Tumor volume measured using MR volumetry as a predictor of prognosis after surgical resection of single hepatocellular carcinoma

The Value of no Evidence of Disease (NED) in Intermediate-Stage Hepatocellular Carcinoma After TACE: A Real-World Study

BACKGROUND AND AIMS

One-third of patients with intermediate-stage hepatocellular carcinoma (HCC) can achieve imaging-based no evidence of disease (NED) during treatment after transarterial chemoembolization (TACE) and sequential therapies; however, its temporal dynamics, contributing factors and prognostic value remain unknown.

METHODS

The longitudinal data of 1665 intermediate-stage HCC patients from Sun Yat-sen University Cancer Center were included as a derivation cohort; 414 patients from three external medical centers served as the validation cohort. Image-Only NED is defined as no evidence of disease based on imaging exams while having a serum level of alpha-fetoprotein (AFP) above the upper limit; Image-Bio NED pertains to an additional achievement of a normal level of AFP. A semi-Markov multistate model was adopted to identify the transitions between intermediate states, which included NED unreached, Image-Only NED, Image-Bio NED, recurrence after NED and death. A time-dependent Cox proportional hazards model for overall survival (OS) was utilised to evaluate the dynamic prognostic value of NED states.

RESULTS

The percentage of patients who reached Image NED and Image-Bio NED was 35.2% and 24.7% in the derivation cohort, and 37.4% and 31.4% in the validation cohort. The proportion of Image-Only NED and Image-Bio NED peaked by the end of the second year since initial treatment and declined gradually. Patients with Image-Only NED had a higher risk of recurrence compared to the Image-Bio NED subgroup (p < 0.05). With the subgroup of NED unreached as reference, the multivariate time-dependent Cox model showed Image-Only NED (HR 0.44; 95% CI 0.33-0.59) and Image-Bio NED (HR 0.26; 0.20-0.33) were significant intermediate states that predict distinct OS for patients with intermediate-stage HCC, which was further confirmed in the multi-centre validation cohort.

CONCLUSIONS

Our study highlights the clinical course of NED states and demonstrates its dynamic prognostic significance in patients with intermediate-stage HCC after TACE. The Image-Bio NED is recommended to serve as an important endpoint during the dynamic management of intermediate-stage HCC.

Usefulness of Semiautomated 3D Volumetric Assessment of Liver Tumor Burden for Patients With Unresectable Pancreatic Neuroendocrine Tumor: A Pilot Study

OBJECTIVES

In patients with metastatic pancreatic neuroendocrine tumors (PanNETs), the Ki-67 index is objectively assessed by pathologists; however, liver tumor burden (LTB) depends on the subjective judgment of physicians. This study aimed to elucidate the usefulness of the semi-automated 3D volumetric assessment of LTB in patients with PanNET.

MATERIALS AND METHODS

We retrospectively reviewed 29 patients (40 computed tomographies [CTs]) with metastatic PanNETs. LTB was measured using a semiautomated 3D volumetric software program (volumetric assessment) or evaluated independently by 6 clinicians using CT imaging (visual assessment). The treatment map was classified into 3 groups based on LTB and Ki-67 index.

RESULTS

Visual and volumetric assessments of the LTB were well correlated. The LTB was significantly higher on visual assessment than volumetric assessment (P < 0.01). Categorization on the map was consistent between the visual and volumetric evaluations in 23 patients (equal group). The remaining 6 patients were overestimated by visual assessment (overestimated group). Progression-free survival was significantly longer in patients in the 'equal group' than the 'overestimated group' (981 vs 366 days, P < 0.01).

CONCLUSIONS

This pilot study revealed a good correlation between visual and volumetric assessments, and visual assessment overestimated LTB, compared to volumetric assessment.

Deep learning-based 3D quantitative total tumor burden predicts early recurrence of BCLC A and B HCC after resection

OBJECTIVES

This study aimed to evaluate the potential of deep learning (DL)-assisted automated three-dimensional quantitative tumor burden at MRI to predict postoperative early recurrence (ER) of hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

This was a single-center retrospective study enrolling patients who underwent resection for BCLC A and B HCC and preoperative contrast-enhanced MRI. Quantitative total tumor volume (cm3) and total tumor burden (TTB, %) were obtained using a DL automated segmentation tool. Radiologists' visual assessment was used to ensure the quality control of automated segmentation. The prognostic value of clinicopathological variables and tumor burden-related parameters for ER was determined by Cox regression analyses.

RESULTS

A total of 592 patients were included, with 525 and 67 patients assigned to BCLC A and B, respectively (2-year ER rate: 30.0% vs. 45.3%; hazard ratio (HR) = 1.8; p = 0.007). TTB was the most important predictor of ER (HR = 2.2; p < 0.001). Using 6.84% as the threshold of TTB, two ER risk strata were obtained in overall (p < 0.001), BCLC A (p < 0.001), and BCLC B (p = 0.027) patients, respectively. The BCLC B low-TTB patients had a similar risk for ER to BCLC A patients and thus were reassigned to a BCLC An stage; whilst the BCLC B high-TTB patients remained in a BCLC Bn stage. The 2-year ER rate was 30.5% for BCLC An patients vs. 58.1% for BCLC Bn patients (HR = 2.8; p < 0.001).

CONCLUSIONS

TTB determined by DL-based automated segmentation at MRI was a predictive biomarker for postoperative ER and facilitated refined subcategorization of patients within BCLC stages A and B.

CLINICAL RELEVANCE STATEMENT

Total tumor burden derived by deep learning-based automated segmentation at MRI may serve as an imaging biomarker for predicting early recurrence, thereby improving subclassification of Barcelona Clinic Liver Cancer A and B hepatocellular carcinoma patients after hepatectomy.

KEY POINTS

Total tumor burden (TTB) is important for Barcelona Clinic Liver Cancer (BCLC) staging, but is heterogenous. TTB derived by deep learning-based automated segmentation was predictive of postoperative early recurrence. Incorporating TTB into the BCLC algorithm resulted in successful subcategorization of BCLC A and B patients.

Exploring the significance of tumor volume in endometrial cancer: Clinical pathological features, prognosis, and adjuvant therapies

To assist clinicians in formulating treatment strategies for endometrial cancer (EC), this retrospective study explores the relationship between tumor volume and clinical pathological features, as well as prognosis, in patients undergoing staging surgery. Preoperative pelvic MRI examinations were conducted on 234 histologically confirmed EC patients. The ITK-SNAP software was employed to manually delineate the region of interest in the MRI images and calculate the tumor volume (MRI-TV). The analysis focused on investigating the relationship between MRI-TV and the clinical pathological features and prognosis of EC patients. Larger MRI-TV was found to be associated with various adverse prognostic factors (G3, deep myometrial invasion, cervical stromal invasion, lymphovascular space invasion, lymph node metastasis, advanced international federation of gynecology and obstetrics staging, and receipt of adjuvant therapy). The receiver operating characteristic curve indicated that MRI-TV ≥ 8 cm3 predicted deep myometrial invasion, and MRI-TV ≥ 12 cm3 predicted lymph node metastasis. Penalized spline (P-spline) regression analysis identified 14 cm3 of MRI-TV as the optimal prognostic cutoff value. MRI-TV ≥ 14 cm3 was an independent prognostic factor for overall survival and disease-free survival. For patients with MRI-TV ≥ 14 cm3, the disease-free survival rate with adjuvant therapy was superior to that of the sole staging surgery group. This study demonstrates a significant correlation between MRI-TV and clinical pathological features and prognosis in EC. For patients with MRI-TV ≥ 14 cm3, staging surgery followed by adjuvant therapy was superior to sole staging surgery.

Quantitative image features of gadoxetic acid-enhanced MRI for predicting glypican-3 expression of small hepatocellular carcinoma ≤3 cm

AIM

To explore the value of quantitative image features of gadoxetic acid-enhanced magnetic resonance imaging (MRI) for predicting Gglypican-3 (GPC3) expression of single hepatocellular carcinoma (HCC) ≤3 cm.

MATERIALS AND METHODS

One hundred and forty-nine patients with histopathologically confirmed HCC were included retrospectively. Quantitative image features and clinicopathological parameters were analysed. The significant predictors for GPC3 expression were identified using multivariate logistic regression analyses. Nomograms were constructed from the prediction model and the progression-free survival (PFS) rate was evaluated by the Kaplan-Meier method.

RESULTS

The tumour-to-liver signal intensity (SI) ratio on the hepatobiliary phase (HBP; odds ratio [OR] = 0.004; p=0.001), serum alpha-fetoprotein (AFP) > 20 ng/ml (OR=6.175; p<0.001), and non-smooth tumour margin (OR=4.866; p=0.002) were independent significant factors for GPC3 expression. When the three factors were combined, the diagnostic specificity was 97.7% (42/43). The nomogram based on the predictive model performed satisfactorily (C-index: 0.852). Kaplan-Meier curves showed that patients with GPC3-positive HCCs have lower PFS rates than patients with GPC3-negative HCCs (Log-rank test, p=0.006).

CONCLUSION

The tumour-to-liver SI ratio on the HBP combined with serum AFP >20 ng/ml and non-smooth tumour margin are potential predictive factors for GPC3 expression of small HCC ≤3cm. GPC3 expression is correlated with a poor prognosis in HCC patients.

Value of Multimodal Data From Clinical and Sonographic Parameters in Predicting Recurrence of Hepatocellular Carcinoma After Curative Treatment

OBJECTIVE

The objective of the work described here was to assess the value of the combination of pre-operative multimodal data-including clinical data, contrast-enhanced ultrasound (CEUS) information and liver stiffness measurement (LSM) based on 2-D shear wave elastography (SWE)-in predicting early (within 1 y) and late (after 1 y) recurrence of hepatocellular carcinoma (HCC) after curative treatment.

METHODS

We retrospectively included 101 patients with HCC who met the Milan criteria and received curative treatment. The multimodel data from clinical parameters, LSM by 2-D SWE and CEUS enhancement patterns were collected. The association between different variables in HCC recurrence was accessed using a Cox proportional hazard model. On the basis of the independent factors of early recurrence, models with different source variables were established (Clinical Model, CEUS-Clinical Model, SWE-Clinical Model, CEUS-SWE-Clinical Model). The goodness-of-fit of models was evaluated and the performance trends of different models were calculated by time-dependent area under the curve (AUC).

RESULTS

Two-dimensional SWE, CEUS enhancement patterns and clinical parameters (spleen length, multiple tumors, α-fetoprotein, albumin and prothrombin time) were independently associated with early recurrence (all p values <0.05). Multiple tumors and a decrease in albumin independently contributed to the late recurrence. The model fit of CEUS-SWE-Clinical Model was superior to other models in predicting early recurrence (all p values <0.05). The AUCs of the CEUS-Clinical Model were higher from 2 mo to 7 mo, while the SWE-Clinical Model had higher AUCs from 9 mo to 12 mo.

CONCLUSION

CEUS enhancement patterns and 2-D SWE were independent predictors of HCC early recurrence as the two factors contributed to the predictive performance at different times. The multimodal model, which included diverse data in predicting early HCC recurrence, had the best goodness-of-fit.

Comparison of quantitative volumetric analysis and linear measurement for predicting the survival of Barcelona Clinic Liver Cancer 0- and A stage hepatocellular carcinoma after radiofrequency ablation

PURPOSE

The prognostic role of the tumor volume in patients with hepatocellular carcinoma (HCC) at the Barcelona Clinic Liver Cancer (BCLC) 0 and A stages remains unclear. This study aims to compare the volumetric measurement with linear measurement in early HCC burden profile and clarify the optimal cut-off value of the tumor volume.

METHODS

The consecutive patients diagnosed with HCC who underwent initial and curative-intent radiofrequency ablation (RFA) were included retrospectively. The segmentation was performed semi-automatically, and enhanced tumor volume (ETV) as well as total tumor volume (TTV) were obtained. The patients were categorized into high- and low-tumor burden groups according to various cutoff values derived from commonly used diameter values, X-tile software, and decision-tree analysis. The inter- and intra-reviewer agreements were measured using the intra-class correlation coefficient. Univariate and multivariate time-to-event Cox regression analyses were performed to identify the prognostic factors of overall survival.

RESULTS

A total of 73 patients with 81 lesions were analyzed in the whole cohort with a median follow-up of 31.0 (interquartile range: 16.0–36.3). In tumor segmentation, excellent consistency was observed in intra- and inter-reviewer assessments. There was a strong correlation between diameter-derived spherical volume and ETV as well as ETV and TTV. As opposed to all linear candidates and 4,188 mm3 (sphere equivalent to 2 cm in diameter), ETV >14,137 mm3 (sphere equivalent to 3 cm in diameter) or 23,000 mm3 (sphere equivalent to 3.5 cm in diameter) was identified as an independent risk factor of survival. Considering the value of hazard ratio and convenience to use, when ETV was at 23,000 mm3, it was regarded as the optimal volumetric cut-off value in differentiating survival risk.

CONCLUSION

The volumetric measurement outperforms linear measurement on tumor burden evaluation for survival stratification in patients at BCLC 0 and A stages HCC after RFA.

Comparison of survival rates as predicted by total tumor volume or tumor burden score in patients with hepatocellular carcinoma concurrent with fatty liver disease and hepatitis B virus

OBJECTIVES

To analyze prognostic value of total tumor volume (TTV) and tumor burden score (TBS) in surgically treated patients with hepatocellular carcinoma and concurrent fatty liver disease and hepatitis B virus (FLD-HCC).

METHODS

FLD-HCC patients who treated with hepatectomy from 2010 to 2018 were analyzed. Prognostic performance of TTV and TBS was determined by ROC analysis. Patients were stratified into low and high tumor burden by optimal cutoff value of 113.4 cm3 for TTV or 6.3 points for TBS. Survival rates were compared between subgroups and independent risk factors were identified by Cox regression. Correlation between TTV and TBS was evaluated.

RESULTS

This study enrolled 342 FLD-HCC patients. Survival was significantly higher among patients with low tumor burden than among those with high tumor burden (p < 0.001). High TTV and TBS were independent risk factors for poor survival of FLD-HCC (HR: 3.27 (2.17-4.93) and 3.48 (2.31-5.26), respectively, all p < 0.001). ROC analyses revealed that TTV and TBS had comparable discriminative ability in stratifying overall and recurrence-free survival of FLD-HCC. Correlation analysis revealed a strong correlation between TTV and TBS.

CONCLUSIONS

Both TTV and TBS have comparable prognostic value and high TTV/TBS predicts poor survival of patients with FLD-HCC.