A Clinical Oncologic Perspective on Breast Magnetic Resonance Imaging

Bloom, Sara; Morrow, Monica

doi:10.1016/j.mric.2010.02.007

Cited by 14 publications

(11 citation statements)

References 110 publications

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“…DW images were co-registered to b 0 image for motion correction, and then the parametric maps were calculated pixel by pixel according the formula. 1 The median K app and D app values were then calculated from the histogram from the whole lesion (Figures 1-4).…”

Section: Image Analysismentioning

confidence: 99%

“…It is widely used as a supplementary modality to mammography and ultrasound, mainly for local staging of recently diagnosed breast cancers and recently as a screening tool for patients at a high risk. [1][2][3][4][5][6] Dynamic contrast-enhanced (DCE)-MRI using gadolinium contrast material offers high sensitivity in detecting breast lesions, and thus it has been widely used in the past decades to locate breast cancers, to show the extent of the disease and to demonstrate small multifocal breast tumours. The sensitivity ranges in literature between 89% and 100%.…”

Section: Introductionmentioning

confidence: 99%

“…The lowest and the highest D app values of malignant lesions were lower than those of benign lesions. A cut-off value of 1 …”

mentioning

confidence: 99%

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Accuracy of diffusion kurtosis imaging in characterization of breast lesions

Christou

Ghiatas²,

Priovolos

et al. 2017

BJR

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Objective: The aim of this study was to evaluate the accuracy of diffusion kurtosis in the characterization and differentiation of breast lesions. Methods: 49 females with 53 breast lesions underwent breast MRI. The MRI magnetic field is 1.5 T, and the protocol is standard MRI sequences, dynamic sequences pre-and post-contrast agent administration and diffusion images. Diffusion kurtosis imaging (DKI) was applied as part of our standard breast MRΙ protocol. Two experienced radiologists on breast MRI, blinded to the final diagnosis, reviewed the parametric maps and placed a volume of interest on all slices including each lesion. Kurtosis [K apparent (K app )] and corrected apparent diffusion coefficient [D apparent (D app )] median values were then calculated from the whole-lesion histogram analysis. Receiver-operating characteristic analysis was used to determine the most effective cut-off values for the differentiation between benign and malignant pathologies. Histological analysis of the breast lesions was performed, and further comparative analysis of the results was performed to investigate the accuracy of the method. Conclusion: DKI is an accurate additional tool for the characterization and differentiation of breast lesions with high K app and D app sensitivity and specificity rates. Advances in knowledge: DKI is able to distinguish benign from malignant breast pathologies. DKI increases the specificity of breast MRI. INTRODUCTIONBreast MRI is a well-established method for the evaluation of breast pathologies. It is widely used as a supplementary modality to mammography and ultrasound, mainly for local staging of recently diagnosed breast cancers and recently as a screening tool for patients at a high risk.

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Section: Image Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accuracy of diffusion kurtosis imaging in characterization of breast lesions

Christou

Ghiatas²,

Priovolos

et al. 2017

BJR

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“…In breast cancer, these small tumor deposits can change surgical decision making, but do not provide such prognostic relevance in breast conserving surgery, as postoperative radiation eliminates microscopic tumor deposits in most cases [26]. For example, the rate of small tumor deposits is 2 to 3 times higher than the incidence of local recurrence using preoperative MR imaging, resulting in mastectomies that may not be beneficial to patient survival [27]. On the other hand, adequate visualization of tumor margins intraoperatively would be beneficial to lower the number of R1 resections and to avoid the need for re-resections and radiotherapeutic boost therapy [28].…”

Section: Discussionmentioning

confidence: 99%

Real-time intraoperative detection of breast cancer using near-infrared fluorescence imaging and Methylene Blue

Tummers

Verbeek

Schaafsma

et al. 2014

European Journal of Surgical Oncology (EJSO)

114

119

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Background Despite recent developments in preoperative breast cancer imaging, intraoperative localization of tumor tissue can be challenging, resulting in tumor-positive resection margins during breast-conserving surgery. Based on certain physicochemical similarities between Technetium(99mTc)-sestamibi (MIBI), a SPECT radiodiagnostic with a sensitivity of 83–90% to detect breast cancer preoperatively, and the near-infrared (NIR) fluorophore Methylene Blue (MB), we hypothesized that MB might detect breast cancer intraoperatively using NIR fluorescence imaging. Methods Twenty-four patients with breast cancer, planned for surgical resection, were included. Patients were divided in 2 administration groups, which differed with respect to the timing of MB administration. N = 12 patients per group were administered 1.0 mg/kg MB intravenously either immediately or 3 h before surgery. The mini-FLARE imaging system was used to identify the NIR fluorescent signal during surgery and on post-resected specimens transferred to the pathology department. Results were confirmed by NIR fluorescence microscopy. Results 20/24 (83%) of breast tumors (carcinoma in N=21 and ductal carcinoma in situ in N=3) were identified in the resected specimen using NIR fluorescence imaging. Patients with non-detectable tumors were significantly older. No significant relation to receptor status or tumor grade was seen. Overall tumor-to-background ratio (TBR) was 2.4 ± 0.8. There was no significant difference between TBR and background signal between administration groups. In 2/4 patients with positive resection margins, breast cancer tissue identified in the wound bed during surgery would have changed surgical management. Histology confirmed the concordance of fluorescence signal and tumor tissue. Conclusions This feasibility study demonstrated an overall breast cancer identification rate using MB of 83%, with real-time intraoperative guidance having the potential to alter patient management.

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“…It is widely used in a variety of clinical settings, such as local staging in patients recently diagnosed with breast cancer and as a screening tool for high-risk females. [8][9][10][11][12][13] DCE breast MRI is the most proposed imaging method, with a high sensitivity ranging between 89 and 100%. However, its suboptimal specificity (reportedly around 75%) imposes a significant setback, particularly in patients referred for evaluation of inconclusive findings on clinical examination and conventional breast imaging.…”

Section: Discussionmentioning

confidence: 99%

Whole-lesion apparent diffusion coefficient (ADC) metrics as a marker of breast tumour characterization—comparison between ADC value and ADC entropy

Bougias¹,

Ghiatas²,

Priovolos³

et al. 2016

The British Journal of Radiology

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Objective: To prospectively assess the role of wholelesion apparent diffusion coefficient (ADC) metrics in the characterization of breast tumours by comparing ADC value with ADC entropy. Methods: 49 patients with 53 breast lesions underwent phased-array breast coil 1.5-T MRI. Two radiologists experienced in breast MRI, blinded to the final diagnosis, reviewed the ADC maps and placed a volume of interest on all slices including each lesion on the ADC map to obtain whole-lesion mean ADC value and ADC entropy. The mean ADC value and ADC entropy in benign and malignant lesions were compared by the Mann-Whitney U-test. Receiver-operating characteristic analysis was performed to assess the sensitivity and specificity of the two variables in the characterization of the breast lesions. Results: The benign (n 5 19) and malignant lesions (n 5 34) had mean diameters of 20.8 mm (10.1-31.5 mm) and 26.4 mm (10.5-42.3 mm), respectively. The mean ADC value of the malignant lesions was significantly lower than that of the benign ones (0.87 3 10 23 vs , the sensitivity and specificity for diagnosing malignancy became optimal (97.1% and 93.7, respectively) with an area under the curve (AUC) of 0.975. With regard to ADC entropy, the sensitivity and specificity at a cut-off of 5.18 were 67.6 and 68.7%, respectively, with an AUC of 0.664. Conclusion: Whole-lesion mean ADC could be a helpful index in the characterization of suspicious breast lesions, with higher sensitivity and specificity than ADC entropy. Advances in knowledge: Two separate parameters of the whole-lesion histogram were compared for their diagnostic accuracy in characterizing breast lesions. Mean ADC was found to be able to characterize breast lesions, whereas entropy proved to be unable to differentiate benign from malignant breast lesions. It is, however, likely that entropy may distinguish these two groups if a larger cohort were used, or the fact that this may be influenced by the molecular subtypes of breast cancers included.

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A Clinical Oncologic Perspective on Breast Magnetic Resonance Imaging

Cited by 14 publications

References 110 publications

Accuracy of diffusion kurtosis imaging in characterization of breast lesions

Accuracy of diffusion kurtosis imaging in characterization of breast lesions

Real-time intraoperative detection of breast cancer using near-infrared fluorescence imaging and Methylene Blue

Whole-lesion apparent diffusion coefficient (ADC) metrics as a marker of breast tumour characterization—comparison between ADC value and ADC entropy

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