1H-MR spectroscopy of suspicious breast mass lesions at 3T: a clinical experience

Magnetic Resonance Imaging (MRI) and MR Spectroscopic Methods in Understanding Breast Cancer Biology and Metabolism

A common malignancy that affects women is breast cancer. It is the second leading cause of cancer-related death among women. Metabolic reprogramming occurs during cancer growth, invasion, and metastases. Functional magnetic resonance (MR) methods comprising an array of techniques have shown potential for illustrating physiological and molecular processes changes before anatomical manifestations on conventional MR imaging. Among these, in vivo proton (1H) MR spectroscopy (MRS) is widely used for differentiating breast malignancy from benign diseases by measuring elevated choline-containing compounds. Further, the use of hyperpolarized 13C and 31P MRS enhanced the understanding of glucose and phospholipid metabolism. The metabolic profiling of an array of biological specimens (intact tissues, tissue extracts, and various biofluids such as blood, urine, nipple aspirates, and fine needle aspirates) can also be investigated through in vitro high-resolution NMR spectroscopy and high-resolution magic angle spectroscopy (HRMAS). Such studies can provide information on more metabolites than what is seen by in vivo MRS, thus providing a deeper insight into cancer biology and metabolism. The analysis of a large number of NMR spectral data sets through multivariate statistical methods classified the tumor sub-types. It showed enormous potential in the development of new therapeutic approaches. Recently, multiparametric MRI approaches were found to be helpful in elucidating the pathophysiology of cancer by quantifying structural, vasculature, diffusion, perfusion, and metabolic abnormalities in vivo. This review focuses on the applications of NMR, MRS, and MRI methods in understanding breast cancer biology and in the diagnosis and therapeutic monitoring of breast cancer.

Multiparameter MRI Model With DCE-MRI, DWI, and Synthetic MRI Improves the Diagnostic Performance of BI-RADS 4 Lesions

Objectives

To evaluate the value of synthetic magnetic resonance imaging (syMRI), diffusion-weighted imaging (DWI), DCE-MRI, and clinical features in breast imaging–reporting and data system (BI-RADS) 4 lesions, and develop an efficient method to help patients avoid unnecessary biopsy.

Methods

A total of 75 patients with breast diseases classified as BI-RADS 4 (45 with malignant lesions and 30 with benign lesions) were prospectively enrolled in this study. T1-weighted imaging (T1WI), T2WI, DWI, and syMRI were performed at 3.0 T. Relaxation time (T1 and T2), apparent diffusion coefficient (ADC), conventional MRI features, and clinical features were assessed. “T” represents the relaxation time value of the region of interest pre-contrast scanning, and “T+” represents the value post-contrast scanning. The rate of change in the T value between pre- and post-contrast scanning was represented by ΔT%.

Results

ΔT1%, T2, ADC, age, body mass index (BMI), menopause, irregular margins, and heterogeneous internal enhancement pattern were significantly associated with a breast cancer diagnosis in the multivariable logistic regression analysis. Based on the above parameters, four models were established: model 1 (BI-RADS model, including all conventional MRI features recommended by BI-RADS lexicon), model 2 (relaxation time model, including ΔT1% and T2), model 3 [multi-parameter (mp)MRI model, including ΔT1%, T2, ADC, margin, and internal enhancement pattern], and model 4 (combined image and clinical model, including ΔT1%, T2, ADC, margin, internal enhancement pattern, age, BMI, and menopausal state). Among these, model 4 has the best diagnostic performance, followed by models 3, 2, and 1.

Conclusions

The mpMRI model with DCE-MRI, DWI, and syMRI is a robust tool for evaluating the malignancies in BI-RADS 4 lesions. The clinical features could further improve the diagnostic performance of the model.

Diagnostic Performance of Proton Magnetic Resonance Spectroscopy and 18F-Fluorocholine PET to Differentiate Benign From Malignant Breast Lesions

PURPOSE

The aim of this study was to evaluate the diagnostic performance of the proton magnetic resonance spectroscopy (MRS) and 18F-fluorocholine (FCH) PET for suspicious breast findings on conventional imaging (mammography and breast ultrasound).

METHODS

From September 2012 to December 2015, 37 women with 39 breast lesions on conventional imaging were enrolled and underwent proton MRS and FCH PET. The MRS parameters of choline signal-to-noise ratio (SNR), choline integral (I(cho)), and the PET parameters including SUVmax in the prone (SUV1) and supine (SUV2) positions were analyzed. Receiver operating characteristic curves with the area under the curve, sensitivity, and specificity under the optimal cutoff points for the different parameters were determined.

RESULTS

Twenty-three lesions (59%) were malignant, and 16 (41.0%) were benign. The malignant lesions tended to show significantly higher MRS and PET parameters than benign lesions (choline SNR, P = 0.007; I(cho), P = 0.003; SUV1 and SUV2, P < 0.0001). Fair to moderate correlations were noted between the choline SNR and PET parameters (SUV1, Spearman rank correlation coefficient, ρ = 0.477; SUV2, ρ = 0.483), as well as I(cho) and PET parameters (SUV1, ρ = 0.493; SUV2, ρ = 0.549). The SUV2 showed the highest diagnostic performance (area under the curve, 0.918). Using 2.5 as the optimal cutoff point, the SUV2 yields 89.5% sensitivity and 87.5% specificity for differentiating malignant from benign lesions.

CONCLUSION

The MRS parameters were fairly to moderately correlated with FCH PET parameters, and both could differentiate malignant from benign breast lesions with SUV2 showing best diagnostic performance.

[Influences of Tumor Volume and FWHM of the Water Peak and T2* Value of Water on the Detection Rate of the Choline Peaks in Proton MR Spectroscopy of Breast Cancer at 3.0 T-MRI]

In proton magnetic resonance (MR) spectroscopy (¹H-MRS) of the breast cancer, choline peak could be detected. The purpose of this study was to evaluate the influences of the tumor volume, full width at half maximum (FWHM) of the water peak (FWHM), and T₂* value of water (T₂* value) on the detection rate of the choline peaks at 3.0 T-MRI. We measured FWHM and T₂* value in 109 cases, and we evaluated the effect of tumor volume on the detection rate of the choline peaks and the effect of FWHM and T₂* value on the detection of choline peaks. In ¹H-MRS of breast cancer at 3.0 T-MRI, the detection rate of the choline peaks improved as the tumor volume was larger. As a shimming environment when acquiring ¹H-MRS of breast cancer, FWHM is preferably 57.4 Hz or less and T₂* value should be 11 ms or more, and T₂* value has a great influence on the detection rate of the choline peaks.

Preoperative loco-regional staging of invasive lobular carcinoma with contrast-enhanced digital mammography (CEDM)

The aim of our study was to assess the performance of contrast-enhanced digital mammography (CEDM) in the preoperative loco-regional staging of invasive lobular carcinoma (ILC) patients, about the valuation of the extension of disease and in measurement of lesions. Then, we selected retrospectively, among the 1500 patients underwent to CEDM at the Breast Diagnostics Department of the Careggi University Hospital of Florence and the National Cancer Institute of Milan from September 2016 to November 2018, 31 women (mean age 57.1 aa; range 41-78 aa) with a definitive histological diagnosis of ILC. CEDM has proved to be a promising imaging technique, being characterized by a sensitivity of 100% in the detection of the index lesion, and of 84.2% in identifying any adjunctive lesions: It was the presence of a non-mass enhancement (NME) to lower the sensitivity of the technique (25% vs. 100% for mass-like enhancements or a mass closely associated with a NME). Specificity in the characterization of additional lesions was 66.7%, and the diagnosis of the extension of disease was correct in 77.4% of cases: NME also led to a decrease in diagnostic accuracy in the evaluation of disease extension up to 40% versus 85% for masses and 80% for masses associated with NME (M/NME). Moreover, in 12/31 (38.7%), CEDM allowed to correctly identify lesions not shown by mammography + ultrasonography + tomosynthesis: In the half of these (6/12), there was a multicentricity, thus allowing an adequate surgical planning change. CEDM was also very accurate in analyzing the maximum diameter of the masses, while it was much less reliable in the case of the M/NME and pure NME. In conclusion, CEDM is a new promising imaging technique in the loco-regional preoperative staging and in the evaluation of disease extension for ILC, especially in case of mass enhancement lesions.

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer

Activated choline metabolism is a hallmark of carcinogenesis and tumor progression, which leads to elevated levels of phosphocholine and glycerophosphocholine in all types of cancer tested so far. Magnetic resonance spectroscopy applications have played a key role in detecting these elevated choline phospholipid metabolites. To date, the majority of cancer-related studies have focused on phosphocholine and the Kennedy pathway, which constitutes the biosynthesis pathway for membrane phosphatidylcholine. Fewer and more recent studies have reported on the importance of glycerophosphocholine in cancer. In this review article, we summarize the recent literature on glycerophosphocholine metabolism with respect to its cancer biology and its detection by magnetic resonance spectroscopy applications.

In vivo MR spectroscopy for breast cancer diagnosis

Breast cancer is a significant health concern in females, worldwide. In vivo proton (1H) MR spectroscopy (MRS) has evolved as a non-invasive tool for diagnosis and for biochemical characterization of breast cancer. Water-to-fat ratio, fat and water fractions and choline containing compounds (tCho) have been identified as diagnostic biomarkers of malignancy. Detection of tCho in normal breast tissue of volunteers and in lactating females limits the use of tCho as a diagnostic marker. Technological developments like high-field scanners, multi channel coils, pulse sequences with water and fat suppression facilitated easy detection of tCho. Also, quantification of tCho and its cut-off for objective assessment of malignancy have been reported. Meta-analysis of in vivo 1H MRS studies have documented the pooled sensitivities and the specificities in the range of 71-74% and 78-88%, respectively. Inclusion of MRS has been shown to enhance the diagnostic specificity of MRI, however, detection of tCho in small sized lesions (≤1 cm) is challenging even at high magnetic fields. Potential of MRS in monitoring the effect of chemotherapy in breast cancer has also been reported. This review briefly presents the potential clinical role of in vivo 1H MRS in the diagnosis of breast cancer, its current status and future developments.

Role of diffusion weighted imaging and magnetic resonance spectroscopy in breast cancer patients with indeterminate dynamic contrast enhanced magnetic resonance imaging findings

PURPOSE

Dynamic contrast enhanced MRI (DCEMRI), diffusion weighted imaging (DWI) and in vivo proton (¹H) magnetic resonance spectroscopy (MRS) provides functional and molecular nature of breast cancer. This study evaluates the potential of the combination of three MR parameters [curve kinetics, apparent diffusion coefficient (ADC) and total choline (tCho) concentration] determined from these techniques in increasing the sensitivity of breast cancer detection.

METHODS

MR investigations were carried out at 1.5 T on 56 patients with cytologically/histologically confirmed breast carcinoma. Single-voxel MRS was used to determine the tCho concentration. 3D FLASH was used for DCEMRI while single shot EPI based DWI was used for ADC determination.

RESULTS

On DCEMRI, one patient showed type I curve, while 8 showed type II and 47 showed type III curve thus giving a sensitivity of 83.9% as detection rate of malignancy. tCho concentration was above cut-off value (2.54 mmol/kg) for 50/56 cases giving a sensitivity of 89.3%. Among 9 indeterminate DCEMRI cases, tCho showed malignancy in 6 cases with type II curve. DWI detected malignancy in 54/56 cases that included 9 cases that were false negative on DCEMRI, yielding a sensitivity of 96.4%. A total of 54 cases showed malignancy when any two of the three MR parameters was positive for malignancy yielding a sensitivity of 96.4% while it increased to 100% when any one parameters showed positive result.

CONCLUSION

DWI showed highest sensitivity of detection compared to DCEMRI and MRS. Multi-parametric approach yielded 96.4% and 100% sensitivity when any two or one of the three parameters was taken as positive for malignancy, respectively. Also the results demonstrated that addition of DWI and MRS play a significant role in establishing the final diagnosis of malignancy, especially in cases where DCEMRI is indeterminate.

Is there a correlation between 3T multiparametric MRI and molecular subtypes of breast cancer?

OBJECTIVES

To test whether 3 T multiparametric magnetic resonance imaging (mMRI) provides information related to molecular subtypes of breast cancer.

METHODS

Women with mammographic or US findings of breast lesions (BI-RADS 4-5) underwent 3 T mMRI (DCE, DWI and MR spectroscopy). The histological type of breast cancer was assessed. Estrogen-receptor (ER), progesterone-receptor (PgR), Ki-67 status and HER-2 expression, assessed by immunohistochemistry (IHC), defined four molecular subtypes: Luminal-A, Luminal-B, HER2-enriched and triple-negative. Non-parametric tests (Kruskal-Wallis, k-sample equality of medians, and Mann-Whitney), logistic regression or ANOVA, and a multivariate analysis were performed to investigate correlations between the four molecular subtypes and mMRI (lesion volume, margins or distribution, enhancement pattern, ADC, type of kinetic curve, and total choline (tCho) signal-to-noise-ratio (SNR)). A ROC analysis was finally performed to test the diagnostic power of a multivariate logistic regression model.

RESULTS

433 patients (453 lesions) were considered. Volume was smaller in Luminal-B and larger in triple-negative tumours compared to the other subtypes combined. Margins were significantly correlated to Luminal-A and Luminal-B. The type of curve was significantly correlated to Luminal-A. ADC values were higher in Luminal-A. tCho SNR was higher in triple-negative tumours. The ROC analysis showed that the area under the curve (AUC) significantly improved when multiple MRI features were used compared to individual parameters.

CONCLUSIONS

A significant correlation was found between some MRI features and molecular subtypes of breast tumours. A multiparametric approach improved the diagnostic power of MRI. However, further research is needed in order to predict the molecular subtype on the sole basis of mMRI.

A simple classification system (the Tree flowchart) for breast MRI can reduce the number of unnecessary biopsies in MRI-only lesions

OBJECTIVES

To assess whether using the Tree flowchart obviates unnecessary magnetic resonance imaging (MRI)-guided biopsies in breast lesions only visible on MRI.

METHODS

This retrospective IRB-approved study evaluated consecutive suspicious (BI-RADS 4) breast lesions only visible on MRI that were referred to our institution for MRI-guided biopsy. All lesions were evaluated according to the Tree flowchart for breast MRI by experienced readers. The Tree flowchart is a decision rule that assigns levels of suspicion to specific combinations of diagnostic criteria. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic accuracy. To assess reproducibility by kappa statistics, a second reader rated a subset of 82 patients.

RESULTS

There were 454 patients with 469 histopathologically verified lesions included (98 malignant, 371 benign lesions). The area under the curve (AUC) of the Tree flowchart was 0.873 (95% CI: 0.839-0.901). The inter-reader agreement was almost perfect (kappa: 0.944; 95% CI 0.889-0.998). ROC analysis revealed exclusively benign lesions if the Tree node was ≤2, potentially avoiding unnecessary biopsies in 103 cases (27.8%).

CONCLUSIONS

Using the Tree flowchart in breast lesions only visible on MRI, more than 25% of biopsies could be avoided without missing any breast cancer.

KEY POINTS

• The Tree flowchart may obviate >25% of unnecessary MRI-guided breast biopsies. • This decrease in MRI-guided biopsies does not cause any false-negative cases. • The Tree flowchart predicts 30.6% of malignancies with >98% specificity. • The Tree's high specificity aids in decision-making after benign biopsy results.