Contrast-enhanced ultrasound-guided biopsy improved diagnostic accuracy in patients with hepatitis: A prospective multicenter study of 2056 patients

Contrast-enhanced ultrasound-guided biopsy improved diagnostic accuracy in patients with hepatitis: A prospective multicenter study of 2056 patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Contrast-enhanced ultrasound-guided biopsy improved diagnostic accuracy in patients with hepatitis: A prospective multicenter study of 2056 patients Binbin Jiang, Xiang Jing, Yuxiang Wang, Xiao-lin Zhu, Jing Wang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4201325/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Although ultrasound-guided biopsy of focal liver lesions is safe and has high diagnostic accuracy, the factors affecting the results of biopsy are unclear. To investigate factors affecting the accuracy of ultrasound-guided biopsy of liver focal lesions and developed a decision model for the management of biopsy results. Methods This study enrolled participants with focal hepatic lesions who underwent biopsy between March 2016 and August 2019 in nine hospitals in China. The frequency of accurate diagnosis was calculated. The variables were analyzed by multivariate logistic regression. Chi-squared automatic interaction detection was used to construct the prediction model. Results 2056 participants (1297 men, 376 women; mean age, 67.8 ± 10.8 years) were enrolled in the study with 2056 lesions (mean: 4.0±2.8 cm; range: 0.7-17.7 cm). 94.2% (1936/2056) of patients were accurately diagnosed. The accurate diagnosis rate of 2-3 passes was significantly higher than that of one pass (95.1% vs. 87.3%, P 3 passes (95.1% vs. 93.2%, P=0.408). The multivariate logistic regression showedthat no hepatitis [2.493 (1.512-4.110), P1 [(1.811 (1.131-2.901), P=0.013] were independent predictors of accurate diagnoses. The decision tree model showed that in patients with hepatitiswho underwent CEUS-guided biopsy, the probability of an accurate diagnosis may be increased from 88.1% to 94.8% in patients with hepatitis who underwent US-guided biopsy. A 97.5% probability of diagnostic accuracy was obtained from patients without hepatitis who underwent US-guided biopsy. Conclusions CEUS-guided biopsy improves diagnostic accuracy in patients with hepatitis. 2-3 passes can achieve 95% accuracy, and a continued increase in the number of punctures did not improve diagnostic accuracy. Liver biopsy Contrast-enhanced ultrasound Hepatitis Diagnostic accuracy Figures Figure 1 Figure 2 Figure 3 Background Although imaging modalities and serological tests have become important tools in the evaluation of liver disease, biopsy of liver lesions remains an effective method for achieving a pathologic diagnosis and guiding novel management strategies, such as immunotherapy and targeted therapies( 1 – 4 ). Image-guided percutaneous biopsy plays a crucial role in diagnosing liver lesions, and its safety and high diagnostic accuracy have been demonstrated( 2 , 5 , 6 ). Ultrasound (US) is the preferred method of guidance because it is widely available and inexpensive, free of ionizing radiation, and provides real-time guidance( 7 – 10 ). Previous studies and World Federation for Ultrasound in Medicine and Biology guidelines indicated that for invisible lesions or lesions with necrosis, contrast-enhanced US (CEUS) may increase conspicuity( 11 – 13 ). Studies have shown that CEUS can effectively improve the diagnostic accuracy of liver biopsy, with accuracy rates of 93–98%( 14 – 16 ). However, with increased operator experience and improved puncture techniques and equipment, conventional US-guided puncture biopsies have also shown high diagnostic accuracy (87%-99%)( 14 – 17 ). The routine use of CEUS-guided biopsy would increase the technical difficulty and cost of US-guided biopsy. This brings up a question: what type of patients are suitable for CEUS-guided biopsy in balancing cost effectiveness and diagnostic accuracy? However, to our knowledge, no practical recommendation has been made on the management of diagnostic accuracy of US/CEUS-guided liver biopsy of focal liver lesions. Therefore, we aimed to prospectively explore the factors affecting the accuracy of US-guided biopsy and develop a decision model for the management of biopsy results in a multicenter study. Methods This was a secondary ancillary analysis of data acquired from a prospective randomized controlled study (Clinical Trials.gov [NCT02413437]) conducted at nine university teaching hospitals in China between March 2016 and August 2019. The inclusion and exclusion criteria of the trial have been reported( 14 ). The study protocol was approved by the institutional ethics committee of all participating centers. Informed consent was obtained from all patients. US/CEUS-guided biopsy Before the biopsy procedure, all patients underwent coagulation status screening to assess hemostasis risk and for decision making regarding preprocedural management of coagulation. Informed consent for the biopsy was obtained. Participants were randomly assigned to undergo either CEUS-guided or conventional US-guided by means of a randomization table. The liver was scanned with US/CEUS to choose the solid components of lesions or hyperenhancement in the arterial phase as the target area. After proper skin disinfection and administration of a local anesthetic (2% lidocaine), core needle biopsy with 18- to 22-gauge automatic (Bard Peripheral Vascular; Argon Medical Devices; TSK Laboratory) or manual (Sonopsy; Hakko Medical) biopsy needles were used for puncture biopsy. The needle was inserted into the targeted lesion using real-time US or CEUS as the guide. Physicians initially assess sample satisfaction based on the color and texture of the sample to determine the number of punctures. After biopsy, the participants stayed in the observation unit for at least 1 hour. All US and CEUS examinations and biopsies were performed by the same investigators who have experience in US-guided and CEUS-guided of more than 500 lesions( 14 ). Final diagnosis Biopsy results lesions diagnosed as malignant at histopathologic analysis were considered true-positive findings. True-negative is defined as the initial biopsy of a benign or indeterminate result, with no evidence of a subsequent amended malignant diagnosis. Accurate diagnosis includes true positives and true negatives. The biopsy result was considered a false-negative when the initial biopsy yielded a benign or indeterminate result but there was evidence of a subsequent amended malignant histologic diagnosis. A final diagnosis of malignancy was made if 1) a malignant diagnosis was made by pathology on the repeat biopsy or surgical resection, 2) lesions at follow-up with an increase in diameter of more than 20% and an absolute increase of 5 mm or more( 18 ), or 3) lesions were diagnosed based on typical imaging findings, clinical features or oncologic history( 19 ). Hepatitis is defined as inflammation of the liver parenchyma. It can be triggered by multiple factors, including viral infections, such as hepatitis A, B, and C, toxic insults from medications or alcohol, autoimmune processes, and other less frequent etiologies. The diagnosis of hepatitis generally necessitates a synergistic approach incorporating clinical evaluation and laboratory investigations, encompassing blood tests and imaging studies. Statistical analyses Clinical characteristics and biopsy results were compared using Student’s t test or Wilcoxon rank sum test for continuous variables. The χ2 test or exact probability was used to compare categorical variables. Prognostic factors were analyzed by using the logistic regression model. Chi-squared automatic interaction detection (CHAID) was used to construct the decision model. To prevent overfitting, the maximum layer of the decision tree was three, and we finally chose 70% of the original data to build the decision tree model and 30% of the data to verify the model. The numbers of parent nodes and children’s nodes were set to 400 and 200, respectively. All statistical tests were performed using SPSS 22.0 (SPSS Inc. Chicago, IL) and R version 2.1.5 (R Foundation for Statistical Computing, Vienna, Austria) with a level of significance set at P < 0.05. Results Final diagnoses and diagnostic efficacy A total of 2056 participants (1297 men, 376 women; mean age, 67.8 ± 10.8 years) were enrolled in the study with 2056 biopsied lesions (mean ± SD: 4.0 ± 2.8 cm; range: 0.7–17.7 cm). A total of 94.2% (1936/2056) of patients were accurately diagnosed, and the false negative rate was 5.8% (120/2056). The final diagnoses included 825 (40.1%) HCCs, 185 (9.0%) CCCs, 21 (1.0%) remaining primary malignant tumors of the liver (50.1%), 806 metastases (39.2%) and 220 benign tumors (10.7%). The accurate diagnosis rate for patients with metastatic cancer was significantly higher than that for patients with primary malignant tumors of the liver (96.7% vs. 91.0%, P < 0.001). The detailed final diagnosis is shown in Table 1 . Table 1 Final diagnosis of all patients who underwent biopsy Final Diagnosis All patients N = 2056 Number of patients (%) False negative N = 120 Accurate diagnosis N = 1936 P value Primary malignant tumor 1030(50.1) 93(9.0) 937(91.0) <0.001 HCC 825(80.9) 85(10.3) 740(89.7) <0.001 CCC 185(18.0) 6(3.2) 179(96.8) 0.115 HCC or CCC 9(0.9) 1(11.1) 8(88.8) 0.419 Vascular original tumor 8(0.8) 1(12.5) 7(87.5) 0.382 Sarcomatoid carcinoma 3(0.3) 0(0) 3(100) 1.000 Metastasis 806(39.2) 27(3.3) 779(96.7) <0.001 Benign lesion 220(10.7) 0(0) 220(100) <0.001 HCC = hepatocellular carcinoma; CCC = cholangiocellular carcinoma. The original vascular tumors included two epithelioid angiomyolipomas, five epithelioid hemangioendotheliomas, and one angiosarcoma. Among patients with metastatic cancer, the most common primary lesions in patients with liver metastasis were pancreatic carcinoma (19.1%), lung carcinoma (15.8%), breast cancer (13.4%) and colorectal cancers (13.0%). All patients with liver metastases from breast cancer were accurately diagnosed by biopsy (0% vs. 13.9%, P = 0.021). Metastatic lesions originated from a variety of primary tumors (Table 2 ). Table 2 Origin of 806 metastatic liver lesions that underwent biopsy Final Diagnosis All patients N = 806 Number of patients (%) False negative N = 27 Accurate diagnosis N = 779 P value Pancreaticobiliary carcinoma 154(19.1) 5(3.2) 149(96.8) 0.937 Lung carcinoma 127(15.8) 7(5.5) 120(94.5) 0.173 Breast cancer 108(13.4) 0(0) 108(100) 0.021 Colorectal carcinoma 105(13.0) 4(3.8) 101(96.2) 0.770 Gallbladder carcinoma 53(6.6) 2(3.8) 51(96.2) 0.696 Neuroendocrine cancer 49(6.1) 1(2.0) 48(98.0) 1.000 Gastric cancer 33(4.1) 0(0) 33(100) 0.622 Carcinoma of bile duct 29(3.6) 2(6.9) 27(93.1) 0.253 Gastrointestinal stromal tumor 21(2.6) 2(9.5) 19(90.5) 0.154 Malignant melanoma 16(2.0) 1(6.2) 15(93.8) 0.423 Leiomyosarcoma 13(1.6) 1(7.7) 12(92.3) 0.360 Lymphoma 9(1.1) 1(11.1) 8(88.9) 0.265 Esophageal cancer 13(1.6) 0(0) 13(100) 1.000 Ovarian carcinoma 13(1.6) 0(0) 13(100) 1.000 Other tumors* 33(4.1) 0(0) 33(100) 0.621 Undefined origin 30(3.7) 1(3.3) 29(96.7) 1.000 *Other tumors included 6 patients with endometrial cancer, 6 patients with cervical cancer, 5 patients with thymic cancer, 4 patients with nasopharyngeal cancer, 4 patients with adrenal cancer, 4 patients with adenoid cystic cancer, 3 patients with renal cancer, and 1 patient with bladder cancer. Baseline characteristics and predictive variables In this study, the sampling satisfaction rate was 99.8% (2053/2056), and 95.7% (1968/2056) of patients were sampled using an automated biopsy gun. The mean number of biopsy passes was 2.3 ± 0.7 (range: 1–6 attempts). One, two to three and more than three biopsy passes were performed in 228 (11.1%), 1755 (83.9%) and 73 (3.6%) patients, respectively. The accurate diagnosis rate of two to three passes was significantly higher than that of one pass (95.1% vs. 87.3%, P < 0.001) and higher than that of more than 3 passes (95.1% vs. 93.2%, P = 0.408). To identify the characteristics associated with accurate diagnoses, we compared the variables of clinical patient-related characteristics, lesion characteristics, and biopsy-related characteristics between the false negatives and accurate diagnoses (Table 3 ). In this study, we included 891 cases of hepatitis B, 46 cases of hepatitis C, 21 cases of alcoholic hepatitis, and 58 cases of other types of hepatitis, among which 726 patients progressed to cirrhosis. There were significant differences in the factors between the two groups, including sex (P = 0.028), hepatitis (P < 0.001), history of malignancy (P = 0.04), lesion size (P = 0.042), lesion echo (P = 0.032), biopsy-guided approach (P = 0.001) and number per biopsy (P < 0.001) (Table 3 ). Table 3 Predictive factors of biopsy accuracy of liver focal lesions Characteristic False-negative N=120 Accuracy N=1936 P value Patient-related Sex 0.028 Male 87(72.5) 1210(62.5) Female 33(27.5) 726(37.5) Age , means ± SDs 56.9 + 10.6 57.9 + 10.8 0.324 Hepatitis ﹤0.001 With 89(74.2) 927(47.9) Without 31(25.8) 1009(52.1) History of malignancy 0.004 Yes 22(18.3) 598(30.9) No 98(81.7) 1338(69.1) Lesion characteristics Location 0.404 Left lobe 27(22.5) 502(25.9) Right lobe 93(77.5) 1434(74.1) Size 0.024 ≤ 2 cm 38(31.7) 439(22.7) > 2 cm 82(68.3) 1497(77.3) Median, range 2.5(0.9~15.4) 3.0(0.7~17.7) 0.042 Morphology 0.304 Regular 57(47.5) 827(42.7) Irregular 63(52.5) 1109(57.3) Echoes 0.032 High 12(10.0) 369(19.1) Equal 13(10.8) 131(6.8) Low 67(55.8) 1070(55.3) Uneven 28(23.2) 366(18.9) Necrosis 0.677 Yes 7(5.8) 132(6.8) No 113(94.2) 1804(93.2) Halo edge 0.286 Yes 20(16.7) 401(20.7) No 100(83.3) 1535(79.3) Biopsy-related CEUS-guided 0.001 Yes 43(35.8) 983(50.8) No 77(64.2) 953(49.2) Needle size 0.602 17/18/19G 114(95.0) 1858(95.8) 20/21G 6(5.0) 78(4.0) Number per biopsy ＜0.001 1 29(24.2) 199(10.3) ≥ 2 91(75.8) 1737(89.7) Mean + SD 2.1 + 0.8 2.3 + 0.7 0.103 Satisfaction with sampling 0.165 Yes 119(99.2) 1934(99.9) No 1(5.8) 2(0.1) Biopsy needles 0.688 Automatic 114(95.0) 1854(95.8) Manual 6(5.0) 82(4.2) Values are presented as numbers (%). The multivariate logistic regression showed that without hepatitis [2.493 (1.512–4.110), P 1 [(1.811 (1.131–2.901), P = 0.013] were independent predictors of accurate diagnoses (Table 4 ). Table 4 Multivariable logistic regression analysis of factors affecting the accuracy of diagnostic biopsy results Variable B SE OR 95%CI P value Sex 0.237 0.218 1.267 0.826–1.943 0.278 Hepatitis 0.914 0.255 2.493 1.512–4.110 <0.001 History of malignancy 0.022 0.281 1.022 0.589–1.773 0.937 Size 0.257 0.2111 1.293 0.855–1.955 0.223 Echoes 0.177 0.108 1.194 0.966–1.476 0.101 CEUS-guided 0.633 0.198 1.884 1.278–2.777 0.001 Multi-biopsy 0.594 0.240 1.811 1.131–2.901 0.013 OR, odds ratio; CI, confidence interval; BMI, body mass index; US, ultrasound. Subgroup analyses of hepatitis and no hepatitis The accurate diagnosis rate was 91.2% (927/1016) for patients with hepatitis and 97.0% (1009/1040) for patients without hepatitis, with a significant difference between the two groups (P<0.001). We conducted univariate and multifactorial analyses. We showed that CEUS-guided biopsy [(1.932(1.228–3.039), P = 0.004)] and the number of biopsy passes [1.839(1.134–2.982), P = 0.014] were independent prognostic factors influencing the accurate diagnostic rate in hepatitis (Supplementary table 1 –2) but did not affect the accurate diagnostic rate in patients with or without hepatitis [3.130 (0.694–14.127), P = 0.138; 1.791 (0.847–3.786, P = 0.127)]. Sex [2.319(1.054–5.101), P = 0.036] was associated with an accurate diagnostic rate in patients without hepatitis (Supplementary table 3 –4). In addition, we conducted a stratified analysis of the relationship between CEUS-guided and the number of puncture attempts and increased the accuracy of diagnostic results in patients with hepatitis and patients without hepatitis, according to potential modifiers, including sex, history of malignancy, lesion location, lesion size, echo and guidance for biopsy. Among patients with hepatitis, except the subgroup with a history of malignancy, all subgroups showed that CEUS-guided biopsy and multi-biopsy conferred a higher accurate diagnostic rate (Fig. 1 – 2 ). Among patients without hepatitis, CEUS-guided biopsy and multiple needle punctures were not associated with improved accurate diagnosis, but multiple biopsies increased the accurate diagnostic rate in male patients (P = 0.032) and those with hyperechoic lesions (P = 0.024) (Supplement Fig. 1 – 2 ). Decision tree predictive model Two variables were identified and tested in our decision tree predictive model for assessing patient likelihood of an accurate diagnosis result: hepatitis and CEUS-guided (Fig. 3 ). According to the model, a 97.5% probability of diagnostic accuracy was obtained from patients without hepatitis who underwent US-guided biopsy. The probability of accurate diagnosis was 88.1% in patients with hepatitis and without CEUS-guided biopsy; if patients with hepatitis underwent CEUS-guided biopsy, the probability of an accurate diagnosis increased to 94.8%. The predictive accuracy of the model was 94.6%. Discussion Our analyses of this prospective multicenter randomized controlled study showed that CEUS-guided puncture biopsy in patients with hepatitis can significantly improve diagnostic accuracy, but for nonhepatitis patients, US-guided puncture biopsy has a higher diagnostic accuracy. Damage to liver cells in patients with hepatitis from various causes including viral and alcoholic leads to cirrhosis. Cirrhosis promotes the occurrence of hepatocellular carcinoma( 20 ). Liver nodules on hepatitis usually undergo a process from benign hyperplastic nodules, atypical hyperplastic nodules and finally hepatocellular liver cancer( 21 ). Due to the intricate liver texture, uneven echogenicity, and significant overlap in the ultrasound appearance of benign and malignant lesions, it is challenging to distinguish liver lesions within a cirrhotic background by conventional US( 22 ). On CEUS, it is easier to identify the cancerous component( 23 ), and the success rate of CEUS-guided biopsy is higher. A prospective randomized clinical trial( 24 ) showed the consistent conclusion of a contrast-enhanced-guided liver biopsy diagnosis of focal liver lesions developed on a background of advanced chronic liver disease. Then, in patients with a nonhepatitis liver, metastases are more common than primary liver malignant tumors, and conventional US is occasionally helpful in detecting the malignant nature of focal liver lesions by demonstrating a hypoechoic halo and infiltration of intrahepatic vessels. In addition, metastatic lesions are usually different from liver cells. Thus, a diagnosis can often be reached more easily in these cases than in patients with primary tumors, where cells more closely resemble normal liver texture. The liver is a common site of metastasis. The most common primary lesions in patients with liver metastasis were pancreatic carcinoma (19.1%), lung carcinoma (15.8%), breast cancer (13.4%) and colorectal cancers (13.0%). All patients with liver metastases from breast cancer were accurately diagnosed by biopsy. This finding is consistent with a large-scale nationwide analysis of pathology reports( 17 , 25 ). In this study, conventional US-guided biopsy also had a high diagnostic accuracy (92.5%), especially for nonhepatitis patients, with an accuracy rate of 97%. This may be related to multiple aspects. First, the operator has extensive operational experience in taking an optimal sample by selecting the margins of lesions to avoid necrotic areas and by recognizing the adequacy of the sampled tissue to repeat biopsy immediately if necessary. Second, lesions in a nonhepatitis background were easily identified in conventional US and easily differentiated pathologically. Acquiring sufficient liver tissue is important for the pathologist to make firm conclusions. Guidelines on the use of liver biopsy in clinical practice( 5 ) recommended the biopsy of focal liver nodules using an 18G needle to obtain a sample of at least 20 mm to facilitate pathological diagnosis. In this study, 90% of patients underwent a puncture biopsy with an 18G needle. We found that the number of biopsy passes was an independent predictor of an accurate diagnosis. Higher diagnostic accuracy was obtained with 2–3 passes than with a single pass (95.1% vs. 87.3%, P < 0.001), and a continued increase in the number of punctures did not significantly improve the diagnostic accuracy (95.1% vs. 93.2%, P = 0.408). Appelbaum L et al.( 26 ) reported the consistent conclusion that three passes would be diagnostic in almost 90% of all cases. Therefore, 2–3 passes avoid the possibility of unsatisfactory sampling with a single puncture and reduce the risk of bleeding and pain in patients with more than 3 punctures( 27 ). In our study, size was not found to be a significant independent prognostic factor influencing the accurate diagnostic rate. Appelbaum, Lita et al( 26 ) reported a similar conclusion. Small hepatic lesions are more challenging to target but may have a more uniform distribution of cancerous tissue without hemorrhage, necrosis, or sclerotic changes( 28 ). Biopsy specimens have more tissue cells for pathological diagnosis. In large lesions, US has been able to more clearly show areas of necrosis in larger lesions, obtaining satisfactory sampling. There were several limitations to our study. First, the final inclusion of US-guided biopsy was visible lesions in conventional ultrasound; therefore, this conclusion applies to patients without hepatitis with visible lesions, and US-guided biopsy has a high diagnostic accuracy. In addition, in this study, a physician with extensive puncture experience performed the puncture and obtained a higher diagnostic accuracy of the puncture, so the influence of the operator's experience on the puncture results needs to be further investigated. Conclusions CEUS-guided puncture biopsy in patients with hepatitis can significantly improve diagnostic accuracy, but for nonhepatitis patients, US-guided puncture biopsy has a high diagnostic accuracy. Two to three needle puncture biopsies can achieve 95% puncture accuracy, and continuing to increase the number of punctures did not improve diagnostic accuracy. The accurate diagnosis rate for patients without hepatitis is significantly higher than that for patients with hepatitis. CEUS guidance and the number of punctures increased the accuracy of diagnostic results in patients with hepatitis but did not influence biopsy outcome correlation in patients without hepatitis. Abbreviations US ultrasound CEUS contrast-enhanced ultrasound HCC hepatocellular carcinoma CCC cholangiocellular carcinoma. CI:confidence interval OR odds ratio Declarations Ethics approval and consent to participate The present study was approved by the Beijing cancer hospital medical ethics committee. Written informed consent was obtained from the patients for publication of this study. Consent for publication NA. Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests Authors declare no Conflict of Interests for this article. Funding This research was supported by Beijing Municipal Science & Technology Commission (grant no. Z151100004015186). Authors' contributions Binbin Jiang, Xiang Jing, Yuxiang Wang and Xiao-lin Zhu have made equal contribution. All authors guided and had access to the data analysis. The authors had full editorial control of the paper and provided their final approval of all contents. Acknowledgements Not applicable References Gore RM, Pickhardt PJ, Mortele KJ, Fishman EK, Horowitz JM, Fimmel CJ, et al. Management of Incidental Liver Lesions on CT: A White Paper of the ACR Incidental Findings Committee. J Am Coll Radiol. 2017;14(11):1429-37. Khalifa A, Rockey DC. The utility of liver biopsy in 2020. Curr Opin Gastroenterol. 2020;36(3):184-91. Rockey DC, Caldwell SH, Goodman ZD, Nelson RC, Smith AD. Liver biopsy. Hepatology (Baltimore, Md). 2009;49(3):1017-44. Colecchia A, Scaioli E, Montrone L, Vestito A, Di Biase AR, Pieri M, et al. Pre-operative liver biopsy in cirrhotic patients with early hepatocellular carcinoma represents a safe and accurate diagnostic tool for tumour grading assessment. Journal of hepatology. 2011;54(2):300-5. Neuberger J, Patel J, Caldwell H, Davies S, Hebditch V, Hollywood C, et al. Guidelines on the use of liver biopsy in clinical practice from the British Society of Gastroenterology, the Royal College of Radiologists and the Royal College of Pathology. Gut. 2020;69(8):1382-403. Adnan A, Sheth RA. Image-guided Percutaneous Biopsy of the Liver. Tech Vasc Interv Radiol. 2021;24(4):100773. Al Knawy B, Shiffman M. Percutaneous liver biopsy in clinical practice. Liver international : official journal of the International Association for the Study of the Liver. 2007;27(9):1166-73. Tian G, Kong D, Jiang T, Li L. Complications After Percutaneous Ultrasound-Guided Liver Biopsy: A Systematic Review and Meta-analysis of a Population of More Than 12,000 Patients From 51 Cohort Studies. J Ultrasound Med. 2020;39(7):1355-65. Howlett DC, Drinkwater KJ, Lawrence D, Barter S, Nicholson T. Findings of the UK national audit evaluating image-guided or image-assisted liver biopsy. Part I. Procedural aspects, diagnostic adequacy, and accuracy. Radiology. 2012;265(3):819-31. Varela-Ponte R, Martínez-Lago N, Vieito-Villar M, Martin Carreira-Villamor J. Impact of risk factors on the efficacy and complications of ultrasound-guided percutaneous liver biopsy of space-occupying lesions. Radiologia (Engl Ed). 2022;64(6):497-505. Francica G, Meloni MF, de Sio I, Terracciano F, Caturelli E, Riccardi L, et al. Biopsy of Liver Target Lesions under Contrast-Enhanced Ultrasound Guidance - A Multi-Center Study. Ultraschall in der Medizin (Stuttgart, Germany : 1980). 2018;39(4):448-53. Kang TW, Lee MW, Song KD, Kim M, Kim SS, Kim SH, et al. Added Value of Contrast-Enhanced Ultrasound on Biopsies of Focal Hepatic Lesions Invisible on Fusion Imaging Guidance. Korean J Radiol. 2017;18(1):152-61. Dietrich CF, Nolsøe CP, Barr RG, Berzigotti A, Burns PN, Cantisani V, et al. Guidelines and Good Clinical Practice Recommendations for Contrast-Enhanced Ultrasound (CEUS) in the Liver-Update 2020 WFUMB in Cooperation with EFSUMB, AFSUMB, AIUM, and FLAUS. Ultrasound in medicine & biology. 2020;46(10):2579-604. Wu W, Jing X, Xue GQ, Zhu XL, Wang J, Du RQ, et al. A Multicenter Randomized Controlled Study of Contrast-enhanced US versus US-guided Biopsy of Focal Liver Lesions. Radiology. 2022;305(3):721-8. Huang JX, Shi CG, Xu YF, Fu J, Zhong Y, Liu LZ, et al. The benefit of contrast-enhanced ultrasound in biopsies for focal liver lesions: a retrospective study of 820 cases. European radiology. 2022;32(10):6830-9. Wu W, Chen MH, Yin SS, Yan K, Fan ZH, Yang W, et al. The role of contrast-enhanced sonography of focal liver lesions before percutaneous biopsy. AJR American journal of roentgenology. 2006;187(3):752-61. Khalifa A, Sasso R, Rockey DC. Role of Liver Biopsy in Assessment of Radiologically Identified Liver Masses. Dig Dis Sci. 2022;67(1):337-43. Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). European journal of cancer (Oxford, England : 1990). 2009;45(2):228-47. Bruix J, Sherman M. Management of hepatocellular carcinoma: an update. Hepatology (Baltimore, Md). 2011;53(3):1020-2. Toh MR, Wong EYT, Wong SH, Ng AWT, Loo LH, Chow PK, et al. Global Epidemiology and Genetics of Hepatocellular Carcinoma. Gastroenterology. 2023;164(5):766-82. Kudo M. Multistep human hepatocarcinogenesis: correlation of imaging with pathology. J Gastroenterol. 2009;44 Suppl 19:112-8. Choi BI, Lee JM, Kim TK, Dioguardi Burgio M, Vilgrain V. Diagnosing Borderline Hepatic Nodules in Hepatocarcinogenesis: Imaging Performance. AJR American journal of roentgenology. 2015;205(1):10-21. Wu W, Chen MH, Sun M, Yan K, Yang W, Li JY. Contrast-enhanced ultrasound of hepatocarcinogenesis in liver cirrhosis. Chinese medical journal. 2012;125(17):3104-9. Sparchez Z, Mocan T, Hagiu C, Kacso G, Zaharie T, Rusu I, et al. Real-Time Contrast-Enhanced-Guided Biopsy Compared with Conventional Ultrasound-Guided Biopsy in the Diagnosis of Hepatic Tumors on a Background of Advanced Chronic Liver Disease: A Prospective, Randomized, Clinical Trial. Ultrasound in medicine & biology. 2019;45(11):2915-24. de Ridder J, de Wilt JH, Simmer F, Overbeek L, Lemmens V, Nagtegaal I. Incidence and origin of histologically confirmed liver metastases: an explorative case-study of 23,154 patients. Oncotarget. 2016;7(34):55368-76. Appelbaum L, Kane RA, Kruskal JB, Romero J, Sosna J. Focal hepatic lesions: US-guided biopsy--lessons from review of cytologic and pathologic examination results. Radiology. 2009;250(2):453-8. Chi H, Hansen BE, Tang WY, Schouten JN, Sprengers D, Taimr P, et al. Multiple biopsy passes and the risk of complications of percutaneous liver biopsy. Eur J Gastroenterol Hepatol. 2017;29(1):36-41. Yu SC, Liew CT, Lau WY, Leung TW, Metreweli C. US-guided percutaneous biopsy of small (< or = 1-cm) hepatic lesions. Radiology. 2001;218(1):195-9. Additional Declarations No competing interests reported. Supplementary Files Additionalfigure1.tif Additionalfigure2.tif Additionalfiletables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4201325","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286995122,"identity":"7b9f1264-d595-47dd-9667-da1d7c104779","order_by":0,"name":"Binbin Jiang","email":"","orcid":"","institution":"Peking University Cancer Hospital \u0026 Institute","correspondingAuthor":false,"prefix":"","firstName":"Binbin","middleName":"","lastName":"Jiang","suffix":""},{"id":286995123,"identity":"7b0c7217-8405-46e9-9267-a34cc4d842ac","order_by":1,"name":"Xiang Jing","email":"","orcid":"","institution":"Tianjin Third Central Hospital, department of Ultrasonography","correspondingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Jing","suffix":""},{"id":286995124,"identity":"2e72df3c-b78f-4c11-9bd0-285d06d22eb7","order_by":2,"name":"Yuxiang Wang","email":"","orcid":"","institution":"Shanxi Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuxiang","middleName":"","lastName":"Wang","suffix":""},{"id":286995125,"identity":"178b9dd6-4eb7-4e84-a13a-fc3bb6a84b09","order_by":3,"name":"Xiao-lin Zhu","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiao-lin","middleName":"","lastName":"Zhu","suffix":""},{"id":286995126,"identity":"d11f3710-f8af-40d2-acb9-1c9089c1f31f","order_by":4,"name":"Jing Wang","email":"","orcid":"","institution":"Yantai Qishan Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Wang","suffix":""},{"id":286995127,"identity":"9dc61040-f630-4845-a6da-c12df9d0b788","order_by":5,"name":"Rui-qing Du","email":"","orcid":"","institution":"Fifth Hospital of Shijiazhuang","correspondingAuthor":false,"prefix":"","firstName":"Rui-qing","middleName":"","lastName":"Du","suffix":""},{"id":286995128,"identity":"652309ab-f952-470c-914e-5ed8fd0e5ef9","order_by":6,"name":"Bin Lv","email":"","orcid":"","institution":"Jining No.1 People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Lv","suffix":""},{"id":286995129,"identity":"750ec969-1f5b-4d06-8f56-e531923d0823","order_by":7,"name":"Ke-feng Wang","email":"","orcid":"","institution":"Cangzhou Infectious Disease Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ke-feng","middleName":"","lastName":"Wang","suffix":""},{"id":286995130,"identity":"d2ee95ea-7faf-4342-81d6-d422d6851dfd","order_by":8,"name":"Zhixiang Gao","email":"","orcid":"","institution":"Shanxi Provincial People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhixiang","middleName":"","lastName":"Gao","suffix":""},{"id":286995132,"identity":"057f7d68-5cbf-4e70-83e4-958161a24af6","order_by":9,"name":"Kun Yan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYFCCHAaGDwwSQAZjA/FaGGeQrIWZhyRnGRzPPfzZts0ij4H/cNuDHwx2crqELDM48y7BOLdNophBIrHdsIch2djsACEtN3IMknPOSCQ2SDC2SfAwHEjcRoyWwxYgLfwH2yT/EKnFsJmhAqiFIbFNmihbJM+8S2bsqZAoZpMAapExIMIvfMAQ+/DDoC6Pn//4M8k3FXZyBLUoQBUksEHcSUA5CMg3QLUQoXYUjIJRMApGKgAAD78/G5nnC74AAAAASUVORK5CYII=","orcid":"","institution":"Peking University Cancer Hospital \u0026 Institute","correspondingAuthor":true,"prefix":"","firstName":"Kun","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2024-04-01 14:41:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4201325/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4201325/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54318106,"identity":"255e6603-e07f-4467-b6ca-efa1d30e3852","added_by":"auto","created_at":"2024-04-08 18:29:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":819752,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for subgroup analyses of the relationship between CEUS-guided biopsy and increased accuracy ofdiagnostic results in patients with hepatitis. CI = confidence interval. OR= odds ratio.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4201325/v1/1968fa46213eb5047193f1c7.png"},{"id":54318104,"identity":"6765cd1c-ba85-4606-8054-7f857aa514a2","added_by":"auto","created_at":"2024-04-08 18:29:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":822385,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for subgroup analyses of the relationship between CEUS-guided biopsy and increased accurate diagnostic results in patients without hepatitis. CI = confidence interval. OR= odds ratio\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4201325/v1/54bc2824b2f97cc94c5ac353.png"},{"id":54318108,"identity":"4cb5e791-722f-492c-8243-751e82a543f6","added_by":"auto","created_at":"2024-04-08 18:29:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":356525,"visible":true,"origin":"","legend":"\u003cp\u003eDecision tree predictive model of accurate diagnosis results of ultrasound-guided liver biopsy based on a history of hepatitis and CEUS-guided biopsy\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4201325/v1/7d7468a6970c5f14411f540a.png"},{"id":75201274,"identity":"760be9b8-3d82-4023-9b4b-1038e777cf7c","added_by":"auto","created_at":"2025-02-01 00:01:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3245755,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4201325/v1/c975df44-e912-4c3d-84da-92abdf389557.pdf"},{"id":54318105,"identity":"aac69d95-91a5-48a7-8947-1549ecef9cb7","added_by":"auto","created_at":"2024-04-08 18:29:36","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":9864988,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-4201325/v1/eb820035301847619a8e5424.tif"},{"id":54318110,"identity":"c381751b-b2c1-4d98-804d-82cd15ab6583","added_by":"auto","created_at":"2024-04-08 18:29:37","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10047344,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-4201325/v1/4c417160b345e992896373a7.tif"},{"id":54318109,"identity":"6fb1121f-3213-466d-9ef4-bc25cfb7d8a4","added_by":"auto","created_at":"2024-04-08 18:29:37","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2773836,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfiletables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4201325/v1/7ac6c848f26c0e5d98353901.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contrast-enhanced ultrasound-guided biopsy improved diagnostic accuracy in patients with hepatitis: A prospective multicenter study of 2056 patients","fulltext":[{"header":"Background","content":"\u003cp\u003eAlthough imaging modalities and serological tests have become important tools in the evaluation of liver disease, biopsy of liver lesions remains an effective method for achieving a pathologic diagnosis and guiding novel management strategies, such as immunotherapy and targeted therapies(\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImage-guided percutaneous biopsy plays a crucial role in diagnosing liver lesions, and its safety and high diagnostic accuracy have been demonstrated(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Ultrasound (US) is the preferred method of guidance because it is widely available and inexpensive, free of ionizing radiation, and provides real-time guidance(\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Previous studies and World Federation for Ultrasound in Medicine and Biology guidelines indicated that for invisible lesions or lesions with necrosis, contrast-enhanced US (CEUS) may increase conspicuity(\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies have shown that CEUS can effectively improve the diagnostic accuracy of liver biopsy, with accuracy rates of 93\u0026ndash;98%(\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, with increased operator experience and improved puncture techniques and equipment, conventional US-guided puncture biopsies have also shown high diagnostic accuracy (87%-99%)(\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The routine use of CEUS-guided biopsy would increase the technical difficulty and cost of US-guided biopsy. This brings up a question: what type of patients are suitable for CEUS-guided biopsy in balancing cost effectiveness and diagnostic accuracy? However, to our knowledge, no practical recommendation has been made on the management of diagnostic accuracy of US/CEUS-guided liver biopsy of focal liver lesions. Therefore, we aimed to prospectively explore the factors affecting the accuracy of US-guided biopsy and develop a decision model for the management of biopsy results in a multicenter study.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis was a secondary ancillary analysis of data acquired from a prospective randomized controlled study (Clinical Trials.gov [NCT02413437]) conducted at nine university teaching hospitals in China between March 2016 and August 2019. The inclusion and exclusion criteria of the trial have been reported(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The study protocol was approved by the institutional ethics committee of all participating centers. Informed consent was obtained from all patients.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eUS/CEUS-guided biopsy\u003c/h2\u003e \u003cp\u003eBefore the biopsy procedure, all patients underwent coagulation status screening to assess hemostasis risk and for decision making regarding preprocedural management of coagulation. Informed consent for the biopsy was obtained. Participants were randomly assigned to undergo either CEUS-guided or conventional US-guided by means of a randomization table. The liver was scanned with US/CEUS to choose the solid components of lesions or hyperenhancement in the arterial phase as the target area. After proper skin disinfection and administration of a local anesthetic (2% lidocaine), core needle biopsy with 18- to 22-gauge automatic (Bard Peripheral Vascular; Argon Medical Devices; TSK Laboratory) or manual (Sonopsy; Hakko Medical) biopsy needles were used for puncture biopsy. The needle was inserted into the targeted lesion using real-time US or CEUS as the guide. Physicians initially assess sample satisfaction based on the color and texture of the sample to determine the number of punctures. After biopsy, the participants stayed in the observation unit for at least 1 hour. All US and CEUS examinations and biopsies were performed by the same investigators who have experience in US-guided and CEUS-guided of more than 500 lesions(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFinal diagnosis\u003c/h2\u003e \u003cp\u003eBiopsy results lesions diagnosed as malignant at histopathologic analysis were considered true-positive findings. True-negative is defined as the initial biopsy of a benign or indeterminate result, with no evidence of a subsequent amended malignant diagnosis. Accurate diagnosis includes true positives and true negatives. The biopsy result was considered a false-negative when the initial biopsy yielded a benign or indeterminate result but there was evidence of a subsequent amended malignant histologic diagnosis. A final diagnosis of malignancy was made if 1) a malignant diagnosis was made by pathology on the repeat biopsy or surgical resection, 2) lesions at follow-up with an increase in diameter of more than 20% and an absolute increase of 5 mm or more(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), or 3) lesions were diagnosed based on typical imaging findings, clinical features or oncologic history(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Hepatitis is defined as inflammation of the liver parenchyma. It can be triggered by multiple factors, including viral infections, such as hepatitis A, B, and C, toxic insults from medications or alcohol, autoimmune processes, and other less frequent etiologies. The diagnosis of hepatitis generally necessitates a synergistic approach incorporating clinical evaluation and laboratory investigations, encompassing blood tests and imaging studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eClinical characteristics and biopsy results were compared using Student\u0026rsquo;s t test or Wilcoxon rank sum test for continuous variables. The χ2 test or exact probability was used to compare categorical variables. Prognostic factors were analyzed by using the logistic regression model. Chi-squared automatic interaction detection (CHAID) was used to construct the decision model. To prevent overfitting, the maximum layer of the decision tree was three, and we finally chose 70% of the original data to build the decision tree model and 30% of the data to verify the model. The numbers of parent nodes and children\u0026rsquo;s nodes were set to 400 and 200, respectively. All statistical tests were performed using SPSS 22.0 (SPSS Inc. Chicago, IL) and R version 2.1.5 (R Foundation for Statistical Computing, Vienna, Austria) with a level of significance set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eFinal diagnoses and diagnostic efficacy\u003c/h2\u003e \u003cp\u003eA total of 2056 participants (1297 men, 376 women; mean age, 67.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8 years) were enrolled in the study with 2056 biopsied lesions (mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SD: 4.0\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;2.8 cm; range: 0.7\u0026ndash;17.7 cm). A total of 94.2% (1936/2056) of patients were accurately diagnosed, and the false negative rate was 5.8% (120/2056). The final diagnoses included 825 (40.1%) HCCs, 185 (9.0%) CCCs, 21 (1.0%) remaining primary malignant tumors of the liver (50.1%), 806 metastases (39.2%) and 220 benign tumors (10.7%). The accurate diagnosis rate for patients with metastatic cancer was significantly higher than that for patients with primary malignant tumors of the liver (96.7% vs. 91.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The detailed final diagnosis is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFinal diagnosis of all patients who underwent biopsy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFinal Diagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;2056\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eNumber of patients (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eFalse negative\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;120\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAccurate diagnosis\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1936\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary malignant tumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1030(50.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93(9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e937(91.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e825(80.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e740(89.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e185(18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e179(96.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC or CCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e9(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8(88.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular original tumor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSarcomatoid carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e3(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMetastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e806(39.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e779(96.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBenign lesion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e220(10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e220(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eHCC\u0026thinsp;=\u0026thinsp;hepatocellular carcinoma; CCC\u0026thinsp;=\u0026thinsp;cholangiocellular carcinoma.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eThe original vascular tumors included two epithelioid angiomyolipomas, five epithelioid hemangioendotheliomas, and one angiosarcoma.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong patients with metastatic cancer, the most common primary lesions in patients with liver metastasis were pancreatic carcinoma (19.1%), lung carcinoma (15.8%), breast cancer (13.4%) and colorectal cancers (13.0%). All patients with liver metastases from breast cancer were accurately diagnosed by biopsy (0% vs. 13.9%, P\u0026thinsp;=\u0026thinsp;0.021). Metastatic lesions originated from a variety of primary tumors (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOrigin of 806 metastatic liver lesions that underwent biopsy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFinal Diagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;806\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eNumber of patients (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFalse negative\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;27\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccurate diagnosis\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;779\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreaticobiliary carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154(19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149(96.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127(15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120(94.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108(13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColorectal carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105(13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101(96.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGallbladder carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53(6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51(96.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.696\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeuroendocrine cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49(6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48(98.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastric cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33(4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarcinoma of bile duct\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29(3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(93.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal stromal tumor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21(2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(90.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignant melanoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeiomyosarcoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophageal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvarian carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther tumors*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33(4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndefined origin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30(3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(96.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Other tumors included 6 patients with endometrial cancer, 6 patients with cervical cancer, 5 patients with thymic cancer, 4 patients with nasopharyngeal cancer, 4 patients with adrenal cancer, 4 patients with adenoid cystic cancer, 3 patients with renal cancer, and 1 patient with bladder cancer.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics and predictive variables\u003c/h2\u003e \u003cp\u003eIn this study, the sampling satisfaction rate was 99.8% (2053/2056), and 95.7% (1968/2056) of patients were sampled using an automated biopsy gun. The mean number of biopsy passes was 2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 (range: 1\u0026ndash;6 attempts). One, two to three and more than three biopsy passes were performed in 228 (11.1%), 1755 (83.9%) and 73 (3.6%) patients, respectively. The accurate diagnosis rate of two to three passes was significantly higher than that of one pass (95.1% vs. 87.3%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher than that of more than 3 passes (95.1% vs. 93.2%, P\u0026thinsp;=\u0026thinsp;0.408).\u003c/p\u003e \u003cp\u003eTo identify the characteristics associated with accurate diagnoses, we compared the variables of clinical patient-related characteristics, lesion characteristics, and biopsy-related characteristics between the false negatives and accurate diagnoses (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In this study, we included 891 cases of hepatitis B, 46 cases of hepatitis C, 21 cases of alcoholic hepatitis, and 58 cases of other types of hepatitis, among which 726 patients progressed to cirrhosis. There were significant differences in the factors between the two groups, including sex (P\u0026thinsp;=\u0026thinsp;0.028), hepatitis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), history of malignancy (P\u0026thinsp;=\u0026thinsp;0.04), lesion size (P\u0026thinsp;=\u0026thinsp;0.042), lesion echo (P\u0026thinsp;=\u0026thinsp;0.032), biopsy-guided approach (P\u0026thinsp;=\u0026thinsp;0.001) and number per biopsy (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 3 Predictive\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003efactors\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of biopsy accuracy of liver focal lesions\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFalse-negative\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=120\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccuracy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=1936\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient-related\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e87(72.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1210(62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e33(27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e726(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e, means \u0026plusmn; SDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e56.9\u003cu\u003e+\u003c/u\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e57.9\u003cu\u003e+\u003c/u\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHepatitis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e﹤0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eWith\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e89(74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e927(47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Without\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e31(25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1009(52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of malignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e22(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e598(30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e98(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1338(69.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLesion characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eLeft lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e27(22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e502(25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eRight lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e93(77.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1434(74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSize\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 2 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e38(31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e439(22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 2 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e82(68.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1497(77.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eMedian, range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e2.5(0.9~15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e3.0(0.7~17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMorphology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eRegular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e57(47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e827(42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eIrregular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e63(52.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1109(57.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchoes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e12(10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e369(19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eEqual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e13(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e131(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e67(55.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1070(55.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eUneven\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e28(23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e366(18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNecrosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e7(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e132(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e113(94.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1804(93.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHalo edge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e20(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e401(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e100(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1535(79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiopsy-related\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCEUS-guided\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e43(35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e983(50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e77(64.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e953(49.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003cstrong\u003eNeedle size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e17/18/19G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e114(95.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1858(95.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e20/21G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e6(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e78(4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber per biopsy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e29(24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e199(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge; 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e91(75.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1737(89.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eMean \u003cu\u003e+\u003c/u\u003e SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e2.1\u003cu\u003e+\u003c/u\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e2.3\u003cu\u003e+\u003c/u\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSatisfaction with sampling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e119(99.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1934(99.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e1(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e2(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiopsy needles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eAutomatic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e114(95.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e1854(95.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.22393822393823%\" valign=\"top\"\u003e\n \u003cp\u003eManual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e6(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.146718146718147%\" valign=\"top\"\u003e\n \u003cp\u003e82(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.814671814671815%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are presented as numbers (%).\u003c/p\u003e \u003cp\u003eThe multivariate logistic regression showed that without hepatitis [2.493 (1.512\u0026ndash;4.110), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], CEUS-guided [1.884 (1.278\u0026ndash;2.777), P\u0026thinsp;=\u0026thinsp;0.001], and biopsy pass\u0026thinsp;\u0026gt;\u0026thinsp;1 [(1.811 (1.131\u0026ndash;2.901), P\u0026thinsp;=\u0026thinsp;0.013] were independent predictors of accurate diagnoses (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression analysis of factors affecting the accuracy of diagnostic biopsy results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.826\u0026ndash;1.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.512\u0026ndash;4.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of malignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.589\u0026ndash;1.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSize\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.855\u0026ndash;1.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEchoes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.966\u0026ndash;1.476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEUS-guided\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.278\u0026ndash;2.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMulti-biopsy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.131\u0026ndash;2.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eOR, odds ratio; CI, confidence interval; BMI, body mass index; US, ultrasound.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analyses of hepatitis and no hepatitis\u003c/h2\u003e \u003cp\u003eThe accurate diagnosis rate was 91.2% (927/1016) for patients with hepatitis and 97.0% (1009/1040) for patients without hepatitis, with a significant difference between the two groups (P\u0026lt;0.001).\u003c/p\u003e \u003cp\u003eWe conducted univariate and multifactorial analyses. We showed that CEUS-guided biopsy [(1.932(1.228\u0026ndash;3.039), P\u0026thinsp;=\u0026thinsp;0.004)] and the number of biopsy passes [1.839(1.134\u0026ndash;2.982), P\u0026thinsp;=\u0026thinsp;0.014] were independent prognostic factors influencing the accurate diagnostic rate in hepatitis (Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;2) but did not affect the accurate diagnostic rate in patients with or without hepatitis [3.130 (0.694\u0026ndash;14.127), P\u0026thinsp;=\u0026thinsp;0.138; 1.791 (0.847\u0026ndash;3.786, P\u0026thinsp;=\u0026thinsp;0.127)]. Sex [2.319(1.054\u0026ndash;5.101), P\u0026thinsp;=\u0026thinsp;0.036] was associated with an accurate diagnostic rate in patients without hepatitis (Supplementary table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;4).\u003c/p\u003e \u003cp\u003eIn addition, we conducted a stratified analysis of the relationship between CEUS-guided and the number of puncture attempts and increased the accuracy of diagnostic results in patients with hepatitis and patients without hepatitis, according to potential modifiers, including sex, history of malignancy, lesion location, lesion size, echo and guidance for biopsy. Among patients with hepatitis, except the subgroup with a history of malignancy, all subgroups showed that CEUS-guided biopsy and multi-biopsy conferred a higher accurate diagnostic rate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among patients without hepatitis, CEUS-guided biopsy and multiple needle punctures were not associated with improved accurate diagnosis, but multiple biopsies increased the accurate diagnostic rate in male patients (P\u0026thinsp;=\u0026thinsp;0.032) and those with hyperechoic lesions (P\u0026thinsp;=\u0026thinsp;0.024) (Supplement Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDecision tree predictive model\u003c/h2\u003e \u003cp\u003eTwo variables were identified and tested in our decision tree predictive model for assessing patient likelihood of an accurate diagnosis result: hepatitis and CEUS-guided (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). According to the model, a 97.5% probability of diagnostic accuracy was obtained from patients without hepatitis who underwent US-guided biopsy. The probability of accurate diagnosis was 88.1% in patients with hepatitis and without CEUS-guided biopsy; if patients with hepatitis underwent CEUS-guided biopsy, the probability of an accurate diagnosis increased to 94.8%. The predictive accuracy of the model was 94.6%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur analyses of this prospective multicenter randomized controlled study showed that CEUS-guided puncture biopsy in patients with hepatitis can significantly improve diagnostic accuracy, but for nonhepatitis patients, US-guided puncture biopsy has a higher diagnostic accuracy.\u003c/p\u003e \u003cp\u003eDamage to liver cells in patients with hepatitis from various causes including viral and alcoholic leads to cirrhosis. Cirrhosis promotes the occurrence of hepatocellular carcinoma(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Liver nodules on hepatitis usually undergo a process from benign hyperplastic nodules, atypical hyperplastic nodules and finally hepatocellular liver cancer(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Due to the intricate liver texture, uneven echogenicity, and significant overlap in the ultrasound appearance of benign and malignant lesions, it is challenging to distinguish liver lesions within a cirrhotic background by conventional US(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). On CEUS, it is easier to identify the cancerous component(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), and the success rate of CEUS-guided biopsy is higher.\u003c/p\u003e \u003cp\u003eA prospective randomized clinical trial(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) showed the consistent conclusion of a contrast-enhanced-guided liver biopsy diagnosis of focal liver lesions developed on a background of advanced chronic liver disease. Then, in patients with a nonhepatitis liver, metastases are more common than primary liver malignant tumors, and conventional US is occasionally helpful in detecting the malignant nature of focal liver lesions by demonstrating a hypoechoic halo and infiltration of intrahepatic vessels. In addition, metastatic lesions are usually different from liver cells. Thus, a diagnosis can often be reached more easily in these cases than in patients with primary tumors, where cells more closely resemble normal liver texture.\u003c/p\u003e \u003cp\u003eThe liver is a common site of metastasis. The most common primary lesions in patients with liver metastasis were pancreatic carcinoma (19.1%), lung carcinoma (15.8%), breast cancer (13.4%) and colorectal cancers (13.0%). All patients with liver metastases from breast cancer were accurately diagnosed by biopsy. This finding is consistent with a large-scale nationwide analysis of pathology reports(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, conventional US-guided biopsy also had a high diagnostic accuracy (92.5%), especially for nonhepatitis patients, with an accuracy rate of 97%. This may be related to multiple aspects. First, the operator has extensive operational experience in taking an optimal sample by selecting the margins of lesions to avoid necrotic areas and by recognizing the adequacy of the sampled tissue to repeat biopsy immediately if necessary. Second, lesions in a nonhepatitis background were easily identified in conventional US and easily differentiated pathologically.\u003c/p\u003e \u003cp\u003eAcquiring sufficient liver tissue is important for the pathologist to make firm conclusions. Guidelines on the use of liver biopsy in clinical practice(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) recommended the biopsy of focal liver nodules using an 18G needle to obtain a sample of at least 20 mm to facilitate pathological diagnosis.\u003c/p\u003e \u003cp\u003eIn this study, 90% of patients underwent a puncture biopsy with an 18G needle. We found that the number of biopsy passes was an independent predictor of an accurate diagnosis. Higher diagnostic accuracy was obtained with 2\u0026ndash;3 passes than with a single pass (95.1% vs. 87.3%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and a continued increase in the number of punctures did not significantly improve the diagnostic accuracy (95.1% vs. 93.2%, P\u0026thinsp;=\u0026thinsp;0.408). Appelbaum L et al.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) reported the consistent conclusion that three passes would be diagnostic in almost 90% of all cases. Therefore, 2\u0026ndash;3 passes avoid the possibility of unsatisfactory sampling with a single puncture and reduce the risk of bleeding and pain in patients with more than 3 punctures(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study, size was not found to be a significant independent prognostic factor influencing the accurate diagnostic rate. Appelbaum, Lita et al(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) reported a similar conclusion. Small hepatic lesions are more challenging to target but may have a more uniform distribution of cancerous tissue without hemorrhage, necrosis, or sclerotic changes(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Biopsy specimens have more tissue cells for pathological diagnosis. In large lesions, US has been able to more clearly show areas of necrosis in larger lesions, obtaining satisfactory sampling.\u003c/p\u003e \u003cp\u003eThere were several limitations to our study. First, the final inclusion of US-guided biopsy was visible lesions in conventional ultrasound; therefore, this conclusion applies to patients without hepatitis with visible lesions, and US-guided biopsy has a high diagnostic accuracy. In addition, in this study, a physician with extensive puncture experience performed the puncture and obtained a higher diagnostic accuracy of the puncture, so the influence of the operator's experience on the puncture results needs to be further investigated.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eCEUS-guided puncture biopsy in patients with hepatitis can significantly improve diagnostic accuracy, but for nonhepatitis patients, US-guided puncture biopsy has a high diagnostic accuracy. Two to three needle puncture biopsies can achieve 95% puncture accuracy, and continuing to increase the number of punctures did not improve diagnostic accuracy. The accurate diagnosis rate for patients without hepatitis is significantly higher than that for patients with hepatitis. CEUS guidance and the number of punctures increased the accuracy of diagnostic results in patients with hepatitis but did not influence biopsy outcome correlation in patients without hepatitis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eultrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCEUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econtrast-enhanced ultrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehepatocellular carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echolangiocellular carcinoma. CI:confidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eodds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was approved by the Beijing cancer hospital medical ethics committee. Written informed consent was obtained from the patients for publication of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare no Conflict of Interests for this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Beijing Municipal Science \u0026amp; Technology Commission (grant no. Z151100004015186).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBinbin Jiang, Xiang Jing, Yuxiang Wang and Xiao-lin Zhu have made equal contribution. All authors guided and had access to the data analysis. The authors had full editorial control of the paper and provided their final approval of all contents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGore RM, Pickhardt PJ, Mortele KJ, Fishman EK, Horowitz JM, Fimmel CJ, et al. Management of Incidental Liver Lesions on CT: A White Paper of the ACR Incidental Findings Committee. J Am Coll Radiol. 2017;14(11):1429-37.\u003c/li\u003e\n\u003cli\u003eKhalifa A, Rockey DC. The utility of liver biopsy in 2020. Curr Opin Gastroenterol. 2020;36(3):184-91.\u003c/li\u003e\n\u003cli\u003eRockey DC, Caldwell SH, Goodman ZD, Nelson RC, Smith AD. Liver biopsy. Hepatology (Baltimore, Md). 2009;49(3):1017-44.\u003c/li\u003e\n\u003cli\u003eColecchia A, Scaioli E, Montrone L, Vestito A, Di Biase AR, Pieri M, et al. Pre-operative liver biopsy in cirrhotic patients with early hepatocellular carcinoma represents a safe and accurate diagnostic tool for tumour grading assessment. Journal of hepatology. 2011;54(2):300-5.\u003c/li\u003e\n\u003cli\u003eNeuberger J, Patel J, Caldwell H, Davies S, Hebditch V, Hollywood C, et al. Guidelines on the use of liver biopsy in clinical practice from the British Society of Gastroenterology, the Royal College of Radiologists and the Royal College of Pathology. Gut. 2020;69(8):1382-403.\u003c/li\u003e\n\u003cli\u003eAdnan A, Sheth RA. Image-guided Percutaneous Biopsy of the Liver. Tech Vasc Interv Radiol. 2021;24(4):100773.\u003c/li\u003e\n\u003cli\u003eAl Knawy B, Shiffman M. Percutaneous liver biopsy in clinical practice. Liver international : official journal of the International Association for the Study of the Liver. 2007;27(9):1166-73.\u003c/li\u003e\n\u003cli\u003eTian G, Kong D, Jiang T, Li L. Complications After Percutaneous Ultrasound-Guided Liver Biopsy: A Systematic Review and Meta-analysis of a Population of More Than 12,000 Patients From 51 Cohort Studies. J Ultrasound Med. 2020;39(7):1355-65.\u003c/li\u003e\n\u003cli\u003eHowlett DC, Drinkwater KJ, Lawrence D, Barter S, Nicholson T. Findings of the UK national audit evaluating image-guided or image-assisted liver biopsy. Part I. Procedural aspects, diagnostic adequacy, and accuracy. Radiology. 2012;265(3):819-31.\u003c/li\u003e\n\u003cli\u003eVarela-Ponte R, Mart\u0026iacute;nez-Lago N, Vieito-Villar M, Martin Carreira-Villamor J. Impact of risk factors on the efficacy and complications of ultrasound-guided percutaneous liver biopsy of space-occupying lesions. Radiologia (Engl Ed). 2022;64(6):497-505.\u003c/li\u003e\n\u003cli\u003eFrancica G, Meloni MF, de Sio I, Terracciano F, Caturelli E, Riccardi L, et al. Biopsy of Liver Target Lesions under Contrast-Enhanced Ultrasound Guidance - A Multi-Center Study. Ultraschall in der Medizin (Stuttgart, Germany : 1980). 2018;39(4):448-53.\u003c/li\u003e\n\u003cli\u003eKang TW, Lee MW, Song KD, Kim M, Kim SS, Kim SH, et al. Added Value of Contrast-Enhanced Ultrasound on Biopsies of Focal Hepatic Lesions Invisible on Fusion Imaging Guidance. Korean J Radiol. 2017;18(1):152-61.\u003c/li\u003e\n\u003cli\u003eDietrich CF, Nols\u0026oslash;e CP, Barr RG, Berzigotti A, Burns PN, Cantisani V, et al. Guidelines and Good Clinical Practice Recommendations for Contrast-Enhanced Ultrasound (CEUS) in the Liver-Update 2020 WFUMB in Cooperation with EFSUMB, AFSUMB, AIUM, and FLAUS. Ultrasound in medicine \u0026amp; biology. 2020;46(10):2579-604.\u003c/li\u003e\n\u003cli\u003eWu W, Jing X, Xue GQ, Zhu XL, Wang J, Du RQ, et al. A Multicenter Randomized Controlled Study of Contrast-enhanced US versus US-guided Biopsy of Focal Liver Lesions. Radiology. 2022;305(3):721-8.\u003c/li\u003e\n\u003cli\u003eHuang JX, Shi CG, Xu YF, Fu J, Zhong Y, Liu LZ, et al. The benefit of contrast-enhanced ultrasound in biopsies for focal liver lesions: a retrospective study of 820 cases. European radiology. 2022;32(10):6830-9.\u003c/li\u003e\n\u003cli\u003eWu W, Chen MH, Yin SS, Yan K, Fan ZH, Yang W, et al. The role of contrast-enhanced sonography of focal liver lesions before percutaneous biopsy. AJR American journal of roentgenology. 2006;187(3):752-61.\u003c/li\u003e\n\u003cli\u003eKhalifa A, Sasso R, Rockey DC. Role of Liver Biopsy in Assessment of Radiologically Identified Liver Masses. Dig Dis Sci. 2022;67(1):337-43.\u003c/li\u003e\n\u003cli\u003eEisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). European journal of cancer (Oxford, England : 1990). 2009;45(2):228-47.\u003c/li\u003e\n\u003cli\u003eBruix J, Sherman M. Management of hepatocellular carcinoma: an update. Hepatology (Baltimore, Md). 2011;53(3):1020-2.\u003c/li\u003e\n\u003cli\u003eToh MR, Wong EYT, Wong SH, Ng AWT, Loo LH, Chow PK, et al. Global Epidemiology and Genetics of Hepatocellular Carcinoma. Gastroenterology. 2023;164(5):766-82.\u003c/li\u003e\n\u003cli\u003eKudo M. Multistep human hepatocarcinogenesis: correlation of imaging with pathology. J Gastroenterol. 2009;44 Suppl 19:112-8.\u003c/li\u003e\n\u003cli\u003eChoi BI, Lee JM, Kim TK, Dioguardi Burgio M, Vilgrain V. Diagnosing Borderline Hepatic Nodules in Hepatocarcinogenesis: Imaging Performance. AJR American journal of roentgenology. 2015;205(1):10-21.\u003c/li\u003e\n\u003cli\u003eWu W, Chen MH, Sun M, Yan K, Yang W, Li JY. Contrast-enhanced ultrasound of hepatocarcinogenesis in liver cirrhosis. Chinese medical journal. 2012;125(17):3104-9.\u003c/li\u003e\n\u003cli\u003eSparchez Z, Mocan T, Hagiu C, Kacso G, Zaharie T, Rusu I, et al. Real-Time Contrast-Enhanced-Guided Biopsy Compared with Conventional Ultrasound-Guided Biopsy in the Diagnosis of Hepatic Tumors on a Background of Advanced Chronic Liver Disease: A Prospective, Randomized, Clinical Trial. Ultrasound in medicine \u0026amp; biology. 2019;45(11):2915-24.\u003c/li\u003e\n\u003cli\u003ede Ridder J, de Wilt JH, Simmer F, Overbeek L, Lemmens V, Nagtegaal I. Incidence and origin of histologically confirmed liver metastases: an explorative case-study of 23,154 patients. Oncotarget. 2016;7(34):55368-76.\u003c/li\u003e\n\u003cli\u003eAppelbaum L, Kane RA, Kruskal JB, Romero J, Sosna J. Focal hepatic lesions: US-guided biopsy--lessons from review of cytologic and pathologic examination results. Radiology. 2009;250(2):453-8.\u003c/li\u003e\n\u003cli\u003eChi H, Hansen BE, Tang WY, Schouten JN, Sprengers D, Taimr P, et al. Multiple biopsy passes and the risk of complications of percutaneous liver biopsy. Eur J Gastroenterol Hepatol. 2017;29(1):36-41.\u003c/li\u003e\n\u003cli\u003eYu SC, Liew CT, Lau WY, Leung TW, Metreweli C. US-guided percutaneous biopsy of small (\u0026lt; or = 1-cm) hepatic lesions. Radiology. 2001;218(1):195-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Liver biopsy, Contrast-enhanced ultrasound, Hepatitis, Diagnostic accuracy","lastPublishedDoi":"10.21203/rs.3.rs-4201325/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4201325/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough ultrasound-guided biopsy of focal liver lesions is safe and has high diagnostic accuracy, the factors affecting the results of biopsy are unclear. To investigate factors affecting the accuracy of ultrasound-guided biopsy of liver focal lesions and developed a decision model for the management of biopsy results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study enrolled participants with focal hepatic lesions who underwent biopsy between March 2016 and August 2019 in nine hospitals in China. The frequency of accurate diagnosis was calculated. The variables were analyzed by multivariate logistic regression. Chi-squared automatic interaction detection was used to construct the prediction model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2056 participants (1297 men, 376 women; mean age, 67.8 ± 10.8 years) were enrolled in the study with 2056 lesions (mean: 4.0±2.8 cm; range: 0.7-17.7 cm). 94.2% (1936/2056) of patients were accurately diagnosed. The accurate diagnosis rate of 2-3 passes was significantly higher than that of one pass (95.1% vs. 87.3%, P \u0026lt; 0.001) and comparable to the accuracy of \u0026gt;3 passes (95.1% vs. 93.2%, P=0.408). The multivariate logistic regression showedthat no hepatitis [2.493 (1.512-4.110), P\u0026lt;0.001], CEUS-guided [1.884 (1.278-2.777), P=0.001], and biopsypass \u0026gt;1 [(1.811 (1.131-2.901), P=0.013] were independent predictors of accurate diagnoses.\u003c/p\u003e\n\u003cp\u003eThe decision tree model showed that in patients with hepatitiswho underwent CEUS-guided biopsy, the probability of an accurate diagnosis may be increased from 88.1% to 94.8% in patients with hepatitis who underwent US-guided biopsy. A 97.5% probability of diagnostic accuracy was obtained from patients without hepatitis who underwent US-guided biopsy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCEUS-guided biopsy improves diagnostic accuracy in patients with hepatitis. 2-3 passes can achieve 95% accuracy, and a continued increase in the number of punctures did not improve diagnostic accuracy.\u003c/p\u003e","manuscriptTitle":"Contrast-enhanced ultrasound-guided biopsy improved diagnostic accuracy in patients with hepatitis: A prospective multicenter study of 2056 patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 18:29:31","doi":"10.21203/rs.3.rs-4201325/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f8296df1-8d40-4abe-8429-8e49d23d444a","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-31T23:53:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 18:29:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4201325","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4201325","identity":"rs-4201325","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}