This retrospective single-center study was approved by the Medical Ethics Committee of our institution, and the requirement for informed consent was waived.

The study population consisted of 102 patients diagnosed with HCC according to the American Association for the Study of Liver Disease between January 1, 2013, and September 1, 2018. All patients were treated with TACE combined with MWA in our hospital (Fig. 1). All included Patients' characteristics are shown in Table 1. The inclusion criteria were as follows: (1) no previous treatment; (2) Barcelona Clinic Liver Cancer (BCLC) stage: 0, A, or B; (3) postoperative survival > 2 months; and (4) received TACE and MWA at our institution. Exclusion criteria were as follows: (1) initially diagnosed with CT, not MRI; (2) HCC after surgical treatment; (3) with history of other cancers; (4) death unrelated to HCC; (5) Lost to followed-ups; (6) with irregular follow-ups, no sufficient data for evaluating OS and prognostic factors; and (7) Serious MR image distortion.

Flowchart for screening HCC patients treated with TACE and MWA in our hospital

We chose the following clinical features for the Cox proportional hazard models: age, sex, hepatitis B viral infection (or other serotypes); Barcelona Clinic Liver Cancer (BCLC) stage (0, A, or B); Child−Pugh class (A, B, or C); maximum diameter (MD) of the lesion, number of lesions (1, or > 1); proximity to a large vessel (yes or no: yes = tumor margin is less than 5 mm from the portal vein, hepatic vein or inferior vena cava and their branches (larger than 3 mm in diameter) or no = tumor margin is more than 5 mm from the large vessels); proximity to extrahepatic organs (yes or no: yes = tumor margin is less than 5 mm from the gastrointestinal tract, liver capsule, diaphragm, and kidney or no = tumor margin is more than 5 mm extrahepatic organs); Alpha-fetoprotein level (AFP ≤ 20 ng/mL, 20–200 ng/mL or ≥ 200 ng/mL); alanine aminotransferase (ALT ≤ 40U/L or > 40U/L); total bilirubin (TBIL ≤ 20 μmol/L or > 20 mol/L); glutamyl transferase (GGT ≤ 50 U/L or > 50 U/L); albumin (ALB ≤ 35 g/L or > 35 g/L); alkaline phosphatase (ALP ≤ 65 U/L or > 65 U/L) and prothrombin time (PT ≤ 13/s or > 13/s).

TACE was performed within 2 weeks after the diagnosis of HCC. Patients were infused with lobaplatin (50 mg/m2), and then iodized oil emulsion mixed with epirubicin (30 mg/m2); a microcatheter was then inserted into the tumor feeding artery. If necessary, gelatin sponge particles (150–350 μm) were injected until the flow was static. Liver and kidney functions were evaluated after TACE to ensure safe MWA. CT-guided MWA was sequentially performed at approximately 7 days after TACE. One or two 14 G antennae were inserted deep into the target lesion. The microwave power was set at 60–80 W, and the procedure lasted 10–20 min. For tumors with clear boundaries, the ablative volume enveloped the entire tumor including a 0.5–1.0 cm margin surrounding normal tissue. For tumors with irregular shapes or with obscure boundary, the ablative volume enveloped the entire tumor with a margin of 1.0 cm or more. Multiple overlapping ablations were used for tumors > 3.5 cm. For irregular tumors larger than 5.0 cm, enhanced CT within 3–7 days after the treatment was used to detect any residual viable tissue that would require the second MWA. Vital signs such as blood pressure, heart rate, and oxygen saturation were monitored during the procedure. Hepatoprotective, anti-inflammatory, analgesic, and symptomatic treatment were prescribed after MWA.

The patients were followed up by telephone or clinical visits 4 weeks after MWA and then every 3 months. Physical examination, hepatic function tests, AFP level, and triphasic contrast-enhanced CT or MRI were reviewed. The decision was made regarding treatment response, evidence from current guidelines, and the patients' status and intention to treat. For patients with tumor recurrence, an effective treatment plan was determined by our multidisciplinary team (MDT). Tumor recurrence included local and intrahepatic recurrence. Local tumor recurrence was defined as the presence of enhancement within or around the treated area, and intrahepatic recurrence was the presence of enhancement outside the treated area of the tumors > 1 month after treatment. OS, local recurrence-free survival (LRFS), and disease-free survival (DFS) were also assessed. All recurrences were confirmed by CT or MRI. OS was defined as the time from baseline MRI to death or end date. LRFS was defined as the time from TACE to local recurrence, death, or end date. DFS was defined as the time from TACE to local and intrahepatic recurrence, death, or end date. Patients were followed up until death or September 1, 2018, if they were still alive.

The pre-therapeutic MR imaging was performed with a 3.0-T scanner (Achieva; Philips Medical Systems, Best, the Netherlands) with a 16-channel dedicated phased-array body coil. The abdominal MR protocol consisted of the following sequences: (1) axial T2-weighted fat-suppressed 2D turbo-spin-echo (TSE); repetition time (TR)/echo time (TE), 3000/70 ms; slice thickness, 5 mm; slice gap, 1.1 mm; matrix, 320 × 280; (2) axial T1-weighted and contrast-enhanced imaging: T1WI three-dimensional turbo field echo sequence (T1 high-resolution isotropic volume examination, THRIVE, Philips Healthcare) was performed before and after injection of gadopentetate dimeglumine (Magnevist; Bayer Healthcare, Germany, 0.1 mmol/kg) at a rate of 2 ml/sec followed by a 20-ml saline flush with the following parameters: TR/TE: 4.1/1.4 ms, slice thickness: 1 mm, no slice gap, matrix: 252 × 198, hepatic arterial phase (HAP), portal venous phase (PVP), and equilibrium phase images were obtained at 20–30 s, 70–80 s, and 180 s after contrast medium injection, respectively.

For enhanced MR imaging, only PVP images were selected and reconstructed to obtain texture features [16]. Thus, in our study, contrast-enhanced T1-weighted PVP images reconstructed with 3 mm thickness, T1-weighted images and T2-weighted images, were transferred to personal computers for texture analyses.

All the BMP format images, including T1-weighted images (T1WI), T2-weighted images (T2WI) and contrast-enhanced T1WI in portal venous phase (PVP), were transferred into the MaZda program (http://www.eletel.p.lodz.pl/programy/mazda/index.php?action = mazda) for texture analysis. The region of interest (ROI) on the MR parametric maps cannot be utilized automatically by MaZda. Thus, one radiologist (J. L, with 11 years of experience in MRI)—blinded to the clinical and pathological findings—manually traced the tumor border on each axial map, to obtain the corresponding two-dimensional (2D) ROI for each map. Both the most superior and the most inferior slices for each tumor were excluded to avoid volume averaging. Based on all the ROIs from the tumor, a three-dimensional (3D) volume of interest (VOI) was generated automatically (Fig. 2). For each VOI, a total of 229 texture features was extracted automatically by MaZda [17]. Nine first-order texture features were described by the histogram of the signal intensity values of pixels in the VOI. 220 s-order texture features (gray level co-occurrence matrix features, GLCM) were derived from 20 co-occurrence matrices produced from 4 directions and 5 inter-pixel distances in the VOI (Table 2).

An example of ROI segmentation and VOI generation on T2WI. a Shows that the 2D region of interest (ROI) was delineated manually on a T2W image. b Presented that 3D view was generated automatically based on all 2D ROIs of the tumor

The discriminant analysis was done with the Mazda software. The best 10 texture features that predicted 3-year survival were screened out using the following statistical methods: Fisher coefficient, classification error probability with average correlation coefficients (POE + ACC), and mutual information coefficient (MI), respectively. Then texture classification was done using the B11 module in the Mazda software. Three different methods, including the principal component analysis (PCA), linear discriminant analysis (LDA), and nonlinear discriminant analysis (NDA), were applied to calculate the error rate for predicting 3-year survival (Fig. 3). The optimal feature group with the lowest misdiagnosis rate was obtained on one MRI sequence and was used for further analysis.

Main steps of MR image texture analysis

SPSS, version 20.0 (IBM SPSS, Armonk, NY, USA) and the R software, version 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria) were used for statistical analyses. P < 0.05 was regarded as statistically significant. The differences in the values of texture features in the optimal feature group dichotomized by 3-year survival were investigated using independent-sample t-tests. The receiver operating characteristic (ROC) was used to explore the diagnostic performance of these identified texture parameters by independent-sample t-tests, and to determine the cutoff value that would yield the best sensitivity and specificity to predict 3-year survival. Univariate analysis was performed using the Kaplan–Meier method and log-rank test concerning 16 clinical factors affecting survival.

The texture features with statistical significance were divided into two groups based on the cutoff value. These significant texture features, and other significant clinical factors (screened by univariate analyses), were entered into a multivariate regression analysis by Cox proportional hazards model to predict OS (Method: forward LR; probability for stepwise: entry variables ≤ 0.05, removal variables > 0.1). To further identify the predictive performance of the multivariate Cox regression models for OS, we applied the area under the ROC curve (AUC). Survival curves for LRFS and DFS were obtained using the Kaplan–Meier method and log-rank tests.