Advances in liver US, CT, and MRI: moving toward the future

Metabolic-associated fatty liver voxel-based quantification on CT images using a contrast adapted automatic tool

BACKGROUND & AIMS

Metabolic-dysfunction associated fatty liver disease (MAFLD) is highly prevalent and can lead to liver complications and comorbidities, with non-invasive tests such as vibration-controlled transient elastography (VCTE) and invasive liver biopsies being used for diagnosis The aim of the present study was to develop a new fully automatized method for quantifying the percentage of fat in the liver based on a voxel analysis on computed tomography (CT) images to solve previously unconcluded diagnostic deficiencies either in contrast (CE) or non-contrast enhanced (NCE) assessments.

METHODS

Liver and spleen were segmented using nn-UNet on CE- and NCE-CT images. Radiodensity values were obtained for both organs for defining the key benchmarks for fatty liver assessment: liver mean, liver-to-spleen ratio, liver-spleen difference, and their average. VCTE was used for validation. A classification task method was developed for detection of suitable patients to fulfill maximum reproducibility across cohorts and highlight subjects with other potential radiodensity-related diseases.

RESULTS

Best accuracy was attained using the average of all proposed benchmarks being the liver-to-spleen ratio highly useful for CE and the liver-to-spleen difference for NCE. The proposed whole-organ automatic segmentation displayed superior potential when compared to the typically used manual region-of-interest drawing as it allows to accurately obtain the percent of fat in liver, among other improvements. Atypical patients were successfully stratified through a function based on biochemical data.

CONCLUSIONS

The developed method tackles the current drawbacks including biopsy invasiveness, and CT-related weaknesses such as lack of automaticity, dependency on contrast agent, no quantification of the percentage of fat in liver, and limited information on region-to-organ affectation. We propose this tool as an alternative for individualized MAFLD evaluation by an early detection of abnormal CT patterns based in radiodensity whilst abording detection of non-suitable patients to avoid unnecessary exposure to CT radiation. Furthermore, this work presents a surrogate aid for assessing fatty liver at a primary assessment of MAFLD using elastography data.

In vitro blood sample assessment: investigating correlation of laboratory hemoglobin and spectral properties of dual-energy CT measurements (ρ/Z)

OBJECTIVES

Our study comprised a single-center retrospective in vitro correlation between spectral properties, namely ρ/Z values, derived from scanning blood samples using dual-energy computed tomography (DECT) with the corresponding laboratory hemoglobin/hematocrit (Hb/Hct) levels and assessed the potential in anemia-detection.

METHODS

DECT of 813 patient blood samples from 465 women and 348 men was conducted using a standardized scan protocol. Electron density relative to water (ρ or rho), effective atomic number (Zeff), and CT attenuation (Hounsfield unit) were measured.

RESULTS

Positive correlation with the Hb/Hct was shown for ρ (r-values 0.37-0.49) and attenuation (r-values 0.59-0.83) while no correlation was observed for Zeff (r-values -0.04 to 0.08). Significant differences in attenuation and ρ values were detected for blood samples with and without anemia in both genders (p value < 0.001) with area under the curve ranging from 0.7 to 0.95. Depending on the respective CT parameters, various cutoff values for CT-based anemia detection could be determined.

CONCLUSION

In summary, our study investigated the correlation between DECT measurements and Hb/Hct levels, emphasizing novel aspects of ρ and Zeff values. Assuming that quantitative changes in the number of hemoglobin proteins might alter the mean Zeff values, the results of our study show that there is no measurable correlation on the atomic level using DECT. We established a positive in vitro correlation between Hb/Hct values and ρ. Nevertheless, attenuation emerged as the most strongly correlated parameter with identifiable cutoff values, highlighting its preference for CT-based anemia detection.

CLINICAL RELEVANCE STATEMENT

By scanning multiple blood samples with dual-energy CT scans and comparing the measurements with standard laboratory blood tests, we were able to underscore the potential of CT-based anemia detection and its advantages in clinical practice.

KEY POINTS

Prior in vivo studies have found a correlation between aortic blood pool and measured hemoglobin and hematocrit. Hemoglobin and hematocrit correlated with electron density relative to water and attenuation but not Zeff. Dual-energy CT has the potential for additional clinical benefits, such as CT-based anemia detection.

Cross-sectional imaging after pancreatic surgery: The dialogue between the radiologist and the surgeon

Pancreatic surgery is nowadays considered one of the most complex surgical approaches and not unscathed from complications. After the surgical procedure, cross-sectional imaging is considered the non-invasive reference standard to detect early and late compilations, and consequently to address patients to the best management possible. Contras-enhanced computed tomography (CECT) should be considered the most important and useful imaging technique to evaluate the surgical site. Thanks to its speed, contrast, and spatial resolution, it can help reach the final diagnosis with high accuracy. On the other hand, magnetic resonance imaging (MRI) should be considered as a second-line imaging approach, especially for the evaluation of biliary findings and late complications. In both cases, the radiologist should be aware of protocols and what to look at, to create a robust dialogue with the surgeon and outline a fitted treatment for each patient.

Development of a Novel Contrast-Enhanced Ultrasound-Based Nomogram for Superficial Lymphadenopathy Differentiation: Postvascular Phase Value

OBJECTIVE

The aim of this study was to develop and prospectively validate a prediction model for superficial lymphadenopathy differentiation using Sonazoid contrast-enhanced ultrasound (CEUS) combined with ultrasound (US) and clinical data.

METHODS

The training cohort comprised 260 retrospectively enrolled patients with 260 pathological lymph nodes imaged between January and December 2020. Two clinical US-CEUS models were created using multivariable logistic regression analysis and compared using receiver operating characteristic curve analysis: Model 1 included clinical and US characteristics; Model 2 included all confirmed predictors, including CEUS characteristics. Feature contributions were evaluated using the SHapley Additive exPlanations (SHAP) algorithm. Data from 172 patients were prospectively collected between January and May 2021 for model validation.

RESULTS

Age, tumor history, long-axis diameter of lymph node, blood flow distribution, echogenic hilus, and the mean postvascular phase intensity (MPI) were identified as independent predictors for malignant lymphadenopathy. The area under the curve (AUC), sensitivity, specificity, and accuracy of MPI alone was 0.858 (95% confidence interval [CI], 0.817-0.891), 86.47%, 74.55%, and 81.2%, respectively. Model 2 had an AUC of 0.919 (95% CI, 0.879-0.949) and good calibration in training and validation cohorts. The incorporation of MPI significantly enhanced diagnostic capability (p < 0.0001 and p = 0.002 for training and validation cohorts, respectively). Decision curve analysis indicated Model 2 as the superior diagnostic tool. SHAP analysis highlighted MPI as the most pivotal feature in the diagnostic process.

CONCLUSION

The employment of our straightforward prediction model has the potential to enhance clinical decision-making and mitigate the need for unwarranted biopsies.

Ultrasound-Derived Fat Fraction for Hepatic Steatosis Assessment: Prospective Study of Agreement With MRI PDFF and Sources of Variability in a Heterogeneous Population

Background: Metabolic dysfunction-associated steatotic liver disease is a growing global public health concern. Quantitative ultrasound measurements, such as ultrasound-derived fat fraction (UDFF), could provide noninvasive, cost-effective, and portable steatosis evaluation. Objective: To evaluate utility of UDFF for steatosis assessment using PDFF as reference in patients undergoing liver MRI for heterogeneous indications, and to assess UDFF variability. Methods: This prospective study included a primary analysis of 187 patients (mean age, 53.8 years; 112 men, 75 women) who underwent 3-T liver MRI for any clinical indication from December 2020 to July 2021. Patients underwent investigational proton-density fat fraction (PDFF) measurement using MR spectroscopy, and investigational ultrasound with UDFF calculation (mean of 5 intercostal measurements) within 1 hour after MRI. In a subanalysis, 21 of these patients underwent additional UDFF measurements 1, 3, and 5 hours after meal consumption. The study also included repeatability and reproducibility (R&R) analysis of 30 patients (mean age, 26.3 years; 11 men, 20 women) who underwent clinical abdominal ultrasound between November 2022 and January 2023; in these patients, three operators sequentially performed UDFF measurements. Results: In primary analysis, UDFF and PDFF showed intraclass correlation coefficient (ICC) of 0.79. In Bland-Altmananalysis, UDFF and PDFF showed mean difference of 1.5% (95% CI, 0.6-2.4%), with 95% limits of agreement from -11.0% to 14.0%. UDFF exhibited AUC for detecting PDFF at historic thresholds of ≥6.5%, ≥17.4%, and ≥22.1% of 0.90, 0.95, and 0.95, respectively. In subanalysis, mean UDFF was not significantly different across time points with respect to meal consumption (p=.21). In R&R analysis, ICC for intraoperator repeatability ranged from 0.98 to 0.99, and for interoperator reproducibility from 0.90 to 0.96. Visual assessment of patient-level data plots indicated increasing variability of mean UDFF measurements across operators, and of intercostal measurements within individual patients, with increasing steatosis. Conclusion: UDFF showed robust agreement with PDFF, diagnostic performance for steatosis grades, as well as intraoperator repeatability and interoperator reproducibility. Nonetheless, UDFF exhibited bias toward slightly larger values versus PDFF, intraoperator and interoperator variation increased with increasing steatosis. Clinical Impact: UDFF shows promise for steatosis assessment across diverse populations, although continued optimization remains warranted.

False Liver Metastasis by Positron Emission Tomography/Computed Tomography Scan after Chemoradiotherapy for Esophageal Cancer-Potential Overstaged Pitfalls of Treatment

In patients with esophageal cancer undergoing neoadjuvant chemoradiotherapy (nCRT), subsequent restaging with F-18-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) can reveal the presence of interval metastases, such as liver metastases, in approximately 10% of cases. Nevertheless, it is not uncommon in clinical practice to observe focal FDG uptake in the liver that is not associated with liver metastases but rather with radiation-induced liver injury (RILI), which can result in the overstaging of the disease. Liver radiation damage is also a concern during distal esophageal cancer radiotherapy due to its proximity to the left liver lobe, typically included in the radiation field. Post-CRT, if FDG activity appears in the left or caudate liver lobes, a thorough investigation is needed to confirm or rule out distant metastases. The increased FDG uptake in liver lobes post-CRT often presents a diagnostic dilemma. Distinguishing between radiation-induced liver disease and metastasis is vital for appropriate patient management, necessitating a combination of imaging techniques and an understanding of the factors influencing the radiation response. Diagnosis involves identifying new foci of hepatic FDG avidity on PET/CT scans. Geographic regions of hypoattenuation on CT and well-demarcated regions with specific enhancement patterns on contrast-enhanced CT scans and MRI are characteristic of radiation-induced liver disease (RILD). Lack of mass effect on all three modalities (CT, MRI, PET) indicates RILD. Resolution of abnormalities on subsequent examinations also helps in diagnosing RILD. Moreover, it can also help to rule out occult metastases, thereby excluding those patients from further surgery who will not benefit from esophagectomy with curative intent.

Recent advances in three-dimensional ultrasound virtual cystoscopy in modeling and local staging for urothelial carcinoma with histopathological correlation: a cohort prospective study

Background

Bladder urothelial carcinoma is an alarming urologic malignancy. Complex factors like modelling and local staging can affect treatment strategy. However, local staging, particularly the muscle invasion status, significantly influences decisions regarding treatment strategies. Therefore, this study aims to evaluate the novel advances of three-dimensional (3D) ultrasound (US) imaging to assess local staging in comparison with conventional cystoscopy.

Methods

Forty-three patients with painless haematuria and conventional cystoscopy findings of bladder mass underwent 3D US virtual cystoscopy. All specimens from conventional cystoscopy were processed histologically.

Results

Out of 43 participants, 18 (41.9%) patients proved to have invasive urothelial carcinoma by histopathology. The 3D US had a sensitivity of 97.5% and a specificity of 100%; however conventional cystoscopy was accurate in only 53.5% of the studied cases. Furthermore, in the case of malignant ulcers, mural extension into both the submucosal and the muscle layers was more readily appreciated in multiplanar images.

Conclusion

3D US updates are promising for use in bladder tumour modelling and local staging; however, they can be of value in evaluating mural and extramural tumour extent and have proven accuracy.

Abbreviated magnetic resonance imaging protocols in oncology: improving accessibility in precise diagnostics

Cancer, as the second leading cause of death in the world, is one of the major public health concerns today. Accurate diagnosis and prompt initiation of adequate treatment are of key importance for prognosis. Abbreviated magnetic resonance protocols (AMRI) are promising techniques based on magnetic resonance imaging (MRI) protocols that shorten acquisition time without significant loss of examination quality. Faster protocols that focus on detection of suspicious lesions with most precise sequences, can contribute to comparable diagnostic performance of a full MRI protocol. The purpose of this article was to review the current application of AMRI protocols in several oncological diseases.

New microvascular ultrasound techniques: abdominal applications

Microvascular ultrasound (MVUS) is a new ultrasound technique that allows the detection of slow-velocity flow, providing the visualization of the blood flow in small vessels without the need of intravenous contrast agent administration. This technology has been integrated in the most recent ultrasound equipment and applied for the assessment of vascularization. Compared to conventional color Doppler and power Doppler imaging, MVUS provides higher capability to detect intralesional flow. A growing number of studies explored the potential applications in hepatobiliary, genitourinary, and vascular pathologies. Different flow patterns can be observed in hepatic and renal focal lesions providing information on tumor vascularity and improving the differential diagnosis. This article aims to provide a detailed review on the current evidences and applications of MVUS in abdominal imaging.

Prognostic Value of Liver Fibrotic Markers in Patients With Heart Failure

Several liver fibrotic markers are associated with prognosis in patients with heart failure (HF). However, the optimal markers for outcome prediction remain unclear. This study aimed to simultaneously investigate the prognostic value of liver fibrotic markers and the associations between these markers and clinical parameters in patients with HF without organic liver disease. We prospectively examined 211 consecutive patients with chronic HF between April 2018 and August 2021, excluding those with organic liver disease, using liver magnetic resonance imaging and ultrasound. A total of 7 representative liver fibrotic markers were measured in all patients. The primary outcome of interest was the composite of all-cause death and hospitalization for worsening HF. During a median follow-up period of 747 (interquartile range 465 to 1,042) days, the primary outcome occurred in 45 patients. Patients with higher hyaluronic acid and type III procollagen N-terminal peptide (P-III-P) levels showed a significantly higher incidence of the primary outcome than those without (p <0.001 and p = 0.005, respectively). The multivariable Cox regression analysis revealed that hyaluronic acid and P-III-P levels were independently associated with the risk of adverse events (hazard ratio 1.84, 95% confidence interval 1.18 to 2.87 and hazard ratio 2.89, 95% confidence interval 1.32 to 6.34, respectively) even after adjustment for a mortality prediction model, whereas the other 5 markers were not associated with the primary outcome. In conclusion, among the representative liver fibrotic markers, hyaluronic acid and P-III-P might be the optimal markers for outcome prediction in patients with HF.

Medical Radiology: Current Progress

Recently, medical radiology has undergone significant improvements in patient management due to advancements in image acquisition by the last generation of machines, data processing, and the integration of artificial intelligence. In this way, cardiovascular imaging is one of the fastest-growing radiological subspecialties. In this study, a compressive review was focused on addressing how and why CT and MR have gained a I class indication in most cardiovascular diseases, and the potential impact of tissue and functional characterization by CT photon counting, quantitative MR mapping, and 4-D flow. Regarding rectal imaging, advances in cancer imaging using diffusion-weighted MRI sequences for identifying residual disease after neoadjuvant chemoradiotherapy and [18F] FDG PET/MRI were provided for high-resolution anatomical and functional data in oncological patients. The results present a large overview of the approach to the imaging of diffuse and focal liver diseases by US elastography, contrast-enhanced US, quantitative MRI, and CT for patient risk stratification. Italy is currently riding the wave of these improvements. The development of large networks will be crucial to create high-quality databases for patient-centered precision medicine using artificial intelligence. Dedicated radiologists with specific training and a close relationship with the referring clinicians will be essential human factors.

Imaging of Hepatobiliary Cancer

The liver and biliary tree are common sites of primary and secondary malignancies. MRI followed by CT is the mainstay for the imaging characterization of these malignancies with the dynamically acquired contrast enhanced phases being the most important for diagnosis. The liver imaging reporting and data system classification provides a useful framework for reporting lesions in patents with underlying cirrhosis or who are at high risk for developing hepatocellular carcinoma. Detection of metastases is improved with the use of liver specific MRI contrast agents and diffusion weighted sequences. Aside from hepatocellular carcinoma, which is often diagnosed noninvasively, other primary hepatobiliary tumors may require biopsy for definite diagnosis, especially when presenting with nonclassic imaging findings. In this review, we examine the imaging findings of common and less common hepatobiliary tumors.

Radiomics in colorectal cancer patients

The main therapeutic options for colorectal cancer are surgical resection and adjuvant chemotherapy in non-metastatic disease. However, the evaluation of the overall adjuvant chemotherapy benefit in patients with a high risk of recurrence is challenging. Radiological images can represent a source of data that can be analyzed by using automated computer-based techniques, working on numerical information coded within Digital Imaging and Communications in Medicine files: This image numerical analysis has been named "radiomics". Radiomics allows the extraction of quantitative features from radiological images, mainly invisible to the naked eye, that can be further analyzed by artificial intelligence algorithms. Radiomics is expanding in oncology to either understand tumor biology or for the development of imaging biomarkers for diagnosis, staging, and prognosis, prediction of treatment response and diseases monitoring and surveillance. Several efforts have been made to develop radiomics signatures for colorectal cancer patient using computed tomography (CT) images with different aims: The preoperative prediction of lymph node metastasis, detecting BRAF and RAS gene mutations. Moreover, the use of delta-radiomics allows the analysis of variations of the radiomics parameters extracted from CT scans performed at different timepoints. Most published studies concerning radiomics and magnetic resonance imaging (MRI) mainly focused on the response of advanced tumors that underwent neoadjuvant therapy. Nodes status is the main determinant of adjuvant chemotherapy. Therefore, several radiomics model based on MRI, especially on T2-weighted images and ADC maps, for the preoperative prediction of nodes metastasis in rectal cancer has been developed. Current studies mostly focused on the applications of radiomics in positron emission tomography/CT for the prediction of survival after curative surgical resection and assessment of response following neoadjuvant chemoradiotherapy. Since colorectal liver metastases develop in about 25% of patients with colorectal carcinoma, the main diagnostic tasks of radiomics should be the detection of synchronous and metachronous lesions. Radiomics could be an additional tool in clinical setting, especially in identifying patients with high-risk disease. Nevertheless, radiomics has numerous shortcomings that make daily use extremely difficult. Further studies are needed to assess performance of radiomics in stratifying patients with high-risk disease.

Real-Time Deep Recognition of Standardized Liver Ultrasound Scan Locations

Liver ultrasound (US) plays a critical role in diagnosing liver diseases. However, it is often difficult for examiners to accurately identify the liver segments captured in US images due to patient variability and the complexity of US images. Our study aim is automatic, real-time recognition of standardized US scans coordinated with reference liver segments to guide examiners. We propose a novel deep hierarchical architecture for classifying liver US images into 11 standardized US scans, which has yet to be properly established due to excessive variability and complexity. We address this problem based on a hierarchical classification of 11 US scans with different features applied to individual hierarchies as well as a novel feature space proximity analysis for handling ambiguous US images. Experiments were performed using US image datasets obtained from a hospital setting. To evaluate the performance under patient variability, we separated the training and testing datasets into distinct patient groups. The experimental results show that the proposed method achieved an F1-score of more than 93%, which is more than sufficient for a tool to guide examiners. The superior performance of the proposed hierarchical architecture was demonstrated by comparing its performance with that of non-hierarchical architecture.

The application of abbreviated MRI protocols in malignant liver lesions surveillance

Cancer is one of the leading public health problems globally. Since time is of the essence in oncology, the sooner an accurate diagnosis is made, the better the prognosis for patients. There is a growing need to find a flawless and fast imaging method for cancer detection, but also for its evaluation during treatment. In this respect, the possibilities and novelties of magnetic resonance imaging are particularly promising. Abbreviated magnetic resonance imaging (AMRI) protocols have aroused universal interest as a compromise between scanning time reduction and preservation of image quality. Shorter protocols focused on the detection of suspicious lesions with the most sensitive sequences could provide a diagnostic performance similar to the one of the standard protocol. The purpose of this article is to review the ongoing accomplishments in the use of AMRI protocols in liver metastases and HCC detection.

Liver involvement in patients with COVID-19 infection: A comprehensive overview of diagnostic imaging features

During the first wave of the pandemic, coronavirus disease 2019 (COVID-19) infection has been considered mainly as a pulmonary infection. However, different clinical and radiological manifestations were observed over time, including involvement of abdominal organs. Nowadays, the liver is considered one of the main affected abdominal organs. Hepatic involvement may be caused by either a direct damage by the virus or an indirect damage related to COVID-19 induced thrombosis or to the use of different drugs. After clinical assessment, radiology plays a key role in the evaluation of liver involvement. Ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) may be used to evaluate liver involvement. US is widely available and it is considered the first-line technique to assess liver involvement in COVID-19 infection, in particular liver steatosis and portal-vein thrombosis. CT and MRI are used as second- and third-line techniques, respectively, considering their higher sensitivity and specificity compared to US for assessment of both parenchyma and vascularization. This review aims to the spectrum of COVID-19 liver involvement and the most common imaging features of COVID-19 liver damage.

Non-invasive biomarkers for liver inflammation in non-alcoholic fatty liver disease: present and future

Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease (NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its dynamic nature and poor correlation with liver biochemical markers. Liver histology keeps its role as the standard tool, yet it is well-known for substantial sampling, intraobserver, and interobserver variability. Serum proinflammatory cytokines and apoptotic markers, namely cytokeratin-18, are well-studied with reasonable accuracy, whereas serum metabolomics and lipidomics have been adopted in some commercially available diagnostic models. Ultrasound and computed tomography imaging techniques are attractive due to their wide availability; yet their accuracies may not be comparable with magnetic resonance imaging-based tools. Machine learning and deep learning models, be they supervised or unsupervised learning, are promising tools to identify various subtypes of NAFLD, including those with dominating liver inflammation, contributing to sustainable care pathways for NAFLD.

Exosomal RBP4 potentiated hepatic lipid accumulation and inflammation in high-fat-diet-fed mice by promoting M1 polarization of Kupffer cells

Exosomes containing various biological cargoes have potential to be novel diagnostic biomarkers for metabolic diseases. In this study, retinol-binding protein 4 (RBP4) was found to be enriched in serum exosomes, and its increased levels could be considered as an independent risk factor for the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Exosomal RBP4 (exo-RBP4), primarily derived from hepatocytes, significantly enhanced the M1-like polarization of Kupffer cells (KCs) via promoting the activation of NOX2 and NF-κB and reactive oxygen species (ROS) accumulation, resulting in the over-production of inflammatory cytokines including TNF-α. Subsequently, those excess cytokines remarkably increased the levels of intracellular free fatty acid uptake and lipogenesis-related genes (FAS and SREBP-1c) but decreased fatty acid degradation-related genes (CPT-1 and PPARα) in palmitic acid-treated LO2 cells. More notably, TNF-α significantly elevated RBP4 transcription by activating STAT3 in hepatocytes, playing a positive role in NAFLD development. Intravenous injection with RBP4 (50 μg/kg) potentiated hepatic lipid accumulation, M1-type KC proportion, and serum pro-inflammatory cytokine levels in the hepatic tissues of high-fat-diet-fed mice. Collectively, these data indicated that exo-RBP4 converted KCs to M1 subtype by mediating the NOX2/ROS/NF-κB pathway, subsequently promoting de novo lipogenesis in hepatocytes by TNF-α secretion to activate the JAK2/STAT3 signaling pathway. Therefore, this study uncovered a novel intercellular communication between the inflammatory microenvironment and lipid metabolism for fostering NAFLD progression and found the potential of exo-RBP4 as a novel diagnostic biomarker and therapeutic target for NAFLD.

Imaging of metabolic and overload disorders in tissues and organs

Metabolic and overload disorders are a heterogeneous group of relatively uncommon but important diseases. While imaging plays a key role in the early detection and accurate diagnosis in specific organs with a pivotal role in several metabolic pathways, most of these diseases affect different tissues as part of a systemic syndromes. Moreover, since the symptoms are often vague and phenotypes similar, imaging alterations can present as incidental findings, which must be recognized and interpreted in the light of further biochemical and histological investigations. Among imaging modalities, MRI allows, thanks to its multiparametric properties, to obtain numerous information on tissue composition, but many metabolic and accumulation alterations require a multimodal evaluation, possibly using advanced imaging techniques and sequences, not only for the detection but also for accurate characterization and quantification. The purpose of this review is to describe the different alterations resulting from metabolic and overload pathologies in organs and tissues throughout the body, with particular reference to imaging findings.

Comparison of reader agreement, correlation with liver biopsy, and time-burden sampling strategies for liver proton density fat fraction measured using magnetic resonance imaging in patients with obesity: a secondary cross-sectional study

Background

The magnetic resonance imaging (MRI)-based proton density fat fraction (PDFF) has become popular for quantifying liver fat content. However, the variability of the region-of-interest (ROI) sampling strategy may result in a lack of standardisation of this technology. In an effort to establish an accurate and effective PDFF measurement scheme, this study assessed the pathological correlation, the reader agreement, and time-burden of different sampling strategies with variable ROI size, location, and number.

Methods

Six-echo spoiled gradient-recalled-echo magnitude-based fat quantification was performed for 50 patients with obesity, using a 3.0-T MRI scanner. Two readers used different ROI sampling strategies to measure liver PDFF, three times. Intra-reader and inter-reader agreement was evaluated using intra-class correlation coefficients and Bland‒Altman analysis. Pearson correlations were used to assess the correlation between PDFFs and liver biopsy. Time-burden was recorded.

Results

For pathological correlations, the correlations for the strategy of using three large ROIs in Couinaud segment 3 (S3 3L-ROI) were significantly greater than those for all sampling strategies at the whole-liver level (P < 0.05). For inter-reader agreement, the sampling strategies at the segmental level for S3 3L-ROI and using three large ROIs in Couinaud segment 6 (S6 3L-ROI) and the sampling strategies at the whole-liver level for three small ROIs per Couinaud segment (27S-ROI), one large ROI per Couinaud segment (9L-ROI), and three large ROIs per Couinaud segment (27S-ROI) had limits of agreement (LOA) < 1.5%. For intra-reader agreement, the sampling strategies at the whole-liver level for 27S-ROI, 9L-ROI, and 27L-ROI had both intraclass coefficients > 0.995 and LOAs < 1.5%. The change in the time-burden was the largest (100.80 s) when 9L-ROI was changed to 27L-ROI.

Conclusions

For hepatic PDFF measurement without liver puncture biopsy as the gold standard, and for general hepatic PDFF assessment, 9L-ROI sampling strategy at the whole-liver level should be used preferentially. For hepatic PDFF with liver puncture biopsy as the gold standard, 3L-ROI sampling strategy at the puncture site segment is recommended.