Simultaneous liver steatosis, fibrosis and iron deposition quantification with mDixon quant based on radiomics analysis in a rabbit model

Radiomics and liver: Where we are and where we are headed?

Hepatic diffuse conditions and focal liver lesions represent two of the most common scenarios to face in everyday radiological clinical practice. Thanks to the advances in technology, radiology has gained a central role in the management of patients with liver disease, especially due to its high sensitivity and specificity. Since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI), radiology has been considered the non-invasive reference modality to assess and characterize liver pathologies. In recent years, clinical practice has moved forward to a quantitative approach to better evaluate and manage each patient with a more fitted approach. In this setting, radiomics has gained an important role in helping radiologists and clinicians characterize hepatic pathological entities, in managing patients, and in determining prognosis. Radiomics can extract a large amount of data from radiological images, which can be associated with different liver scenarios. Thanks to its wide applications in ultrasonography (US), CT, and MRI, different studies were focused on specific aspects related to liver diseases. Even if broadly applied, radiomics has some advantages and different pitfalls. This review aims to summarize the most important and robust studies published in the field of liver radiomics, underlying their main limitations and issues, and what they can add to the current and future clinical practice and literature.

Magnetic susceptibility and R2*-based texture analysis for evaluating liver fibrosis in chronic liver disease

PURPOSE

To explore potential feasibility of texture features in magnetic susceptibility and R2* maps for evaluating liver fibrosis.

METHODS

Thirty-one patients (median age 46 years; 22 male) with chronic liver disease were prospectively recruited and underwent magnetic resonance imaging (MRI), blood tests, and liver biopsy. Susceptibility and R2* maps were obtained using a 3-dimensional volumetric interpolated breath-hold examination sequence with a 3T MRI scanner. Texture features, including histogram, gray-level co-occurrence matrix (GLCM), gray-level dependence matrix (GLDM), gray-level run length matrix (GLRLM), gray-level size zone matrix (GLSZM), and neighboring gray tone difference matrix (NGTDM) features, were extracted. Texture features and blood test results of non-significant (Ishak-F < 3) and significant fibrosis patients (Ishak-F ≥ 3) were compared, and correlations with Ishak-F stages were analyzed. Areas under the curve (AUCs) were calculated to determine the efficacy for evaluating liver fibrosis.

RESULTS

Nine texture features of susceptibility maps and 19 features of R2* maps were significantly different between non-significant and significant fibrosis groups (all P < 0.05). Large dependence high gray-level emphasis (LDHGLE) of GLDM and long run high gray-level emphasis (LRHGLE) of GLRLM in R2* maps showed significantly negative and good correlations with Ishak-F stages (r = -0.616, P < 0.001; r = -0.637, P < 0.001). Busyness (NGTDM) in susceptibility maps, LDHGLE of GLDM and LRHGLE of GLRLM in R2* maps yield the highest AUCs (AUC = 0.786, P = 0.007; AUC = 0.807, P = 0.004; AUC = 0.819, P = 0.003).

CONCLUSION

Texture characteristics of susceptibility and R2* maps revealed possible staging values for liver fibrosis. Susceptibility and R2*-based texture analysis may be a useful and noninvasive method for staging liver fibrosis.

MRI Assessment of Renal Lipid Deposition and Abnormal Oxygen Metabolism of Type 2 diabetes Mellitus Based on mDixon-Quant

BACKGROUND

Diabetic nephropathy (DN) is the main cause of end-stage renal failure. Multiecho Dixon-based imaging utilizes chemical shift for water-fat separation that may be valuable in detecting changes both fat and oxygen content of the kidney from a single dataset.

PURPOSE

To investigate whether multiecho Dixon-based imaging can assess fat and oxygen metabolism of the kidney in a single breath-hold acquisition for patients with type 2 diabetes mellitus (DM).

STUDY TYPE

Prospective.

SUBJECTS

A total of 40 DM patients with laboratory examination of biochemical parameters and 20 age- and body mass index (BMI)-matched healthy volunteers (controls).

FIELD STRENGTH/SEQUENCE

3D multiecho Dixon gradient-echo sequence at 3.0 T.

ASSESSMENT

The DM patients were divided into two groups based on urine albumin-to-creatinine ratio (ACR): type 2 diabetes mellitus (DM, 20 patients, ACR < 30 mg/g) and diabetic nephropathy (DN, 20 patients, ACR ≥ 30 mg/g). In all subjects, fat fraction (FF) and relaxation rate (R2*) maps were derived from the Dixon-based imaging dataset, and mean values in manually drawn regions of interest in the cortex and medulla compared among groups. Associations between MRI and biochemical parameters, including β2-microglobulin, were investigated.

STATISTICAL TESTS

Kruskal-Wallis tests, Spearman correlation analysis, and receiver operating characteristic (ROC) curve analysis.

RESULTS

FF and R2* values of the renal cortex and medulla were significantly different among the three groups with control group < DM < DN (FF: control, 1.11± 0.30, 1.10 ± 0.39; DM, 1.52 ± 0.32, 1.57 ± 0.35; DN, 1.99 ± 0.66, 2.21 ± 0.59. R2*: Control, 16.88 ± 0.77, 20.70 ± 0.86; DM, 17.94 ± 0.75, 22.10 ± 1.12; DN, 19.20 ± 1.24, 23.63 ± 1.33). The highest correlation between MRI and biochemical parameters was that between cortex R2* and β2-microglobulin (r = 0.674). A medulla R2* cutoff of 21.41 seconds-1 resulted in a sensitivity of 80%, a specificity of 85% and achieved the largest area under the ROC curve (AUC) of 0.83 for discriminating DM from the controls. A cortex FF of 1.81% resulted in a sensitivity of 80%, a specificity of 100% and achieved the largest AUC of 0.83 for discriminating DM from DN.

DATA CONCLUSION

Multiecho Dixon-based imaging is feasible for noninvasively distinguishing DN, DM and healthy controls by measuring FF and R2* values.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 2.

The value of multimodal functional magnetic resonance imaging in differentiating p53abn from p53wt endometrial carcinoma

BACKGROUND

Endometrial carcinoma (EC) is the sixth most common cancer in women. P53 gene expression in patients with endometrial cancer can predict the efficacy and prognosis of patients with neoadjuvant therapy.

PURPOSE

To explore the value of multimodal magnetic resonance imaging (MRI) in differentiating p53 abnormal (p53abn) from p53 wild-type (p53wt) EC.

MATERIAL AND METHODS

Data from 47 EC patients, including 14 p53abn cases and 33 p53wt cases, were retrospectively analyzed. The preoperative MRI sequences included amide proton transfer weighted (APTw) imaging, T2 mapping, mDIXON-Quant imaging and diffusion-weighted imaging (DWI). After post-processing, APT, T2, transverse relaxation rate (R2*), fat fraction (FF) and apparent diffusion coefficient (ADC) maps were obtained. The APT, T2, R2*, FF and ADC values for lesions of the two groups of cases were measured by two observers who were blind to the pathological data.

RESULTS

The APT value and R2* value in the p53abn group were higher than those in the p53wt group, while the ADC value was lower (all P < 0.05). There was no statistically significant difference in T2 value and FF value between the two groups (all P > 0.05). The area under curve of APT, R2*, ADC and combined APT + R2*+ADC values for identification of p53abn and p53wt EC were 0.739, 0.689, 0.718 and 0.820, respectively (all P > 0.05).

CONCLUSION

APTw, mDIXON-Quant and DWI techniques can be usedfor quantitative identification of p53abn and p53wt EC. The multimodal MRI provides a new way for preoperative quantitative evaluation of EC molecular typing, which has certain clinical application value.