Apparent diffusion coefficient histogram in breast cancer brain metastases may predict their biological subtype and progression

Ahn, Sung Jun; Park, Mijin; Bang, Sungkyu; Cho, Eun-Seo; Suh, Sang Hyun; Lee, Jongmin

doi:10.1038/s41598-018-28315-y

“…The relationship between DWI parameters of BMs and biological markers of breast cancer was assessed in a study of 34 patients with BCBM. 38 ADC variables did not show any statistical difference between HER2 positive and HER2 negative groups. However, it was found that ADC histogram parameters (25 th percentile of the ADC histogram) are highly correlated (P<0.05) to the ER/PR status of breast cancer.…”

Section: Mri Imaging Features and Their Correlation To Bc Subtypementioning

confidence: 64%

<p>Breast Cancer Brain Metastasis: The Potential Role of MRI Beyond Current Clinical Applications</p>

Hadjipanteli

¹

,

Doolan

²

,

Kyriacou

³

et al. 2020

CMAR

View full text Add to dashboard Cite

Breast cancer brain metastasis (BCBM) represents a major clinical challenge. Can MRI help in advancements in the management of BCBM? This review discusses MRI developments and the corresponding potential advancements in BCBM management. Methods: An exhaustive literature search was undertaken to identify studies which look into the potential of MRI in BCBM management. Seven hundred and eighty-four studies published from September 1984 to May 2020 were identified. Three topics are covered where MRI is not clinically established yet: 1) the prognosis of BCBM; 2) the screening of BC patients for BCBM development, and 3) the assessment of imaging features correlated to BC subtype. Results: Thirty-six studies were considered eligible for the purposes of this review. Ongoing progress is made with the identification of different BCBM characteristics and MRI metrics that might be related to prognosis. Progress has been made with the identification of different BCBM characteristics, including BCBM location, degree of edema, white matter disruption, tumor edge sharpness, and temporal muscle thickness. A more accurate prediction of prognosis could lead to more suitable patient management and treatment. The use of MRI in BCBM screening of the high-risk breast cancer population remains a controversial subject. To date, there are no results from clinical trials; however, there is a rising number of relatively small studies that show concern on this subject and support BCBM screening. It is important to oncologists to be able to assess the tumor subtype non-invasively. MRI features, which have shown some correlation with subtype, include the number of tumors, location, and their distribution in the brain. Advanced tools and metrics have been produced to carry out radiological characteristics analysis on MRI images. Assessing MRI features in more detail could provide a more personalized management of patients. Conclusion: Developments in the use of MRI have the potential to improve BCBM management.

show abstract

“…However, the procedure for ADC measurements in breast lesions has not been standardized, and size and positioning of the region of interest (ROI) affect both the ADC levels and reproducibility of the measurements [7]. The ADC measurements in the previous study were mostly based on traditional 2D regions of interest (ROIs) manually drawn from a single representative slice of the breast lesion, which might limit these ADC measurements in their ability to reflect whole tumour characteristics [4,[8][9][10][11]. Assessments with whole volume histogram analyses of the ADC might provide more reliable results to reflect the biological characteristics of the heterogeneous breast lesions [3,[8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index

Guo

¹

,

Kong

²

,

Li

³

et al. 2021

BioMed Research International

View full text Add to dashboard Cite

Objectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-67 expression in breast cancers. Methods. The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki-67 were analysed using Spearman’s correlation analysis. Results. Of the 189 breast lesions included, there were significant differences in patient age ( P < 0.001 ) and lesion size ( P = 0.006 ) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P < 0.001 ). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER-2) status (both P = 0.001 ) and estrogen receptor (ER)/progesterone receptor (PR) status ( P = 0.020 and P = 0.041 , respectively). Among all breast cancer lesions, 35 tumours in the low-proliferation group ( Ki − 67 < 14 % ) and 70 tumours in the high-proliferation group ( Ki − 67 ≥ 14 ) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki-67 status ( P = 0.007 and P < 0.001 , respectively), and there were weak correlations between ADC entropy ( r = 0.383 ) and skewness ( r = 0.209 ) and the Ki-67 index. Conclusion. The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.

show abstract

“…Their ADC min values were lower in the metastatic lesions in the ER-positive and PR-positive patients in comparison to those in lesions with negative receptors; however, this difference was not statistically significant. A statistically significant correlation was reported between ER positivity and ADC value in some studies, which was less in the ERpositive group (1,13,15,16,23), and also between PR positivity and ADC values, which was less in the PR positive group (1,15,32). The molecular diffusion of water through perfusion has an impact on the ADC value.…”

Section: █ Discussionmentioning

confidence: 90%

“…Very few studies have examined the ADC characteristics of metastatic brain lesions from various primary tumours, which might help in differentiating the origin of different brain metastases (1,7,11,14,19,24). Hayashida et al demonstrated that well-differentiated adenocarcinomas were usually hypointense, while small-and large-cell neuroendocrine carcinomas showed hyperintensity on DWI (11).…”

mentioning

confidence: 99%

Diffusion-weighted MRI of metastatic brain tumors: relation of diffusion parameters with histologic type

Ulu

¹

,

Öztürk²,

Atalay³

et al. 2021

Turkish Neurosurgery

View full text Add to dashboard Cite

AIM:To compare the diffusion properties of brain metastases as imaging biomarkers in various types of tumours, to determine their histology and origin.MATERIAL and METHODS: Magnetic Resonance Imaging (MRI) and diffusion-weighted imaging (DWI) were used to retrospectively study the data of 143 patients suffering from brain metastases. Four categories of primary tumours with metastases to the brain were included: lung carcinoma (n=102, 71.3%); breast carcinoma (n=27, 18.8%); colon carcinoma (n=8, 5.6%); and others (n=6, 4.2%). The Apparent Diffusion Coefficient (ADCmin ) values, as well as the normalised ADC ratio (nADC), were determined. The lesions on the DWI were categorised as follows: type 1, with negative findings on DWI; type 2, which were isointense with the normal cortical grey matter; type 3, which were hyperintense compared to the normal cortical grey matter. RESULTS:The diffusion type, mean ADCmin, and mean nADC showed statistically significant differences in different types of metastases. In the subgroup analysis, it was found that type 3 was the diffusion type found most extensively in the brain metastases of small cell carcinoma (SCLC) (n=52, 65.8%, p<0.000). Furthermore, the mean ADCmin and nADC values were the least for the brain metastases of the SCLC (552.0 ± 134.2 and nADC = 0.8 ± 0.1, p<0.000, respectively). The value of the mean ADCmin was low in the human epidermal growth factor receptor 2 (HER-2) negative groups than in the HER-2 positive groups at 786.8 ± 299.1 vs 844.8 ± 141.3 (p<0.006). CONCLUSION:Our findings indicated that there is a correlation between diffusion parameters as imaging biomarkers of the solid component of brain metastases of primary tumours and the tumour histology.

show abstract

Apparent diffusion coefficient histogram in breast cancer brain metastases may predict their biological subtype and progression

Cited by 15 publications

References 29 publications

<p>Breast Cancer Brain Metastasis: The Potential Role of MRI Beyond Current Clinical Applications</p>

<p>Breast Cancer Brain Metastasis: The Potential Role of MRI Beyond Current Clinical Applications</p>

Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index

Diffusion-weighted MRI of metastatic brain tumors: relation of diffusion parameters with histologic type

Contact Info

Product

Resources

About