terms of qualitative parameters, Reader 1 and Reader 2 assigned significantly higher scores to the LCP, RMA, MPDC, and OIQ for HASTEDL compared to HASTECS and BLADE sequences; As for the quantitative parameters, the SNR values of the pancreatic head, body, tail, and lesions, the CNR of the pancreatic lesion measured by the two readers were also significantly higher for HASTEDL than for HASTECS and BLADE sequences.

Conclusions

Compared to conventional T2WI sequences (HASTECS and BLADE), deep-learning reconstructed HASTE enables thin slice and single-breath-hold acquisition with clinical acceptable image quality for detection of pancreatic lesions.

Advanced Magnetic Resonance Imaging Modalities for Breast Cancer Diagnosis: An Overview of Recent Findings and Perspectives

Breast cancer is the most prevalent cancer among women and the leading cause of death. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced magnetic resonance imaging (MRI) procedures that are widely used in the diagnostic and treatment evaluation of breast cancer. This review article describes the characteristics of new MRI methods and reviews recent findings on breast cancer diagnosis. This review study was performed on the literature sourced from scientific citation websites such as Google Scholar, PubMed, and Web of Science until July 2021. All relevant works published on the mentioned scientific citation websites were investigated. Because of the propensity of malignancies to limit diffusion, DWI can improve MRI diagnostic specificity. Diffusion tensor imaging gives additional information about diffusion directionality and anisotropy over traditional DWI. Recent findings showed that DWI and DTI and their characteristics may facilitate earlier and more accurate diagnosis, followed by better treatment. Overall, with the development of instruments and novel MRI modalities, it may be possible to diagnose breast cancer more effectively in the early stages.

Predictive Value of Preoperative Dynamic Contrast-Enhanced MRI Imaging Features in Breast Cancer Patients with Postoperative Recurrence Time

Although the implementation of surgery has reduced the mortality of breast cancer, postoperative recurrence is still an important problem bothering patients. DCE-GMRI can not only clearly display the morphological characteristics of breast lesions but also dynamically observe the blood perfusion of the lesions. On account of this, we explored the predictive value of preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) imaging features in breast cancer patients on postoperative recurrence time of breast cancer. The results showed that DCE-MRI images can clearly show the hemodynamic characteristics and morphological characteristics of tumor lesions, and have important value in predicting the recurrence time of breast cancer after surgery. The prognosis of early recurrence of breast cancer is worse. DCE-MRI can predict the time of postoperative recurrence and provide important clinical references.

Intra-tumoural lipid composition and lymphovascular invasion in breast cancer via non-invasive magnetic resonance spectroscopy

OBJECTIVES

Despite improved survival due to new treatments, the 10-year survival rate in patients with breast cancer is approximately 75%. Lymphovascular invasion (LVI), a prognostic marker independent from histological grade and stage, can only be fully determined at final histological examination. Lipid composition is deregulated in tumour via de novo lipogenesis, with alteration in lipogenic genes in LVI. We hypothesise alteration in lipid composition derived from novel non-invasive spectroscopy method is associated with LVI positivity.

METHODS

Thirty female patients (age 39-78) with invasive ductal carcinoma were enrolled, with 13 LVI negative and 17 LVI positive. Saturated, monounsaturated, polyunsaturated fatty acids and triglycerides (SFA, MUFA, PUFA and TRG) were quantified from ex vivo breast tumours freshly excised from patients on a 3 T clinical MRI scanner, and proliferative activity marker Ki-67 and serotonin derived histologically.

RESULTS

There were significantly lower MUFA (p = 0.0189) in LVI positive (median: 0.37, interquartile range (IQR): 0.25-0.64) than negative (0.63, 0.49-0.96). There were significantly lower TRG (p = 0.0226) in LVI positive (1.32, 0.95-2.43) than negative (2.5, 1.92-4.15). There was no significant difference in SFA (p = 0.6009) or PUFA (p = 0.1641). There was no significant correlation between lipid composition against Ki-67 or serotonin, apart from a borderline negative correlation between PUFA and serotonin (r = - 0.3616, p = 0.0496).

CONCLUSION

Lipid composition might provide a biomarker to study lymphovascular invasion in breast cancer.

KEY POINTS

• Monounsaturated fatty acids in lymphovascular invasion (LVI) positive invasive breast carcinoma were significantly lower than that in LVI negative. • Triglycerides in LVI positive invasive breast carcinoma were significantly lower than that in LVI negative. • Lipid composition from MR spectroscopy reflects the rate of de novo lipogenesis and provides a potential biomarker independent from histological grade and stage.