Patients
This study was approved by the Sun Yat-sen Cancer Centre Institutional Review Board (No. B2021-214-01) with a waiver of written informed consent. All methods were carried out in accordance with relevant guidelines and regulations. From January 2014 to June 2022, data on patients with histological diagnoses of HCC were retrieved from our center's databases. Inclusion criteria were (1) patients with contrast-enhanced CT of the abdomen performed before the initiation of treatment; (2) and who received TACE treatment. Exclusion criteria included (1) patients with a single lesion with a maximal diameter of less than 1 cm or not detectable on CT; (2) disseminated disease within the liver precluding the placement of regions of interest (ROIs); (3) received surgery after TACE; (4) no corresponding laboratory test results; (5) the time interval between CT examination and TACE treatment longer than 14 days; and (6) with other malignancies. Patients’ demographics were recorded, including age, gender, BCLC stage, Child − Pugh class, Eastern Cooperative Oncology Group (ECOG) performance status and complications (diabetes or hypertension). Laboratory test results including platelet (PLT) count, alanine transaminase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), international normalized ratio (INR), alkaline phosphatase (ALP), albumin (ALB), C-reactive protein (CRP), Alpha-fetoprotein (AFP), Hepatitis B virus (HBV) and hepatitis C virus (HCV) were collected.
CT acquisition
CT examinations were performed using 2 scanners with intravenous contrast media. The volume of the contrast media was determined by multiplying the body weight (in kilograms) by 2 to a maximum of 100 mL. The concentration of the iodinated contrast media used was 350 mg/mL with an injection rate of 2 mL/s. The scanning parameters of the 2 scanners were as follows: (1) The 128-channel CT scanner (Discovery CT750, GE Healthcare, US): field of view, 25 cm; matrix, 512 x 512; tube voltage, 120 kVp; tube current, 200–400 mA; reconstructed thickness, 5 mm; (2) The 128-channel CT scanners (Somatom Definition or Definition AS+, Siemens Healthcare, US): field of view, 35 cm; matrix, 512 x 512; tube voltage, 80–120 kVp; tube current, 248–578 mA; reconstructed thickness, 5 mm. Finally, the arterial phase images of the CT examination were anonymized and assigned a research code for assessment of general imaging features and texture features extraction.
General imaging features assessment and ROI delineation
All data were reviewed by 2 board-certified radiologists on a dedicated software (ITK-SNAP, v 3.8.0). The senior radiologist (R1) had more than 10 years of cross-sectional imaging experience, while the junior radiologist (R2) had 5 years of cross-sectional imaging experience. This was designed to test for inter-observer agreement. Only the data from the senior radiologist was used for subsequent feature extraction and model construction.
To begin with, they identified all lesions for each patient in consensus and marked the slice of the largest axial diameter of each lesion. Then, they evaluated general imaging features and drew ROIs separately. Four general imaging features were assessed, including (1) the largest tumor diameter, (2) the number of lesions, (3) the presence or absence of portal vein thrombus, and (4) the presence or absence of ascites. ROIs were drawn by strictly delineating around the margin of the mass with careful inclusion of both solid and cystic components but exclusion of adjacent normal structures. If there were multiple lesions, all the lesions would be given a ROI delineation (Suppl 1).
Texture feature extraction
Texture feature extraction was performed on an open-source Python-based radiomics software (PyRadiomics, v 2.2.0). First, all images are normalized and scaled before textual computation. Then, 5 filters were applied, including Laplacian of Gaussian, wavelet, square, square root, logarithm, and exponential filters [14]. Finally, 7 groups of 1511 texture features were extracted, including (1) first-order statistics, (2) shape-based features, (3) gray-level co-occurrence matrix (GLCM), (4) gray-level-dependent matrix (GLDM), (5) neighboring gray tone difference matrix (NGTDM), (6) gray-level size zone matrix (GLSZM), and (7) gray-level run length matrix (GLRLM). More details about these features were tabulated in Table 1 [15].
Table 1
Description of texture feature groups
Texture feature group
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Description
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(1) First-order statistics
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Distribution of grey-level intensities
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(2) Shape-based features
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Description of two- and three- dimensional shape and size
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(3) Gray-level co-occurrence matrix (GLCM)
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The spatial relationship of pixel intensities
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(4) Gray-level-dependent matrix (GLDM)
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Gray level dependencies independent from angles
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(5) Neighboring gray tone difference matrix (NGTDM)
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Difference between gray-level and the average within certain distances
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(6) Gray-level size zone matrix (GLSZM)
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Description of the size of homogeneous zones for each grey-level in 3 dimensions
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(7) Gray-level run length matrix (GLRLM)
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The number of pairs of gray level value and its length of runs
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Feature reduction and selection
First, all quantitative features were tested by intraclass correlation coefficient (ICC), and all qualitative features were tested by kappa score. Features with low inter-rater reproducibility (ICC < 0.8 and kappa score < 0.8) were excluded.
Next, patients were dichotomized into progress-free group, including those who achieved complete response (CR), partial response (PR), stable disease (SD), and progress group, including those who exhibited progressive disease (PD) during follow-up. Univariate logistic regression was conducted to select features that had independent prognostic value (p < 0.1).
Finally, the least absolute shrinkage and selection operator (LASSO) algorithm was employed for further feature reduction. The tuning parameter (λ) was selected using 10-fold cross-validation and minimum criteria. A plot of the partial likelihood deviance was made against log (λ). The minimum (lambda.min) and 1-SE criteria (lambda.1se) were used to draw the dotted vertical lines at the optimal values (Fig. 1, Suppl 2).
TACE procedures
Patients were given one of the three treatments, conventional TACE (c-TACE) using cytotoxic drugs, drug-eluting beads TACE (DEB-TACE) using chemotherapeutic agents, or microwave ablation with TACE (MWA-TACE), as determined by local multi-disciplinary team in accordance with the recommendations of the European/American Association for Liver Disease guidelines [16, 17].
TACE was performed through femoral access under moderate sedation using the Seldinger technique [18]. To cause embolization of the tumor microcirculation, cytotoxic drugs or chemotherapeutic agents suspended in lipiodol were administrated into the tumor feeding artery with a dose ranging from 5 mL to 30 mL depending on the location, the size, and the number of lesions. If necessary, gelatin sponge particles (150–350 µm) were injected to block the blood until the flow was static.
For patients who received MWA-TACE, CT-guided MWA was performed within 7 days after TACE. One or two 14 G antennae were inserted into the target lesion with the microwave power set from 60 W to 80 W and lasted from 10 to 20 minutes.
Assessment of treatment response and follow-up
All patients were followed up by telephone or clinical visits once every 2 months during the first year and once every 3 months after that until death or the last follow-up day (30th June 2022). Physical examination, hepatic function tests, AFP level, and post-treatment contrast-enhanced CT were reviewed. Their treatment response was evaluated by mRECIST. CR was defined as no intratumorally arterial enhancement in all target lesions. PR was defined as an over 30% reduction of the sum of diameters of target lesions. SD was defined as neither PR nor PD. PD was defined as an over 20% increase in the sum of the diameters of target lesions. OS was defined as the time from baseline CT to death or censoring date. PFS was defined as the time from TACE to disease progression (local recurrence or distant organ metastasis), death, or censoring date.
Statistics
Data were described as mean and standard deviation or median and range tested by the Shapiro-Wilk test. Fisher’s exact test and Welch’s T-test were used to verify differences among features. Dice coefficient was calculated between the ROIs drawn by the two radiologists. Kappa score and ICC were used to evaluate feature reproducibility between the two radiologists. A random forest classifier was created to differentiate the progress-free group from the progress group. Random survival forest and Cox proportional hazards models were used to evaluate OS and PFS in patients with HCC treated with TACE. A p < 0.05 was considered statistically significant. Statistical analysis was conducted using R software (version 3.5.1).