Inter- and intra-observer variability of an anatomical landmark-based, manual segmentation method by MRI for the assessment of skeletal muscle fat content and area in subjects from the general population

Comparison of Manual vs Artificial Intelligence-Based Muscle MRI Segmentation for Evaluating Disease Progression in Patients With CMT1A

BACKGROUND AND OBJECTIVES

Intramuscular fat fraction (FF), assessed with quantitative MRI (qMRI), has emerged as one of the few responsive outcome measures in CMT1A patients. The main limitation for its use in future therapeutic trials is the time required for the manual segmentation of individual muscles. This study aimed to evaluate the accuracy and responsiveness of a fully automatic artificial intelligence (AI)-based segmentation pipeline to assess disease progression in a cohort of CMT1A patients over 1 year.

METHODS

Twenty CMT1A patients were included in this observational, prospective, longitudinal study. FF was measured twice a year apart using qMRI in the lower limbs. Individual muscle segmentation was performed fully automatically using a trained convolutional neural network with or without human quality check (QC). The corresponding results were compared with those obtained by fully manual (FM) segmentation using the Dice similarity coefficient (DSC). FF progression and its standardized response mean (SRM) were also computed in individual muscles over the single central slice and a 3D volume to define the most sensitive region of interest.

RESULTS

AI-based segmentation showed excellent DSC values (>0.90). Significant global FF progression was observed at thigh (+0.71% ± 1.28%; p = 0.016) and leg (+1.73% ± 2.88%, p = 0.007) levels, similarly to that calculated using the FM technique (p = 0.363 and p = 0.634). FF progression of each individual muscle was comparable when computed from either the central slice or the 3D volume. The best SRM value (0.70) was obtained for the FF progression computed using the AI-based technique with human QC in the 3D volume at the leg level. The time required for fully automatic segmentation using AI with a QC was 10 hours for the entire data set compared with 90 hours for the FM.

DISCUSSION

qMRI combined with AI-based segmentation can be considered as a process ready for assessing longitudinal FF changes in CMT1A patients. Given the slow FF progression at a thigh level and the large heterogeneity between muscles and individuals, FF should be quantified from a 3D volume at the leg level for longitudinal analyses. A QC performed after the AI-based segmentation is still advised given the increased SRM value.

Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach

BACKGROUND

There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of insulin resistance. With advances in artificial intelligence, automated and accurate algorithms have become feasible to fill this gap.

METHODS

In this retrospective study, we developed and tested a fully automated deep learning model using data from two prospective cohort studies (German National Cohort [NAKO] and Cooperative Health Research in the Region of Augsburg [KORA]) to quantify myosteatosis on whole-body T1-weighted Dixon magnetic resonance imaging as (1) intramuscular adipose tissue (IMAT; the current standard) and (2) quantitative skeletal muscle (SM) fat fraction (SMFF). Subsequently, we investigated the two measures for their discrimination of and association with impaired glucose metabolism beyond baseline demographics (age, sex and body mass index [BMI]) and cardiometabolic risk factors (lipid panel, systolic blood pressure, smoking status and alcohol consumption) in asymptomatic individuals from the KORA study. Impaired glucose metabolism was defined as impaired fasting glucose or impaired glucose tolerance (140-200 mg/dL) or prevalent diabetes mellitus.

RESULTS

Model performance was high, with Dice coefficients of ≥0.81 for IMAT and ≥0.91 for SM in the internal (NAKO) and external (KORA) testing sets. In the target population (380 KORA participants: mean age of 53.6 ± 9.2 years, BMI of 28.2 ± 4.9 kg/m2, 57.4% male), individuals with impaired glucose metabolism (n = 146; 38.4%) were older and more likely men and showed a higher cardiometabolic risk profile, higher IMAT (4.5 ± 2.2% vs. 3.9 ± 1.7%) and higher SMFF (22.0 ± 4.7% vs. 18.9 ± 3.9%) compared to normoglycaemic controls (all P ≤ 0.005). SMFF showed better discrimination for impaired glucose metabolism than IMAT (area under the receiver operating characteristic curve [AUC] 0.693 vs. 0.582, 95% confidence interval [CI] [0.06-0.16]; P < 0.001) but was not significantly different from BMI (AUC 0.733 vs. 0.693, 95% CI [-0.09 to 0.01]; P = 0.15). In univariable logistic regression, IMAT (odds ratio [OR] = 1.18, 95% CI [1.06-1.32]; P = 0.004) and SMFF (OR = 1.19, 95% CI [1.13-1.26]; P < 0.001) were associated with a higher risk of impaired glucose metabolism. This signal remained robust after multivariable adjustment for baseline demographics and cardiometabolic risk factors for SMFF (OR = 1.10, 95% CI [1.01-1.19]; P = 0.028) but not for IMAT (OR = 1.14, 95% CI [0.97-1.33]; P = 0.11).

CONCLUSIONS

Quantitative SMFF, but not IMAT, is an independent predictor of impaired glucose metabolism, and discrimination is not significantly different from BMI, making it a promising alternative for the currently established approach. Automated methods such as the proposed model may provide a feasible option for opportunistic screening of myosteatosis and, thus, a low-cost personalized risk assessment solution.

Development of an initial training and evaluation programme for manual lower limb muscle MRI segmentation

BACKGROUND

Magnetic resonance imaging (MRI) quantification of intramuscular fat accumulation is a responsive biomarker in neuromuscular diseases. Despite emergence of automated methods, manual muscle segmentation remains an essential foundation. We aimed to develop a training programme for new observers to demonstrate competence in lower limb muscle segmentation and establish reliability benchmarks for future human observers and machine learning segmentation packages.

METHODS

The learning phase of the training programme comprised a training manual, direct instruction, and eight lower limb MRI scans with reference standard large and small regions of interest (ROIs). The assessment phase used test-retest scans from two patients and two healthy controls. Interscan and interobserver reliability metrics were calculated to identify underperforming outliers and to determine competency benchmarks.

RESULTS

Three experienced observers undertook the assessment phase, whilst eight new observers completed the full training programme. Two of the new observers were identified as underperforming outliers, relating to variation in size or consistency of segmentations; six had interscan and interobserver reliability equivalent to those of experienced observers. The calculated benchmark for the Sørensen-Dice similarity coefficient between observers was greater than 0.87 and 0.92 for individual thigh and calf muscles, respectively. Interscan and interobserver reliability were significantly higher for large than small ROIs (all p < 0.001).

CONCLUSIONS

We developed, implemented, and analysed the first formal training programme for manual lower limb muscle segmentation. Large ROI showed superior reliability to small ROI for fat fraction assessment.

RELEVANCE STATEMENT

Observers competent in lower limb muscle segmentation are critical to application of quantitative muscle MRI biomarkers in neuromuscular diseases. This study has established competency benchmarks for future human observers or automated segmentation methods.

KEY POINTS

• Observers competent in muscle segmentation are critical for quantitative muscle MRI biomarkers. • A training programme for muscle segmentation was undertaken by eight new observers. • We established competency benchmarks for future human observers or automated segmentation methods.

Quantitative whole-body muscle MRI in idiopathic inflammatory myopathies including polymyositis with mitochondrial pathology: indications for a disease spectrum

OBJECTIVE

Inflammatory myopathies (IIM) include dermatomyositis (DM), sporadic inclusion body myositis (sIBM), immune-mediated necrotizing myopathy (IMNM), and overlap myositis (OLM)/antisynthetase syndrome (ASyS). There is also a rare variant termed polymyositis with mitochondrial pathology (PM-Mito), which is considered a sIBM precursor. There is no information regarding muscle MRI for this rare entity. The aim of this study was to compare MRI findings in IIM, including PM-Mito.

METHODS

This retrospective analysis included 41 patients (7 PM-Mito, 11 sIBM, 11 PM/ASyS/OLM, 12 IMNM) and 20 healthy controls. Pattern of muscle involvement was assessed by semiquantitative evaluation, while Dixon method was used to quantify muscular fat fraction.

RESULTS

The sIBM typical pattern affecting the lower extremities was not found in the majority of PM-Mito-patients. Intramuscular edema in sIBM and PM-Mito was limited to the lower extremities, whereas IMNM and PM/ASyS/OLM showed additional edema in the trunk. Quantitative assessment showed increased fat content in sIBM, with an intramuscular proximo-distal gradient. Similar changes were also found in a few PM-Mito- and PM/ASyS/OLM patients. In sIBM and PM-Mito, mean fat fraction of several muscles correlated with clinical involvement.

INTERPRETATION

As MRI findings in patients with PM-Mito relevantly differed from sIBM, the attribution of PM-Mito as sIBM precursor should be critically discussed. Some patients in PM/ASyS/OLM and PM-Mito group showed MR-morphologic features predominantly observed in sIBM, indicative of a spectrum from PM/ASyS/OLM toward sIBM. In some IIM subtypes, MRI may serve as a biomarker of disease severity.

Thigh muscle fat fraction is independently associated with impaired glucose metabolism in individuals with obesity

Background

The aim of this study was to address the intramuscular adipose tissue (IMAT) accumulation in the lower extremities and further detect the relationship between adipose tissue (AT) distribution in the muscle and glucose metabolism in subjects with obesity.

Methods

We conducted a cross-sectional study in 120 Chinese obese adults (80 male and 40 female) with BMI ≥ 28 kg/m2. MRI was applied to access the IMAT content in lower extremities. The oral glucose tolerance test was used to evaluate the glucose metabolism and insulin secretion in all individuals. The correlations between glucose metabolism and the fat content of the lower extremities were further assessed.

Results

Among 120 included subjects, 54 were classified as subjects with normal glucose tolerance (NGT) and 66 with impaired glucose regulation (IGR). We presented that those with IGR had higher fat accumulation in semitendinosus, adductor magnus, gracilis and sartorius than those with NGT (all P < 0.05). In sex-specific analyses, females have higher IMAT in adductor magnus than males (P < 0.001). Males with IGR had higher fat fraction of semitendinosus and sartorius than those with NGT (P = 0.020, P = 0.014, respectively). Logistic regression analyses revealed that IMAT content in semitendinosus was the independent factor of IGR in individuals with obesity after adjustment for age, gender, triglycerides, creatinine and albumin (odds ratio: 1.13, 95% CI: 1.02-1.26, P = 0.024).

Conclusions

Increased adipose tissue accumulation in thigh muscles was associated with glucose dysregulation in patients with obesity. IMAT content in semitendinosus may serve as a possible risk factor for impaired glucose metabolism.

Reliability Analysis of Vertebral Landmark Labelling on Lumbar Spine X-ray Images

Vertebral landmark labelling on X-ray images is important for objective and quantitative diagnosis. Most studies related to the reliability of labelling focus on the Cobb angle, and it is difficult to find studies describing landmark point locations. Since points are the most fundamental geometric feature that can generate lines and angles, the assessment of landmark point locations is essential. The aim of this study is to provide a reliability analysis of landmark points and vertebral endplate lines with a large number of lumbar spine X-ray images. A total of 1000 pairs of anteroposterior and lateral view lumbar spine images were prepared, and 12 manual medicine experts participated in the labelling process as raters. A standard operating procedure (SOP) was proposed by consensus of the raters based on manual medicine and provided guidelines for reducing sources of error in landmark labelling. High intraclass correlation coefficients ranging from 0.934 to 0.991 verified the reliability of the labelling process using the proposed SOP. We also presented means and standard deviations of measurement errors, which could be a valuable reference for evaluating both automated landmark detection algorithms and manual labelling by experts.

Associations of myosteatosis with disc degeneration: A 3T magnetic resonance imaging study in individuals with impaired glycaemia

BACKGROUND

Intervertebral disc degeneration (IVDD) may be linked to dysregulations of skeletal muscle glucose metabolism and fatty alterations of muscle composition (Myosteatosis). Our aim was to evaluate the different associations of magnetic resonance imaging (MRI)-based paravertebral myosteatosis with lumbar disc degeneration in individuals with impaired glucose metabolism and normoglycaemic controls.

METHODS

In total, 304 individuals (mean age: 56.3 ± 9.1 years, 53.6% male sex, mean body mass index [BMI]: 27.6 ± 4.7 kg/m² ) from a population-based cohort study who underwent 3-Tesla whole-body chemical-shift-encoded (six echo times) and T2-weighted single-shot-fast-spin-echo MRI were included. Lumbar disc degeneration was assessed at motion segments L1 to L5, categorized according to the Pfirrmann score and defined as Pfirrmann grade > 2 and/or disc bulging/herniation on at least one segment. Fat content of the autochthonous back muscles and the quadratus lumborum muscle was quantified as proton density fat fraction (PDFF_muscle ). Logistic regression models adjusted for age, sex, BMI and regular physical activity were calculated to evaluate the association between PDFF_muscle and outcome IVDD.

RESULTS

The overall prevalence of IVDD was 79.6%. There was no significant difference in the prevalence or severity distribution of IVDD between participants with or without impaired glucose metabolism (77.7% vs. 80.7%, P = 0.63 and P = 0.71, respectively). PDFF_muscle was significantly and positively associated with an increased risk for the presence of IVDD in participants with impaired glycaemia when adjusted for age, sex and BMI (PDFF_{autochthonous back muscles} : odds ratio [OR] 2.16, 95% confidence interval [CI] [1.09, 4.3], P = 0.03; PDFF_{quadratus lumborum} : OR 2.01, 95% CI [1.04, 3.85], P = 0.04). After further adjustment for regular physical activity, the results attenuated, albeit approaching statistical significance (PDFF_{autochthonous back muscles} : OR 1.97, 95% CI [0.97, 3.99], P = 0.06; PDFF_{quadratus lumborum} : OR 1.86, 95% CI [0.92, 3.76], P = 0.09). No significant associations were shown in healthy controls (PDFF_{autochthonous back muscles} : OR 0.62, 95% CI [0.34, 1.14], P = 0.13; PDFF_{quadratus lumborum} : OR 1.06, 95% CI [0.6, 1.89], P = 0.83).

CONCLUSIONS

Paravertebral myosteatosis is positively associated with intervertebral disc disease in individuals with impaired glucose metabolism, independent of age, sex and BMI. Regular physical activity may confound these associations. Longitudinal studies will help to better understand the pathophysiological role of skeletal muscle in those with concomitant disturbed glucose haemostasis and intervertebral disc disease, as well as possible underlying causal relationships.

Association of lumbar vertebral bone marrow and paraspinal muscle fat composition with intervertebral disc degeneration: 3T quantitative MRI findings from the population-based KORA study

OBJECTIVE

To assess the association of lumbar bone marrow adipose tissue fat fraction (BMAT-FF) and paraspinal muscle proton density fat fraction (PDFF) and their interplay with intervertebral disc degeneration (IVDD).

METHODS

In this retrospective cross-sectional study based on a prospective population-based cohort, BMAT-FF and PDFF of asymptomatic individuals were calculated based on 3T-MRI dual-echo and multi-echo Dixon VIBE sequences. IVDD was assessed at motion segments L1 to L5 and dichotomized based on Pfirrmann grade ≥ 4 and/or presence of other severe degenerative changes or spinal abnormalities at least at one segment. Pearson's correlation coefficients were calculated for BMAT-FF and PDFF. Univariable and multivariable logistic regression models for IVDD were calculated.

RESULTS

Among 335 participants (mean age: 56.2 ± 9.0 years, 43.3% female), the average BMI was 27.7 ± 4.5 kg/m2 and the prevalence of IVDD was high (69.9%). BMAT-FF and PDFF were significantly correlated (r = 0.31-0.34; p < 0.001). The risk for IVDD increased with higher PDFF (OR = 1.45; CI 1.03, 2.04) and BMAT-FF (OR = 1.56; CI 1.16, 2.11). Pairwise combinations of PDFF and BMAT-FF quartiles revealed a lower risk for IVDD in individuals in the lowest BMAT-FF and PDFF quartile (OR = 0.21; CI 0.1, 0.48). Individuals in the highest BMAT-FF and PDFF quartile showed an increased risk for IVDD (OR = 5.12; CI 1.17, 22.34) CONCLUSION: Lumbar BMAT-FF and paraspinal muscle PDFF are correlated and represent both independent and additive risk factors for IVDD. Quantitative MRI measurements of paraspinal myosteatosis and vertebral bone marrow fatty infiltration may serve as imaging biomarkers to assess the individual risk for IVDD.

KEY POINTS

• Fat composition of the lumbar vertebral bone marrow is positively correlated with paraspinal skeletal muscle fat. • Higher fat-fractions of lumbar vertebral bone marrow and paraspinal muscle are both independent as well as additive risk factors for intervertebral disc degeneration. • Quantitative magnetic resonance imaging measurements of bone marrow and paraspinal muscle may serve as imaging biomarkers for intervertebral disc degeneration.

Ultrasound and magnetic resonance imaging as diagnostic tools for sarcopenia in immune-mediated rheumatic diseases (IMRDs)

Sarcopenia is characterized by loss of muscle mass, altered muscle composition, fat and fibrous tissue infiltration, and abnormal innervation, especially in older individuals with immune-mediated rheumatic diseases (IMRDs). Several techniques for measuring muscle mass, strength, and performance have emerged in recent decades. The portable dynamometer and gait speed represent the most frequently used tools for the evaluation of muscle strength and physical efficiency, respectively. Aside from dual-energy, X-ray, absorptiometry, and bioelectrical impedance analysis, ultrasound (US) and magnetic resonance imaging (MRI) techniques appear to have a potential role in evaluating muscle mass and composition. US and MRI have been shown to accurately identify sarcopenic biomarkers such as inflammation (edema), fatty infiltration (myosteatosis), alterations in muscle fibers, and muscular atrophy in patients with IMRDs. US is a low-cost, easy-to-use, and safe imaging method for assessing muscle mass, quality, architecture, and biomechanical function. This review summarizes the evidence for using US and MRI to assess sarcopenia.

Population-based cohort imaging: skeletal muscle mass by magnetic resonance imaging in correlation to bioelectrical-impedance analysis

BACKGROUND

Skeletal muscle mass is subjected to constant changes and is considered a good predictor for outcome in various diseases. Bioelectrical-impedance analysis (BIA) and magnetic resonance imaging (MRI) are approved methodologies for its assessment. However, muscle mass estimations by BIA may be influenced by excess intramuscular lipids and adipose tissue in obesity. The objective of this study was to evaluate the feasibility of quantitative assessment of skeletal muscle mass by MRI as compared with BIA.

METHODS

Subjects from a population-based cohort underwent BIA (50 kHz, 0.8 mA) and whole-body MRI including chemical-shift encoded MRI (six echo times). Abdominal muscle mass by MRI was quantified as total and fat-free cross-sectional area by a standardized manual segmentation-algorithm and normalized to subjects' body height² (abdominal muscle mass indices: AMMI_MRI ).

RESULTS

Among 335 included subjects (56.3 ± 9.1 years, 56.1% male), 95 (28.4%) were obese (BMI ≥ 30 kg/m² ). MRI-based and BIA-based measures of muscle mass were strongly correlated, particularly in non-obese subjects [r < 0.74 in non-obese (P < 0.001) vs. r < 0.56 in obese (P < 0.001)]. Median AMMI_Total(MRI) was significantly higher in obese as compared with non-obese subjects (3246.7 ± 606.1 mm² /m² vs. 2839.0 ± 535.8 mm² /m² , P < 0.001, respectively), whereas the ratio AMMI_Fat-free /AMMI_Total (by MRI) was significantly higher in non-obese individuals (59.3 ± 10.1% vs. 53.5 ± 10.6%, P < 0.001, respectively). No significant difference was found regarding AMMI_{Fat-free(MRI)} (P = 0.424). In analyses adjusted for age and sex, impaired glucose tolerance and measures of obesity were significantly and positively associated with AMMI_Total(MRI) and significantly and inversely with the ratio AMMI_{Fat-free(MRI)} /AMMI_Total(MRI) (P < 0.001).

CONCLUSIONS

MRI-based assessment of muscle mass is feasible in population-based imaging and strongly correlated with BIA. However, the observed weaker correlation in obese subjects may explain the known limitation of BIA in obesity and promote MRI-based assessments. Thus, skeletal muscle mass parameters by MRI may serve as practical imaging biomarkers independent of subjects' body weight.

Pancreatic enzymes and abdominal adipose tissue distribution in new-onset prediabetes/diabetes after acute pancreatitis

BACKGROUND

New-onset prediabetes/diabetes after acute pancreatitis (NODAP) is the most common sequela of pancreatitis, and it differs from type 2 prediabetes/diabetes mellitus (T2DM).

AIM

To study the associations between circulating levels of pancreatic amylase, pancreatic lipase, chymotrypsin and fat phenotypes in NODAP, T2DM, and health.

METHODS

Individuals with NODAP (n = 30), T2DM (n = 30), and sex-matched healthy individuals (n = 30) were included. Five fat phenotypes (intra-pancreatic fat, liver fat, skeletal muscle fat, visceral fat, and subcutaneous fat) were determined using the same magnetic resonance imaging protocol and scanner magnet strength for all participants. One-way analysis of covariance, linear regression analysis, and relative importance analysis were conducted.

RESULTS

Intra-pancreatic fat deposition (IPFD) was higher in NODAP (9.4% ± 1.8%) and T2DM (9.8% ± 1.1%) compared with healthy controls (7.8% ± 1.9%) after adjusting for covariates (P = 0.003). Similar findings were observed in regards to visceral fat volume (P = 0.005), but not subcutaneous fat volume, liver fat, or skeletal muscle fat. Both IPFD (β = -2.201, P = 0.023) and visceral fat volume (β = -0.004, P = 0.028) were significantly associated with circulating levels of pancreatic amylase in NODAP, but not in T2DM or healthy individuals. Of the five fat phenotypes, IPFD explained the highest amount of variance in pancreatic amylase concentration (R² = 15.3% out of 41.2%). None of the phenotypes contributed meaningfully to the variance in pancreatic lipase or chymotrypsin.

CONCLUSION

Both NODAP and T2DM are characterized by increased IPFD and visceral fat volume. However, only NODAP is characterized by significant inverse associations between the two fat phenotypes and pancreatic amylase.

The feasibility of quantitative MRI of extra-ocular muscles in myasthenia gravis and Graves' orbitopathy

Although quantitative MRI can be instrumental in the diagnosis and assessment of disease progression in orbital diseases involving the extra-ocular muscles (EOM), acquisition can be challenging as EOM are small and prone to eye-motion artefacts. We explored the feasibility of assessing fat fractions (FF), muscle volumes and water T2 (T2_water ) of EOM in healthy controls (HC), myasthenia gravis (MG) and Graves' orbitopathy (GO) patients. FF, EOM volumes and T2_water values were determined in 12 HC (aged 22-65 years), 11 MG (aged 28-71 years) and six GO (aged 28-64 years) patients at 7 T using Dixon and multi-echo spin-echo sequences. The EOM were semi-automatically 3D-segmented by two independent observers. MANOVA and t-tests were used to assess differences in FF, T2_water and volume of EOM between groups (P < .05). Bland-Altman limits of agreement (LoA) were used to assess the reproducibility of segmentations and Dixon scans. The scans were well tolerated by all subjects. The bias in FF between the repeated Dixon scans was -0.7% (LoA: ±2.1%) for the different observers; the bias in FF was -0.3% (LoA: ±2.8%) and 0.03 cm³ (LoA: ± 0.36 cm³ ) for volume. Mean FF of EOM in MG (14.1% ± 1.6%) was higher than in HC (10.4% ± 2.5%). Mean muscle volume was higher in both GO (1.2 ± 0.4 cm³ ) and MG (0.8 ± 0.2 cm³ ) compared with HC (0.6 ± 0.2 cm³ ). The average T2_water for all EOM was 24.6 ± 4.0 ms for HC, 24.0 ± 4.7 ms for MG patients and 27.4 ± 4.2 ms for the GO patient. Quantitative MRI at 7 T is feasible for measuring FF and muscle volumes of EOM in HC, MG and GO patients. The measured T2_water was on average comparable with skeletal muscle, although with higher variation between subjects. The increased FF in the EOM in MG patients suggests that EOM involvement in MG is accompanied by fat replacement. The unexpected EOM volume increase in MG may provide novel insights into underlying pathophysiological processes.

Noninvasive, longitudinal imaging-based analysis of body adipose tissue and water composition in a melanoma mouse model and in immune checkpoint inhibitor-treated metastatic melanoma patients

Background

As cancer cachexia (CC) is associated with cancer progression, early identification would be beneficial. The aim of this study was to establish a workflow for automated MRI-based segmentation of visceral (VAT) and subcutaneous adipose tissue (SCAT) and lean tissue water (LTW) in a B16 melanoma animal model, monitor diseases progression and transfer the protocol to human melanoma patients for therapy assessment.

Methods

For in vivo monitoring of CC B16 melanoma-bearing and healthy mice underwent longitudinal three-point DIXON MRI (days 3, 12, 17 after subcutaneous tumor inoculation). In a prospective clinical study, 18 metastatic melanoma patients underwent MRI before, 2 and 12 weeks after onset of checkpoint inhibitor therapy (CIT; n = 16). We employed an in-house MATLAB script for automated whole-body segmentation for detection of VAT, SCAT and LTW.

Results

B16 mice exhibited a CC phenotype and developed a reduced VAT volume compared to baseline (B16 − 249.8 µl, − 25%; controls + 85.3 µl, + 10%, p = 0.003) and to healthy controls. LTW was increased in controls compared to melanoma mice. Five melanoma patients responded to CIT, 7 progressed, and 6 displayed a mixed response. Responding patients exhibited a very limited variability in VAT and SCAT in contrast to others. Interestingly, the LTW was decreased in CIT responding patients (− 3.02% ± 2.67%; p = 0.0034) but increased in patients with progressive disease (+ 1.97% ± 2.19%) and mixed response (+ 4.59% ± 3.71%).

Conclusion

MRI-based segmentation of fat and water contents adds essential additional information for monitoring the development of CC in mice and metastatic melanoma patients during CIT or other treatment approaches.

The Relationship between Abdominal Fat Phenotypes and Insulin Resistance in Non-Obese Individuals after Acute Pancreatitis

Both type 2 prediabetes/diabetes (T2DM) and new-onset prediabetes/diabetes after acute pancreatitis (NODAP) are characterized by impaired tissue sensitivity to insulin action. Although the outcomes of NODAP and T2DM are different, it is unknown whether drivers of insulin resistance are different in the two types of diabetes. This study aimed to investigate the associations between abdominal fat phenotypes and indices of insulin sensitivity in non-obese individuals with NODAP, T2DM, and healthy controls. Indices of insulin sensitivity (homeostasis model assessment of insulin sensitivity (HOMA-IS), Raynaud index, triglyceride and glucose (TyG) index, Matsuda index) were calculated in fasting and postprandial states. Fat phenotypes (intra-pancreatic fat, intra-hepatic fat, skeletal muscle fat, visceral fat, and subcutaneous fat) were determined using magnetic resonance imaging and spectroscopy. Linear regression and relative importance analyses were conducted. Age, sex, and glycated hemoglobin A1c were adjusted for. A total of 78 non-obese individuals (26 NODAP, 20 T2DM, and 32 healthy controls) were included. Intra-pancreatic fat was significantly associated with all the indices of insulin sensitivity in the NODAP group, consistently in both the unadjusted and adjusted models. Intra-pancreatic fat was not significantly associated with any index of insulin sensitivity in the T2DM and healthy controls groups. The variance in HOMA-IS was explained the most by intra-pancreatic fat (R² = 29%) in the NODAP group and by visceral fat (R² = 21%) in the T2DM group. The variance in the Raynaud index was explained the most by intra-pancreatic fat (R² = 18%) in the NODAP group and by visceral fat (R² = 15%) in the T2DM group. The variance in the TyG index was explained the most by visceral fat in both the NODAP group (R² = 49%) and in the T2DM group (R² = 25%). The variance in the Matsuda index was explained the most by intra-pancreatic fat (R² = 48%) in the NODAP group and by visceral fat (R² = 38%) in the T2DM group. The differing association between intra-pancreatic fat and insulin resistance can be used to differentiate NODAP from T2DM. Insulin resistance in NODAP appears to be predominantly driven by increased intra-pancreatic fat deposition.

Associations Between Cannabis Use, Abdominal Fat Phenotypes and Insulin Traits

Background

General obesity has been linked to dysregulation of the endocannabinoid system in humans. However, there is a lack of studies on the relationship between cannabis use and specific abdominal fat phenotypes. The aim was to investigate the associations between cannabis use and magnetic resonance imaging-derived fat phenotypes, as well as indices of insulin sensitivity and insulin secretion.

Methods

In this cross-sectional study, magnetic resonance imaging was used to quantify subcutaneous fat volume (SFV), visceral fat volume (VFV), intra-hepatic fat deposition (IHFD), intra-pancreatic fat deposition (IPFD) and skeletal muscle fat deposition (SMFD) by two independent observers. Insulin sensitivity was determined based on HOMA-IS, Raynaud index and Matsuda index, whereas insulin secretion was determined based on HOMA-β, insulinogenic index 30’ and insulinogenic index 60’. A validated questionnaire was used to ascertain participants’ cannabis use. Linear regression models were constructed, adjusting for demographics, glycated hemoglobin, physical activity, tobacco smoking and alcohol consumption.

Results

A total of 120 individuals were included. Cannabis use explained 9.2% of variance in IHFD, 4.4% in SMFD, 3.4% in VFV, 0.4% in SFV and 0.2% in IPFD. Regular cannabis users had significantly greater IHFD compared with never users, in both the unadjusted (P = 0.002) and all adjusted (P = 0.002; P = 0.008) analyses. The other fat phenotypes did not differ significantly between either regular or non-regular users compared with never users. Regular cannabis users had significantly greater insulin secretion (as defined by the insulinogenic index 60’) compared with never users, in both the unadjusted (P = 0.049) and all adjusted (P = 0.003; P = 0.004) analyses. Cannabis use explained 20.3% of variance in the insulinogenic index 60’, but was not significantly associated with the other indices of insulin secretion. There were no significant differences in indices of insulin sensitivity in either regular or non-regular cannabis users compared with never users.

Conclusion

Regular cannabis use may be a risk factor for non-alcoholic fatty liver disease (but not IPFD) and may alter the neuromodulation of insulin secretion. Further investigations are now warranted to elucidate the mechanisms underlying these associations.

Computed tomography-based psoas skeletal muscle area and radiodensity are poor sentinels for whole L3 skeletal muscle values

Background and aims

Computed tomography (CT)-based measurement of skeletal muscle cross-sectional area (CSA) and Hounsfield unit (HU) radiodensity are used to assess the presence of sarcopenia and myosteatosis, respectively. The validated CT-based technique involves analysis of skeletal muscle at the third lumbar vertebral (L3) level. Recently there has been increasing interest in the use of psoas muscle alone as a sentinel. However, this technique has not been extensively investigated or compared with the previous validated standard approach.

Methods

Portovenous phase CT images at the L3 level were identified retrospectively from a single institution in 150 patients who had non-emergency scans and were analysed by a single assessor using SliceOmatic software v5.0 (TomoVision, Canada). Manual segmentation based upon validated HU thresholds for skeletal muscle density was performed for all skeletal muscle, as well as the individual muscle groups. The muscle CSA and mean radiodensity of each group were compared against the whole L3 slice values.

Results

When compared with whole L3 slice CSA, anterior abdominal wall CSA had the strongest correlation (r = 0.9315, p < 0.0001) followed by paravertebral (r = 0.8948, p < 0.0001), then psoas muscle (r = 0.7041, p < 0.0001). The mean ± SD density of the psoas muscle (42 ± 8.4 HU) was significantly higher than the whole slice radiodensity (32.3 ± 9.5 HU, p < 0.0001), with paravertebral radiodensity being a more accurate estimation (34.5 ± 10.8 HU). There was a significant difference in the prevalence of myosteatosis when the density measured from the psoas was compared with that of the whole L3 skeletal muscle (27.7% vs. 66.0%, p < 0.0001).

Conclusion

Whole L3 slice CSA correlated positively with psoas muscle CSA but was subject to wide variability in results. Psoas muscle radiodensity was significantly greater than whole L3 slice density and resulted in underestimation of the prevalence of myosteatosis. Given the lack of equivalence from individual muscle groups, we recommend that further work be undertaken to investigate which muscle group, or indeed whether the gold standard of whole L3 skeletal muscle, provides the best correlation with clinical outcomes.