Reproducibility of shear wave elastography (SWE) in patients with chronic liver disease

Mancini, Marcello; Megna, Angelo Salomone; Ragucci, Monica; Luca, Massimo De; Marsilia, Giuseppina Marino; Nardone, Gerardo; Coccoli, Pietro; Prinster, Anna; Mannelli, Lorenzo; Vergara, Emilia; Monti, Serena; Liuzzi, Raffaele; Incoronato, Mariarosaria

doi:10.1371/journal.pone.0185391

Cited by 36 publications

(32 citation statements)

References 35 publications

(33 reference statements)

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“…In our study, a median of six SWV measurements was the minimum number required that resulted in an error rate of less than 5% compared with a median of 10 measurements. In addition, the 95% agreement limit from the Bland Altman analysis was also comparable to the 95% agreement limit from interobserver variability previously described (26). The area under the receiver operating characteristic curve GASTROINTESTINAL IMAGING: Reducing the Number of Measurements in Liver Point Shear-Wave Elastography Fang et al rate with histologic evaluation for differentiating between significant and severe fibrosis or cirrhosis, respectively, compared with patients with higher reliability measurements (IQR-to-median ratio, 30%).…”

Section: Discussionsupporting

confidence: 74%

Reducing the Number of Measurements in Liver Point Shear-Wave Elastography: Factors that Influence the Number and Reliability of Measurements in Assessment of Liver Fibrosis in Clinical Practice

Fang¹,

Jaffer²,

Yusuf³

et al. 2018

Radiology

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Purpose To identify the minimum number of measurements required for the noninvasive assessment of liver fibrosis by using point shear-wave elastography (pSWE) and determine whether the use of a reliability indicator such as interquartile range [IQR]-to-median ratio will affect diagnostic performance. Materials and Methods Ten liver shear-wave velocity (SWV) measurements by pSWE were obtained in 232 participants. Interclass correlation coefficients (ICC) between the median of the first two through the first nine measurements and all 10 measurements were calculated; the minimum number of measurements with ICC greater than 0.95 versus all 10 measurements was determined. The diagnostic performance of the minimum number of measurements and 10 measurements in identifying significant (Ishak stage, ≥3) and severe fibrosis or cirrhosis (Ishak stage, ≥5) was compared by using areas under the receiver operating characteristic curve. These were compared between measurements that demonstrated higher or lower reliability (IQR-to-median ratio of ≤ 30% and IQR-to-median ratio of > 30%, respectively). Results Compared with 10 measurements, a minimum of six SWV measurements was required. The overall area under the curve for diagnosing significant (areas under the receiver operating characteristic curve, 0.828 vs 0.839; P = .487) and severe fibrosis or cirrhosis (0.953 vs 0.969, respectively; P = .145) did not differ according to number of measurements (six vs 10); a median of six measurements resulted in only limited disagreement (nine of 232 [3.9%]) versus histologic evaluation. When using 10 measurements, higher reliability measurements showed a lower percentage of discordance between pSWE and significant fibrosis and severe fibrosis or cirrhosis (22 [14.7%] and three [2.0%] of 150 cases, respectively) compared with lower reliability measurements (26 [31.7%] and eight [9.8%] of 82 cases, respectively). Significant fibrosis was an independent predictor for lower reliability (hazard ratio, 2.22; P < .020). Conclusion A limited number of SWV measurements (median six vs median 10) were required for the assessment of liver fibrosis by using pSWE. The number of measurements had less influence on the diagnostic accuracy compared with lower reliability measurements. RSNA, 2018 Online supplemental material is available for this article.

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Section: Discussionsupporting

confidence: 74%

Reducing the Number of Measurements in Liver Point Shear-Wave Elastography: Factors that Influence the Number and Reliability of Measurements in Assessment of Liver Fibrosis in Clinical Practice

Fang¹,

Jaffer²,

Yusuf³

et al. 2018

Radiology

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“…RTE can differentiate malignant from benign thyroid nodules because malignant nodules are harder than the surrounding adjacent parenchyma (23)(24)(25)(26)(27). Several meta-analyses suggest that RTE is superior to SWE for this purpose (28,29).…”

Section: Discussionmentioning

confidence: 99%

Machine Learning–Assisted System for Thyroid Nodule Diagnosis

Zhang

Tian²,

Pei

et al. 2019

Thyroid

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Background: Ultrasound (US) examination is helpful in the differential diagnosis of thyroid nodules (malignant vs. benign), but its accuracy relies heavily on examiner experience. Therefore, the aim of this study was to develop a less subjective diagnostic model aided by machine learning. Methods: A total of 2064 thyroid nodules (2032 patients, 695 male; M age = 45.25-13.49 years) met all of the following inclusion criteria: (i) hemi-or total thyroidectomy, (ii) maximum nodule diameter 2.5 cm, (iii) examination by conventional US and real-time elastography within one month before surgery, and (iv) no previous thyroid surgery or percutaneous thermotherapy. Models were developed using 60% of randomly selected samples based on nine commonly used algorithms, and validated using the remaining 40% of cases. All models function with a validation data set that has a pretest probability of malignancy of 10%. The models were refined with machine learning that consisted of 1000 repetitions of derivatization and validation, and compared to diagnosis by an experienced radiologist. Sensitivity, specificity, accuracy, and area under the curve (AUC) were calculated. Results: A random forest algorithm led to the best diagnostic model, which performed better than radiologist diagnosis based on conventional US only (AUC = 0.924 [confidence interval (CI) 0.895-0.953] vs. 0.834 [CI 0.815-0.853]) and based on both conventional US and real-time elastography (AUC = 0.938 [CI 0.914-0.961] vs. 0.843 [CI 0.829-0.857]). Conclusions: Machine-learning algorithms based on US examinations, particularly the random forest classifier, may diagnose malignant thyroid nodules better than radiologists.

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“…In healthy participants, the intraobserver repeatability of 2D SWE was excellent (ICC ranged from 0.92-0.95), 22,27,28 and the interobserver agreement across different days was good (ICC ranged from 0.63-0.88). 22,28 In patients with chronic liver disease, Yoon et al 15 reported excellent overall intraobserver repeatability (ICC, 0.95), and Mancini et al 29 reported excellent interobserver agreement (ICC, 0.94). These previously published studies showed that experience, patient age, and disease, as well as different days, liver segments, and times of examinations, can affect the repeatability of the measurements.…”

Section: Discussionmentioning

confidence: 99%

Does Operator Experience and the Q‐Box Diameter Affect the Repeatability of Liver Stiffness Measurements Obtained by 2‐Dimensional Shear Wave Elastography?

Wang

Zheng

Liang

et al. 2019

J of Ultrasound Medicine

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Objectives The purpose of this research was to evaluate whether operator experience and the quantitative analysis system (Q‐Box; SuperSonic Imagine, Aix‐en‐Provence, France) diameter affect the repeatability of liver stiffness measurements. Methods We enrolled 417 outpatients. All measurements were performed by 2 operators, including an expert and a novice. Each patient was continuously measured 3 times by the 2 operators. The Q‐Box diameter was adjusted to 10, 20, and 30 mm each time, and the mean elasticity values were recorded. Intraobserver repeatability was evaluated by the intraclass correlation coefficient (ICC). Interobserver repeatability was evaluated by the ICC, coefficient of variation (CV), and Bland‐Altman plots. Results The study group included 241 male and 176 female patients. The expert operator had higher ICCs than the novice operator at each Q‐Box diameter. The overall interobserver agreement was excellent, and the results showed that compared to other groups, the ICC was the lowest and the CV was the largest for the 30‐mm‐diameter group. The ICC and CV values were similar between the 10‐ and 20 mm‐diameter groups. The Bland‐Altman plots showed that the mean difference was –0.2 kPa for the 10‐, 20‐, and 30 mm‐diameter groups. However, the limits of agreement were the largest in the 30‐mm‐diameter group and were similar between the 10‐ and 20‐mm‐diameter groups. Conclusions The repeatability of liver stiffness measurements is affected not only by experience but also by the Q‐Box diameter.

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Reproducibility of shear wave elastography (SWE) in patients with chronic liver disease

Cited by 36 publications

References 35 publications

Reducing the Number of Measurements in Liver Point Shear-Wave Elastography: Factors that Influence the Number and Reliability of Measurements in Assessment of Liver Fibrosis in Clinical Practice

Reducing the Number of Measurements in Liver Point Shear-Wave Elastography: Factors that Influence the Number and Reliability of Measurements in Assessment of Liver Fibrosis in Clinical Practice

Machine Learning–Assisted System for Thyroid Nodule Diagnosis

Does Operator Experience and the Q‐Box Diameter Affect the Repeatability of Liver Stiffness Measurements Obtained by 2‐Dimensional Shear Wave Elastography?

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