European Radiology: MRI Diffusion Signature Index for Noninvasive Evaluation of Histological Phenotype of Invasive Breast Cancer!

At this stage, diffusion-weighted imaging (DWI) has been widely used to diagnose and monitor neoplastic lesions in many organs
.
In order to quantify the diffusivity of tissue, the apparent diffusion coefficient (ADC) is usually calculated, and ADC maps are generated from this
.
In breast lesions, the addition of DWI sequences to conventional dynamic contrast-enhanced (DCE) MRI has shown great value in breast cancer detection and diagnosis, treatment response monitoring and prognosis prediction
.

The expression levels of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and proliferative status (Ki-67) are the main prognostic factors guiding treatment decisions in aggressive breast cancer
.
These markers are generally obtained from biopsy samples, but differences in receptor or proliferative status between biopsy and surgical specimens may occur in up to 20% of patients
.
Therefore, it is necessary to use preoperative non-invasive markers to predict histological status
.

Recent studies have proposed more advanced DWI models for the diagnosis of breast DWI, especially models sensitive to non-Gaussian diffusion (high diffusion weighting) and blood microcirculation (in vivo incoherent motion [IVIM], low diffusion weighting)
.
IVIM/non-Gaussian diffusion models provide valuable information about tissue microcirculation and microarchitecture, and potentially provide additional information to describe pathological or physiological tumor conditions beyond standard ADCs
.
However, these models require the acquisition of multiple signals over a wide range of b-values, resulting in long acquisition times and advanced post-processing, both parts of which are often incompatible with normal clinical use
.

The signature index (S-index) is an advanced DWI marker that integrates IVIM and non-Gaussian diffusion information and does not require modeling
.
The S-index reflects the similarity in diffusion signal decay between typical benign and malignant tissue signal repertoires, as well as using a set of only two key b-values
.
Studies have found that S-index and DCE MRI have equal diagnostic performance in distinguishing malignant and benign breast lesions, and improve the specificity of DCE MRI for the diagnosis of lesions
.
Furthermore, the S-index showed different trends in invasive breast cancer based on PR and HER2 expression
.

Recently, a study published in the European Radiology journal further evaluated the relationship between the S-index and important prognostic factors and molecular phenotypes of invasive breast cancer, for the preoperative noninvasive assessment of pathological classification and risk of invasive breast cancer.
Layering provides support
.

This study conducted a retrospective study of patients with invasive carcinoma from 2017 to 2021
.
All patients underwent dynamic contrast-enhanced MRI and DWI using a 3-T system
.
For DWI, the S-index was calculated using three b values ​​(0, 200 and 1500 s/mm ²
) .
On DWI, a three-dimensional ROI was manually placed over the entire tumor
.
Mean and 85th percentile S-index values ​​were compared with IHC status, proliferation rate, and molecular subtypes of lesions
.
 

The study included 153 patients (mean age, 60 ± 13 years) with a total of 160 invasive breast cancer lesions
.
Estrogen receptor positivity (mean, p = .
005; 85th percentile, p < .
001) and progesterone receptor positivity (mean, p = .
003; 85th percentile, p < .
001 ) tumors had significantly higher S-index values, while human epidermal growth factor receptor 2 (HER2)-positive tumors had significantly lower S-index values ​​(mean, p = 023; 85th percentile, p < .
001)
.
Mean and 85th percentile S-index values ​​differed significantly among breast cancer subtypes (mean, p = .
015; 85th percentile, p = .
002), and these values ​​were significantly associated with AUC for predicting IHC status 0.
64 and 0.
66 for HER2 and 0.
70 and 0.
74 for hormone receptors, respectively
.
 

Figure 50-year-old woman with acinar type A invasive ductal carcinoma
.
Axial early dynamic contrast-enhanced MRI shows a mass with irregular margins in the left breast (a, arrow)
.
Diffusion-weighted image (b = 1500) clearly shows a mass with high signal intensity (b, arrow)
.
The resulting average feature index (S-index) map for each slice (c) and 3D rendering of the entire tumor (d) was calculated at the ROI slice and voxel-by-voxel, showing a high S-index (red).
)
.
The mean S-index for this mass was 90.
4 and the 85th percentile was 105

The present study showed that quantitative diffusion MRI S-index values ​​showed a high correlation with prognostic factors in invasive breast cancer, and the mean and 85th percentile S-index values ​​could be used to predict HER2 and hormone receptor status
.
This study shows that the S-index is a simple and readily available imaging method to non-invasively assess the histological phenotype of invasive breast cancer
.

Original source:

Mariko Goto, Denis Le Bihan, Koji Sakai, et al.
The diffusion MRI signature index is highly correlated with immunohistochemical status and molecular subtype of invasive breast carcinoma.
DOI: 10.
1007/s00330-022-08562-4