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MRI accurately identifies early murine mammary cancers and reliably differentiates between in situ and invasive cancer: correlation of MRI with histology.

ABSTRACT: MRI methods that accurately identify various stages of mouse mammary cancer could provide new knowledge that may have a direct impact on the management of breast cancer in patients. This research investigates whether we can accurately follow the progression from in situ to invasive cancer by the evaluation of in vivo and ex vivo MRI, and in comparison with histology as the gold standard for the diagnosis and staging of cancer. Six C3(1)SV40Tag virgin female mice, aged 12-16 weeks, were studied. At this age, these mice develop in situ cancer that resembles human ductal carcinoma in situ (DCIS). Fast spin-echo images of inguinal mammary glands were acquired at 9.4 T. After in vivo MRI, mice were sacrificed; inguinal mammary glands were excised and fixed in formalin for ex vivo MRI. Three-dimensional, volume-rendered, in vivo and ex vivo MR images were then correlated with histology. High-resolution ex vivo scans facilitated the comparison of in vivo scans with histology. The sizes of mammary cancers classified as in situ on the basis of histology ranged from 150 to 400 µm in largest diameter, and the average signal intensity relative to muscle was 1.40 ± 0.18 on T2 -weighted images. Cancers classified as invasive on the basis of histology were >400 µm in largest diameter, and the average intensity relative to muscle on T2 -weighted images was 2.34 ± 0.26. Using a cut-off of 400 µm in largest diameter to distinguish between in situ and invasive cancers, a T2 -weighted signal intensity of at least 1.4 times that of muscle for in situ cancer, and at least 2.3 times that of muscle for invasive cancer, 96% of in situ and 100% of invasive cancers were correctly identified on in vivo MRI, using histology as the gold standard. Precise MRI-histology correlation demonstrates that MRI reliably detects early in situ cancer and differentiates in situ from invasive cancers in the SV40Tag mouse model of human breast cancer.

SUBMITTER: Mustafi D

PROVIDER: S-EPMC4696760 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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MRI accurately identifies early murine mammary cancers and reliably differentiates between in situ and invasive cancer: correlation of MRI with histology.

Mustafi Devkumar D Zamora Marta M Fan Xiaobing X Markiewicz Erica E Mueller Jeffrey J Conzen Suzanne D SD Karczmar Gregory S GS

NMR in biomedicine 20150707 9

MRI methods that accurately identify various stages of mouse mammary cancer could provide new knowledge that may have a direct impact on the management of breast cancer in patients. This research investigates whether we can accurately follow the progression from in situ to invasive cancer by the evaluation of in vivo and ex vivo MRI, and in comparison with histology as the gold standard for the diagnosis and staging of cancer. Six C3(1)SV40Tag virgin female mice, aged 12-16 weeks, were studied. ...[more]

PMID: 26152557

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Project description:PurposeThis prospective study evaluated the use of vascular, extracellular and restricted diffusion for cytometry in tumours (VERDICT) MRI to investigate the tissue microstructure in glioma. VERDICT-derived parameters were correlated with both histological features and tumour subtype and were also used to explore the peritumoural region.MethodsFourteen consecutive treatment-naïve patients (43.5 years ± 15.1 years, six males, eight females) with suspected glioma underwent diffusion-weighted imaging including VERDICT modelling. Tumour cell radius and intracellular and combined extracellular/vascular volumes were estimated using a framework based on linearisation and convex optimisation. An experienced neuroradiologist outlined the peritumoural oedema, enhancing tumour and necrosis on T2-weighted imaging and contrast-enhanced T1-weighted imaging. The same regions of interest were applied to the co-registered VERDICT maps to calculate the microstructure parameters. Pathology sections were analysed with semi-automated software to measure cellularity and cell size.ResultsVERDICT parameters were successfully calculated in all patients. The imaging-derived results showed a larger intracellular volume fraction in high-grade glioma compared to low-grade glioma (0.13 ± 0.07 vs. 0.08 ± 0.02, respectively; p = 0.05) and a trend towards a smaller extracellular/vascular volume fraction (0.88 ± 0.07 vs. 0.92 ± 0.04, respectively; p = 0.10). The conventional apparent diffusion coefficient was higher in low-grade gliomas compared to high-grade gliomas, but this difference was not statistically significant (1.22 ± 0.13 × 10-3 mm2/s vs. 0.98 ± 0.38 × 10-3 mm2/s, respectively; p = 0.18).ConclusionThis feasibility study demonstrated that VERDICT MRI can be used to explore the tissue microstructure of glioma using an abbreviated protocol. The VERDICT parameters of tissue structure correlated with those derived on histology. The method shows promise as a potential test for diagnostic stratification and treatment response monitoring in the future.Key points• VERDICT MRI is an advanced diffusion technique which has been correlated with histopathological findings obtained at surgery from patients with glioma in this study. • The intracellular volume fraction measured with VERDICT was larger in high-grade tumours compared to that in low-grade tumours. • The results were complementary to measurements from conventional diffusion-weighted imaging, and the technique could be performed in a clinically feasible timescale.

Project description:Since the advent of screening mammography, approximately one-quarter of newly diagnosed breast cancers are at the earliest preinvasive stage of ductal carcinoma in situ (DCIS). Concomitant with this improvement in early detection has been a growing clinical concern that distinguishing aggressive from indolent DCIS is necessary to optimize patient management. Genetically engineered mouse models offer an appealing experimental framework in which to investigate factors that influence and predict progression of preinvasive neoplasias. Because of the small size of early stage carcinomas in mice, high-resolution imaging techniques are required to effectively observe longitudinal progression. The purpose of the present study was to evaluate the feasibility of MRI for assessment of in situ mammary neoplasias and early invasive mammary cancers that stochastically arise in mammary glands of C3(1) SV40 Tag transgenic mice. Additionally, images of normal mammary glands from wild-type FVB/N mice were acquired and compared with those from transgenic mice. Sixteen mice underwent MR examinations employing axial two-dimensional multi-slice gradient recalled echo scans (TR/TE =∼1000/5.5 ms) with fat suppression in a two-step process targeting both the upper and lower mammary glands. MRI successfully detected in situ and early invasive neoplasias in transgenic mice with high sensitivity and specificity. The average signal-to-noise ratio (SNR) of in situ lesions on fat-suppressed high-resolution T(1) -weighted images was 22.9, which was lower than that of invasive tumors, lymph nodes and muscle (average SNR of 29.5-34.9, p < 0.0001) but significantly higher than that of normal mammary tissue (average SNR = 5.5, p < 0.0001). Evaluation of wild-type mammary glands revealed no cancerous or benign lesions, and comparable image contrast characteristics (average SNR = 5.2) as compared with normal tissue areas of transgenic mice. This present study demonstrates that MRI is an excellent candidate for performing longitudinal assessment of early stage mammary cancer disease progression and response to therapy in the transgenic model system.

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MRI accurately identifies early murine mammary cancers and reliably differentiates between in situ and invasive cancer: correlation of MRI with histology.

Publications

MRI accurately identifies early murine mammary cancers and reliably differentiates between in situ and invasive cancer: correlation of MRI with histology.

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