Wen Feng1, Junqiang Lei1, Yuhui Xiong2, Mengmeng Qu1, Xinran Liu1, Jianlin Li1, and Wencheng Dang3
1Radiology, The First Hospital of Lanzhou University, Lanzhou, China, 2GE HealthCare MR Research, Beijing, China, 3Breast Disease, The First Hospital of Lanzhou University, Lanzhou, China
Synopsis
Keywords: Breast, Breast, MRI; MUSE-IVIM; IVIM; HER-2
Motivation: Few studies had explored different diffusion imaging techniques of magnetic resonance imaging for molecular prognostic factors of breast cancer, and human epidermal growth factor receptor-2(HER-2) was closely related to targeted therapy.
Goal(s): To compare the effect of high-resolution magnetic resonance intravoxel incoherent motion based on multiplexed sensitivity encoding (MUSE-IVIM) and conventional IVIM in predicting HER-2 status in breast cancer.
Approach: Different parameters of MUSE-IVIM and IVIM within and around the tumor were analyzed, including apparent diffusion coefficient (ADC), tissue diffusivity (Dt), pseudo diffusivity (Dp), perfusion fraction (f).
Results: IVIM-Dt-intratumoral predicted HER-2 with the highest value(AUC=0.775, P=0.003).
Impact: Although the signal to noise ratio (SNR) of MUSE-IVIM was higher than
IVIM, they may be evenly matched in predicting HER-2 in breast cancer, which
required more research and exploration.
Introduction
Previous studies on
breast cancer mainly were dedicated to the intratumoral region1-3,
while recent studies have shown that the microenvironment of tumor was crucial
in the occurrence and progression of breast cancer, and the peritumoral region
may contain characteristic information, for instance, vascular lymphatic and immune cell infiltration4.
The parameters of traditional IVIM were calculated by means of double
exponential curve fitting5. Nevertheless MUSE-IVIM was used to fill K-space with multiple excitations to achieve
high resolution and high SNR6. At present, the gold standard of HER-2 examination are invasive
pathological methods, therefore, non-invasive prediction of HER-2 status before surgery has to
be settled urgently.Methods
Participants
and data acquisition:
This study was conducted in accordance with the Helsinki Declaration
and written informed consent for study participation was waived, which was
permitted by Institutional Ethics Committee. A total of 47 cases of breast
cancer patients confirmed by pathology were collected, including 14 cases in
the positive HER-2 group and 33 cases in the negative HER-2 group, who
underwent preoperative 3.0T
MR scanning( SIGNATM Architect, GE Healthcare, Milwaukee WI, USA) with
sequences of IVIM and MUSE-IVIM analyzed retrospectively from September 2022 to
August 2023.
Image
analysis:
Breast MRI images were obtained by a 3.0T scanner using a dedicated
8-channel phased-array breast coil in the prone position. Dt, Dp, f and ADC
images were analyzed with iQuant workstation. Image registration was performed
on ITK-SNAP software (version 3.8, http://www.itksnap.org) with reference to the breast MRI images at the maximum
intensification stage. Two breast-specialized radiologists delineated the tumor
regions of interest (ROI) and peritumoral regions of the tumor( the square ROIs were placed
on the enhanced image at the solid area of maximum intratumoral enhancement and
the area within 2mm periatumoral area respectively). The ROIs were plotted in the solid region
inside the tumor and the region within 2mm of the tumor circumference without considering
about the HER-2 status, and intraclass correlation coefficient(ICC) was
calculated. In addition, SNR0 (b=0 s/mm2) and SNR800
(b=800 s/mm2) were measured in picture archiving and communication
systems(PACS) .
Pathological
criteria:
A HER-2 staining intensity
score of not lower than 3 with immumohistochemical staining, or a HER-2
staining intensity score of 2 with gene amplification confirmed by fluorescence
in situ hybridization(FISH), was considered to be positive (HER-2 positive
group, 14 cases), while otherwise was
considered to be low (HER-2 negative group, 31 cases)7.
Statistical
analysis:
The differences of the clinicopathological characteristics and multimodal
MRI quantitative parameters(the intratumoral parameters were expressed by “-in”
and the peritumoral parameters were expressed by “-per”) between the positive
HER-2 group and the negative HER-2 group were analyzed by Shapiro Wilk-test,
Chi Square-test, student’s T-test, and Mann Whitney U-test of two independent samples.
The parameters with statistically significant differences between the two
groups were formed into logistic regression model, and the diagnostic efficacy
of these models were analyzed by ROC curves. ICC
test was applied to verify the intergroup consistency, and paired t-test or
Wilcoxon rank sum test were used to compare the differences between objective
scores for image quality. IBM SPSS
Statistics 25 was used for statistical analyses at the bilateral 5%
significance level, and P<0.05 indicated that the differences were
statistically significant. All drawings were done on
MedCalc statistical software(version 20.02, Belgium) and GraphPad Prism
software(version 9.51, Boston).Results
The amount of breast cancer patients was 47 with positive pathologic
results were included in our study. The values of IVIM-ADC-in, IVIM-ADC-per, IVIM-Dt-in,
IVIM-Dt-per, MUSE-ADC-per and MUSE-Dt-per in the HER-2 positive group were
higher than those in the negative group, while values of MUSE-Dp-per were lower
than those in the negative group, with statistical significance (P<
0. 05).The combination of MUSE-ADC-per, MUSE-Dt-per and MUSE-Dp-per had an AUC
of 0.794 (P=0. 002), while the combination of IVIM-ADC-in, IVIM-Dt-in,
IVIM-Dt-per and IVIM-ADC-per had an AUC of 0.797(P=0.001).
The SNR of MUSE was higher than that of IVIM b
was equal to 0 and 800 s/mm2(P=0.097, P=0.472).Discussion
According to our analysis, the reason why the efficacy of IVIM model
was better than that of MUSE-IVIM may be relevant to the sample size, and the
IVIM model contained intratumoral information, which made the heterogeneity of
breast cancer tumors more prominent possibly. MUSE had an higher SNR than IVIM,
which was similar to other studies8. In this study, the scanning time of IVIM
was shorter than that of MUSE-IVIM.Conclusion
Statistical difference in the value of IVIM and MUSE-IVIM parameters
was found between HER-2 expression in breast carcinoma. This may indicate the
potential to provide a surrogate measure of HER-2 expression through
noninvasive imaging tools.Acknowledgements
The authors would
like to thank Dr. Yuhui Xiong for his
contribution.References
- Granzier R W Y, Ibrahim A, Primakov S P, et al. MRI-based radiomics
analysis for the pretreatment prediction of pathologic complete tumor response
to neoadjuvant systemic therapy in breast cancer patients: a multicenter
study[J]. Cancers, 2021, 13(10): 2447.
- Ma W, Zhao Y, Ji Y, et al. Breast cancer molecular subtype prediction by
mammographic radiomic features[J]. Academic radiology, 2019, 26(2): 196-201.
- Bitencourt A G V, Gibbs P, Saccarelli C R, et al. MRI-based machine
learning radiomics can predict HER2 expression level and pathologic response
after neoadjuvant therapy in HER2 overexpressing breast cancer[J]. Ebio Medicine,
2020, 61.
- Xu Q, Chen S, Hu Y, et al. Landscape of immune microenvironment under
immune cell infiltration pattern in breast cancer[J]. Frontiers in immunology,
2021, 12: 711433.
- Kang H S, Kim J Y, Kim J J, et al. Diffusion kurtosis MR imaging of
invasive breast cancer: correlations with prognostic factors and molecular
subtypes[J]. Journal of Magnetic Resonance Imaging, 2022, 56(1): 110-120.
- Chen N, Guidon A, Chang H C, et al. A robust multi-shot scan strategy
for high-resolution diffusion weighted MRI enabled by multiplexed
sensitivity-encoding (MUSE)[J]. Neuroimage, 2013, 72: 41-47.
- Wolff A C, Hammond M E H, Hicks D G, et al. Recommendations for human
epidermal growth factor receptor 2 testing in breast cancer: American Society
of Clinical Oncology/College of American Pathologists clinical practice
guideline update[J]. Archives of Pathology and Laboratory Medicine, 2014,
138(2): 241-256.
- Daimiel Naranjo I, Lo Gullo R, Morris E A, et al.
High-spatial-resolution multishot multiplexed sensitivity-encoding
diffusion-weighted imaging for improved quality of breast images and
differentiation of breast lesions: a feasibility study[J]. Radiology: Imaging
Cancer, 2020, 2(3): e190076.
-
Kim Y Y, Kim M J, Gho S M, et al. Comparison of multiplexed sensitivity
encoding and single-shot echo-planar imaging for diffusion-weighted imaging of
the liver[J]. European Journal of Radiology, 2020, 132: 109292.