Accuracy of Controlled Attenuation Parameter for Assessing Liver Steatosis in Individuals With Morbid Obesity Before Bariatric Surgery

Federica Tavaglione; Antonio De Vincentis; Vincenzo Bruni; Ida Francesca Gallo; Simone Carotti; Dario Tuccinardi; Giuseppe Spagnolo; Ester Ciociola; Rosellina Margherita Mancina; Oveis Jamialahmadi; Rossella D'Alessio; Bruna Bottazzi; Silvia Manfrini; Antonio Picardi; Giuseppe Perrone; Paolo Pozzilli; Marco Caricato; Umberto Vespasiani-Gentilucci; Stefano Romeo

Disclosures

Liver International. 2022;42(2):374-383.

Abstract and Introduction

Abstract

Background & Aims: The ultrasound-based controlled attenuation parameter (CAP) is a non-invasive tool widely validated for assessing liver steatosis across different etiologies. However, few studies, with liver biopsy available, have investigated its performance in individuals with morbid obesity. Herein, we aimed to evaluate the diagnostic accuracy of CAP in participants with morbid obesity from the MAFALDA study before bariatric surgery.

Methods: A total of 120 individuals with valid examinations within three months from bariatric surgery were included. Clinical, laboratory, FibroScan® (XL probe), and liver biopsy data were collected using standardized procedures. The overall accuracy of CAP for detecting liver steatosis was estimated by the area under the receiver-operating characteristics curve (AUROC). Optimal cut-offs were chosen at points with the highest Youden index.

Results: The AUROCs of CAP for detecting S ≥ S1, S ≥ S2, and S = S3 were 0.91 (95% CI 0.86–0.97), 0.83 (95% CI 0.76–0.90), and 0.86 (95% CI 0.79–0.94), respectively. The best CAP cut-offs for S ≥ S1, S ≥ S2, and S = S3 were 300 dB/m (95% CI 275–316), 328 dB/m (95% CI 296–345), and 344 dB/m (95% CI 343–352), respectively. CAP values were independently influenced by steatosis grade (estimate 20.60, 95% CI 12.70–28.40, P = 1.05 × 10⁻⁶). The AUROC of FibroScan-AST (FAST) score for detecting progressive non-alcoholic steatohepatitis was 0.76 (95% CI 0.66–0.86).

Conclusions: In individuals with morbid obesity, CAP measured by XL probe is an accurate non-invasive tool for grading liver steatosis. Measurement of liver fat content by CAP may help identify those eligible for bariatric procedures and estimate the effect of bariatric surgery on hepatic steatosis.

Lay Summary: The ultrasound-based controlled attenuation parameter (CAP) by using the XL probe has an excellent performance for grading liver steatosis among individuals with morbid obesity.

CAP may represent an accurate tool for the non-invasive assessment of liver steatosis among individuals with morbid obesity before and after bariatric surgery.

Introduction

Non-alcoholic fatty liver disease (NAFLD) is becoming the major cause of chronic liver disease worldwide, paralleling the epidemics of obesity and type 2 diabetes. The prevalence of NAFLD in the general population is estimated to be approximately 25% but it reaches over 90% among individuals with severe obesity undergoing weight loss procedures.^[1]

NAFLD/non-alcoholic steatohepatitis (NASH) are serious obesity-related complications and their presence qualifies individuals to be eligible for bariatric surgery.^[2] Therefore, an accurate diagnosis and staging of NAFLD play an important role in the clinical management of obesity and decision-making on the most appropriate treatment modality (ie, lifestyle changes, pharmacological therapy, or bariatric surgery).

Although the stage of liver fibrosis is the main determinant of liver-related outcomes,^[3] the degree of liver fat accumulation has a crucial role in the physiopathology of NAFLD and is causally related to liver damage.^[4,5] Consistently, novel drugs under clinical investigation for the treatment of NAFLD primarily target the reduction of liver steatosis.^[6]

To date, liver biopsy represents the most accurate technique for the assessment of hepatic steatosis, necroinflammation, and fibrosis.^[7] However, this procedure is considered invasive and accompanied by a low, but not negligible, risk of complications, including hepatic bleeding, perforation of adjacent organs, and infection.^[8] Therefore, in the last years, an intensive effort has been carried out to identify reliable non-invasive diagnostic tests for NAFLD/NASH detection and to follow its course over time.

The ultrasound-based controlled attenuation parameter (CAP) is a non-invasive tool for the assessment of liver steatosis. CAP has primarily been validated among individuals with chronic liver disease due to different etiologies, including NAFLD and viral hepatitis.^[9–12]

To reduce the failure rate of transient elastography with the M probe due to high body mass index (BMI), the XL probe has been recently developed and specifically designed for individuals with overweight/obesity (skin-to-liver capsular distance ≥25 mm).^[13–15] Several studies have examined the feasibility of XL-CAP for liver steatosis among individuals with overweight/obesity.^[12,15–20] However, a handful of histologically characterized cohort studies have specifically investigated the use of CAP for assessing liver steatosis in individuals with morbid obesity.^[21–23]

The aim of this study was to evaluate the diagnostic accuracy of CAP measured by the XL probe to detect liver steatosis in participants with morbid obesity from MAFALDA, a study in which liver biopsy was available. Additionally, we assessed the performance of FibroScan-AST (FAST) score^[24] for detecting progressive NASH (NASH + NAFLD activity score ^NAS ≥ 4 + F ≥ F2) in this cohort.

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Abstract and Introduction
Methods
Results
Discussion
References

Table 1. Clinical and demographic characteristics stratified by steatosis grade
	Overall cohort (n = 120)	S0 (n = 35)	S1 (n = 46)	S2 (n = 23)	S3 (n = 16)	P value
Clinical data
Age, years	43.8 (10.1)	40.4 (9.2)	45.1 (10.3)	47 (9.7)	42.8 (10.3)	0.07
Women, n (%)	93 (78%)	34 (97%)	30 (65%)	17 (74%)	12 (75%)	0.06
BMI, kg/m²	41.0 (4.0)	40.1 (3.7)	42 (4.6)	40.4 (3.8)	41.4 (2.8)	0.25
BMI ≥45 kg/m², n (%)	20 (17%)	3 (9%)	12 (26%)	4 (17%)	1 (6%)	0.74
Waist circumference, cm	123.1 (11.4)	119.4 (10.6)	125.6 (11.7)	123.1 (12.2)	124.3 (9.5)	0.81
Hip circumference, cm	132.1 (10.0)	132.8 (7.8)	131.6 (11.6)	133.3 (11.2)	130.2 (7.5)	0.52
Waist to hip ratio	0.9 (0.9–1.0)	0.9 (0.8–0.9)	1.0 (0.9–1.0)	0.9 (0.9–1.0)	0.9 (0.9–1.0)	0.53
Systolic blood pressure, mmHg	130 (120–140)	120 (120–135)	138 (123–144)	130 (120–140)	135 (120–144)	0.23
Diastolic blood pressure, mmHg	80 (80–90)	80 (80–88)	82.5 (80–90)	90 (80–90)	80 (80–90)	0.46
Metabolic profile
Glucose, mg/dL	99 (93–108)	93 (90–98)	100 (95–111)	101 (95–104)	114 (101–127)	1.29 × 10⁻⁴
HbA1c, %	5.6 (5.3–5.9)	5.3 (5.1–5.6)	5.7 (5.4–5.9)	5.6 (5.4–5.8)	6.1 (5.7–6.4)	4.78 × 10⁻⁴
Insulin, uUI/mL	14.8 (11.2–18.8)	11.9 (7.7–14.5)	15.5 (11.9–17.7)	17.5 (14.3–20.5)	22.2 (13.9–37.4)	4.26 × 10⁻⁷
HOMA-IR	3.8 (2.8–4.9)	2.5 (1.8–3.4)	3.8 (3.1–4.5)	4.5 (3.4–5.2)	6.5 (4.2–9.3)	4.78 × 10⁻⁸
Circulating lipoproteins
Cholesterol, mg/dL	181 (31)	181 (27)	177 (32)	184 (31)	187 (34)	0.16
HDL cholesterol, mg/dL	45 (9)	49 (10)	44 (10)	44 (7)	44 (7)	0.07
LDL cholesterol, mg/dL	123 (30)	120 (32)	120 (29)	128 (31)	127 (26)	0.09
Triglycerides, mg/dL	129 (99–167)	111 (82–134)	132 (105–164)	154 (123–183)	154 (103–180)	2.21 × 10⁻⁴
Liver function tests
ALT, U/L	32 (20–45)	19 (16–27)	32 (24–44)	41 (29–60)	51 (45–72)	6.06 × 10⁻⁹
AST, U/L	26 (22–32)	20 (19.5–25)	28 (24–32)	28 (25–35)	35 (32–41)	5.85 × 10⁻⁷
ALP, U/L	69 (17)	67 (15)	70 (17)	69 (18)	73 (19)	0.43
GGT, U/L	26 (18–36)	20 (14–26)	25 (18–39)	33 (23–42)	36 (28–47)	4.81 × 10⁻³
Bilirubin, mg/dL	0.6 (0.4–0.7)	0.6 (0.4–0.7)	0.6 (0.4–0.7)	0.6 (0.5–0.9)	0.5 (0.4–0.6)	0.80
Albumin, g/dL	4.3 (0.3)	4.2 (0.2)	4.3 (0.2)	4.2 (0.3)	4.3 (0.3)	0.20
Platelets, ×10³/μL	289.0 (67.5)	304.7 (75.5)	279.6 (67.6)	287.9 (57.8)	283.1 (61.3)	0.76
INR	0.97 (0.93–1.00)	0.97 (0.95–1.00)	0.98 (0.94–1.02)	0.96 (0.92–1.02)	0.95 (0.92–0.98)	0.06
Ferritin, ng/mL	61.4 (28.4–108.0)	36.6 (20.8–64.8)	70.4 (32.4–105.2)	96.4 (42.0–140.5)	86.2 (51.8–133.5)	0.04
Comorbidities
Hypertension, n (%)	56 (47%)	6 (17%)	23 (50%)	14 (61%)	13 (81%)	1.02 × 10⁻⁴
Dyslipidemia, n (%)	67 (56%)	15 (43%)	25 (54%)	17 (74%)	10 (62%)	0.07
Type 2 diabetes, n (%)	23 (19%)	4 (11%)	9 (20%)	4 (17%)	6 (38%)	0.13
Metabolic syndrome, n (%)	86 (72%)	17 (49%)	34 (74%)	20 (87%)	15 (94%)	9.21 × 10⁻⁴
Cardiovascular disease, n (%)	4 (3%)	1 (3%)	2 (4%)	1 (4%)	0 (0%)	0.54
FibroScan
CAP, dB/m	320 (288–351)	267 (256–292)	325 (295–347)	345 (332–354)	364 (351–386)	7.39 × 10⁻¹³
LSM, kPa	5.4 (4.6–6.5)	5.1 (4.6–5.9)	5.2 (4.6–6.5)	5.6 (5–6.5)	6.4 (5.0–7.0)	0.10
Days between FibroScan® and liver biopsy	23 (20)	20 (15)	23 (19)	27 (21)	26 (28)	0.53
Liver biopsy
NASH, n (%)	54 (45%)	0 (0%)	15 (33%)	23 (100%)	16 (100%)	0.41
Progressive NASH, n (%)	23 (19%)	0 (0%)	6 (13%)	11 (48%)	6 (38%)	1.17 × 10⁻⁵
Fibrosis staging, n (%)
F0	31 (26%)	20 (57%)	9 (20%)	1 (4%)	1 (6%)	6.57 × 10⁻⁷
F1	59 (49%)	14 (40%)	25 (54%)	11 (48%)	9 (56%)
F2	27 (22%)	1 (3%)	11 (24%)	9 (39%)	6 (38%)
F3	3 (2%)	0 (0%)	1 (2%)	2 (9%)	0 (0%)
F4	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
Biopsy length, cm	1.6 (0.5)	1.6 (0.5)	1.5 (0.4)	1.8 (0.6)	1.6 (0.6)	0.48
Biopsy length ≥1.5 cm, n (%)	65 (54%)	18 (51%)	25 (54%)	15 (65%)	7 (44%)	0.84

Note: Continuous variables are shown as mean (SD) or median (IQR) as appropriate. Categorical variables are shown as number (percentage).
P values are calculated using ordinal logistic regression models adjusted for age, gender, and BMI.
P values <0.05 are considered statistically significant.
Abbreviations: ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; CAP, controlled attenuation parameter; GGT, gamma glutamyltransferase; HbA1c, haemoglobin A1c; HDL, high-density lipoprotein; INR, international normalized ratio; LDL, low-density lipoprotein; LSM, liver stiffness measurement; NASH, non-alcoholic steatohepatitis.

Table 2. Diagnostic performance of CAP for steatosis severity
	S ≥ S1 (≥5% steatosis)	S ≥ S2 (≥34% steatosis)	S = S3 (≥67% steatosis)
AUROC	0.91 (0.86–0.97)	0.83 (0.76–0.90)	0.86 (0.79–0.94)
Optimal cut-off, dB/m	300 (275–316)	328 (296–345)	344 (343–352)
Sensitivity	0.82 (0.67–0.98)	0.87 (0.67–1)	0.94 (0.75–1)
Specificity	0.89 (0.69–1)	0.73 (0.49–0.89)	0.77 (0.67–0.88)
Positive predictive value	0.95 (0.88–1)	0.60 (0.49–0.78)	0.39 (0.30–0.53)
Negative predictive value	0.67 (0.54–0.93)	0.92 (0.84–1)	0.99 (0.96–1)
False positive rate	0.11 (0–0.31)	0.27 (0.11–0.51)	0.23 (0.12–0.33)
False negative rate	0.18 (0.02–0.33)	0.13 (0–0.33)	0.06 (0–0.25)
Cut-off by Petroff et al,¹⁹ dB/m	297	317	333
Sensitivity	0.81 (0.73–0.89)	0.85 (0.72–0.95)	0.94 (0.81–1)
Specificity	0.80 (0.66–0.91)	0.67 (0.57–0.77)	0.63 (0.53–0.72)
Positive predictive value	0.91 (0.85–0.96)	0.55 (0.47–0.64)	0.28 (0.23–0.34)
Negative predictive value	0.64 (0.53–0.76)	0.90 (0.83–0.97)	0.99 (0.95–1)
False positive rate	0.20 (0.09–0.34)	0.33 (0.23–0.43)	0.38 (0.28–0.47)
False negative rate	0.19 (0.11–0.27)	0.15 (0.05–0.28)	0.06 (0–0.19)

Note: Results of the receiver operating curve (ROC) analysis are presented based on a bootstrap method (10,000 stratified bootstrap replicates). Optimal cut-offs are based on the maximal sum of sensitivity and specificity (Youden index). Numbers in brackets are 95% confidence intervals.
Abbreviations: AUROC, area under the receiver operating curve.

Table 3. Impact of covariates on CAP values
	Estimate (95% CI)	P value
Steatosis grade (0–3)	20.60 (12.70 to 28.40)	1.05 × 10⁻⁶
Age, per 10 years	2.80 (−3.41 to 9.00)	0.37
Female gender	−10.30 (−25.50 to 4.84)	0.18
BMI, per unit kg/m²	1.17 (−0.29 to 2.62)	0.12
Type 2 diabetes	−0.24 (−14.80 to 14.30)	0.97
ALT, per ln(U/L)	20.0 (−1.07 to 41.0)	0.06
AST, per ln(U/L)	−0.60 (−33.60 to 32.40)	0.97
Fibrosis stage (0–4)	1.86 (−6.58 to 10.30)	0.66
Biopsy length ≥1.5 cm	−1.15 (−12.70 to 10.40)	0.84
Pre-surgery diet >7 days	−11.0 (−23.90 to 1.82)	0.09
FibroScan® > 14 days before biopsy	6.99 (−5.63 to 19.60)	0.28

Note: Estimates with 95% CIs are calculated by a multivariable linear regression model.
Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; CI, confidence interval.

Table 4. Diagnostic performance of FAST score for progressive NASH
	Progressive NASH (NASH + NAS ≥ 4 + F ≥ F2)
Prevalence, n (%)	23 (19%)
AUROC (95% CI)	0.76 (0.66–0.86)
FAST ≤0.35 (rule-out zone)
n (%)	88 (73%)
Sensitivity	0.52 (0.30–0.70)
Specificity	0.79 (0.71–0.88)
Positive predictive value	0.38 (0.25–0.52)
Negative predictive value	0.88 (0.83–0.92)
False positive rate	0.21 (0.12–0.29)
False negative rate	0.48 (0.30–0.70)
FAST ≥0.67 (rule-in zone)
n (%)	4 (3%)
Sensitivity	0.09 (0–0.22)
Specificity	0.98 (0.95–1)
Positive predictive value	0.50 (0–1)
Negative predictive value	0.82 (0.80–0.84)
False positive rate	0.02 (0–0.05)
False negative rate	0.91 (0.78–1)

Note: Results of the receiver operating curve (ROC) analysis are presented based on a bootstrap method (10,000 stratified bootstrap replicates). Cut-offs are those published by Newsome et al²⁴ Numbers in brackets are 95% confidence intervals.
Abbreviations: AUROC, area under the receiver operating curve; CI, confidence interval; FAST, FibroScan-AST; NAS, NAFLD activity fibrosis score; NASH, non-alcoholic steatohepatitis.

Authors and Disclosures

Federica Tavaglione^1,2, Antonio De Vincentis^3,4, Vincenzo Bruni⁵, Ida Francesca Gallo⁵, Simone Carotti^6,7, Dario Tuccinardi⁸, Giuseppe Spagnolo⁵, Ester Ciociola², Rosellina Margherita Mancina², Oveis Jamialahmadi², Rossella D'Alessio⁵, Bruna Bottazzi¹, Silvia Manfrini⁸, Antonio Picardi¹, Giuseppe Perrone^6,9, Paolo Pozzilli⁸, Marco Caricato¹⁰, Umberto Vespasiani-Gentilucci¹ and Stefano Romeo^2,11,12

¹Clinical Medicine and Hepatology Unit, Department of Internal Medicine and Geriatrics, Campus Bio-Medico University, Rome, Italy
²Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Wallenberg Laboratory, University of Gothenburg, Gothenburg, Sweden
³Internal Medicine Unit, Department of Internal Medicine and Geriatrics, Campus Bio-Medico University, Rome, Italy
⁴Clinical Lecturer of Internal Medicine, Saint Camillus International University of Health and Medical Sciences, Rome, Italy
⁵Bariatric Surgery Unit, Campus Bio-Medico University, Rome, Italy
⁶Research Unit of Microscopic and Ultrastructural Anatomy, Department of Medicine, Campus Bio-Medico University, Rome, Italy
⁷Predictive Molecular Diagnostic Unit, Department of Pathology, Campus Bio-Medico University Hospital, Rome, Italy
⁸Department of Endocrinology and Diabetes, Campus Bio-Medico University, Rome, Italy
⁹Research Unit of Pathology, Campus Bio-Medico University, Rome, Italy
¹⁰Unit of Colon and Rectal Surgery, Department of General Surgery, Campus Bio-Medico University, Rome, Italy
¹¹Department of Cardiology, Sahlgrenska University Hospital, Gothenburg, Sweden
¹²Clinical Nutrition Unit, Department of Medical and Surgical Sciences, University Magna Graecia, Catanzaro, Italy

Correspondence
Stefano Romeo, MD, PhD, Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Wallenberg Laboratory, University of Gothenburg, Bruna Stråket 16, 41345 Gothenburg, Sweden. Email: stefano.romeo@wlab.gu.se
Umberto Vespasiani-Gentilucci, MD, PhD, Clinical Medicine and Hepatology Unit, Department of Internal Medicine and Geriatrics, Campus Bio-Medico University, Via Alvaro del Portillo 200, 00128 Rome, Italy. Email: u.vespasiani@unicampus.it
Federica Tavaglione, MD, Clinical Medicine and Hepatology Unit, Department of Internal Medicine and Geriatrics, Campus Bio-Medico University, Via Alvaro del Portillo 200, 00128 Rome, Italy. Email: f.tavaglione@unicampus.it

Umberto Vespasiani-Gentilucci and Stefano Romeo shared senior authorship.

Conflicts of Interest
The authors declare no financial or other relationships with drug manufacturers that could lead to a conflict of interest.

Author Contributions
UVG and SR contributed to study concept and design. FT, UVG, and SR contributed to drafting the manuscript. FT and ADV contributed to perform the statistical analysis. All authors contributed to analysis and interpretation of data, critically revised the manuscript for important intellectual content and approved the final version for submission. All authors had fully access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

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Accuracy of Controlled Attenuation Parameter for Assessing Liver Steatosis in Individuals With Morbid Obesity Before Bariatric Surgery

Abstract and Introduction

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