Hepatic capsular retraction: An updated MR imaging review

Clinical and DCE-CT signs in predicting microvascular invasion in cHCC-ICC

BACKGROUND

To predict the microvascular invasion (MVI) in patients with cHCC-ICC.

METHODS

A retrospective analysis was conducted on 119 patients who underwent CT enhancement scanning (from September 2006 to August 2022). They were divided into MVI-positive and MVI-negative groups.

RESULTS

The proportion of patients with CEA elevation was higher in the MVI-positive group than in the MVI-negative group, with a statistically significant difference (P = 0.02). The MVI-positive group had a higher rate of peritumoral enhancement in the arterial phase (P = 0.01) whereas the MVI-negative group had more oval and lobulated masses (P = 0.04). According to the multivariate analysis, the increase in CEA (OR = 10.15, 95% CI: 1.11, 92.48, p = 0.04), hepatic capsular withdrawal (OR = 4.55, 95% CI: 1.44, 14.34, p = 0.01) and peritumoral enhancement (OR = 6.34, 95% CI: 2.18, 18.40, p < 0.01) are independent risk factors for predicting MVI. When these three imaging signs are combined, the specificity of MVI prediction was 70.59% (series connection), and the sensitivity was 100% (parallel connection).

CONCLUSIONS

Our multivariate analysis found that CEA elevation, liver capsule depression, and arterial phase peritumoral enhancement were independent risk factors for predicting MVI in cHCC-ICC.

Translating imaging traits of mass-forming intrahepatic cholangiocarcinoma into the clinic: From prognostic to therapeutic insights

Background & Aims

The progress toward clinical translation of imaging biomarkers for mass-forming intrahepatic cholangiocarcinoma (MICC) is slower than anticipated. Questions remain on the biologic behaviour underlying imaging traits. We developed and validated imaging-based prognostic systems for resected MICCs with an appraisal of the tumour immune microenvironment (TIME) underpinning patient-specific imaging traits.

Methods

Between January 2009 and December 2019, a total of 322 patients who underwent dynamic computed tomography/magnetic resonance imaging and curative-intent resection for MICC at three hepatobiliary institutions were retrospectively recruited, divided into training (n = 193) and validation (n = 129) datasets. Two radiological and clinical scoring (RACS) systems, one integrating preoperative variables and one integrating preoperative and postoperative variables, were developed using Cox regression analysis. We then prospectively analysed the TIME of tissue samples from 20 patients who met study criteria from January 2021 to December 2021 using multiplexed immunofluorescence.

Results

Preoperative and postoperative MICC-RACS systems built on carbohydrate antigen 19-9, albumin, tumour number, radiological/pathological nodal status, pathological necrosis, and three radiological traits (arterial enhancement pattern, tumour boundary, and capsular retraction) demonstrated good performance in predicting disease-specific (C-statistic >0.80) and disease-free (C-statistic >0.75) survival that outperformed rival models and staging systems across study cohorts (P <0.05 for all). Patients with MICC-RACS score of 0-2 (low risk), 3-5 (medium risk), and ≥6 (high risk) had incrementally worse prognosis after surgery. Significant differences in spatial distribution and infiltration level of immune cells were identified between arterial enhancement patterns. Enhanced infiltration of immunosuppressive regulatory T cells and M2-like macrophages at the invasive margin were noted in tumours with distinct boundary and capsular retraction, respectively.

Conclusions

Our MICC-RACS systems are simple but powerful prognostic tools that may facilitate the understanding of spatially distinct TIMEs and patient-tailored immunotherapy approach.

Impact and Implications

The progress toward clinical translation of imaging biomarkers for mass-forming intrahepatic cholangiocarcinoma (MICC) is slower than anticipated. Questions remain on the biologic behaviour of MICC underlying imaging traits. In this study, we proposed novel and easy-to-use tools, built on radiological and clinical features, that demonstrated good performance in predicting the prognosis either before or after surgery and outperformed rival models/systems across major imaging modalities. The characteristic radiological traits integrated into prognostic systems (arterial enhancement pattern, tumour boundary, and capsular retraction) were highly correlated with heterogeneous tumour-immune microenvironments, thereby renovating treatment paradigms for this difficult-to-treat disease.

Hepatic epithelioid hemangioendothelioma-a single-institution experience with 51 cases

Objectives

The aim of the present study was to describe the experience at a single institution in the management of hepatic epithelioid hemangioendothelioma (HEHE).

Methods

We included 51 patients with histologically confirmed HEHE. We performed log-rank (Cox-Mantel) survival analyses using Kaplan-Meier methods to test differences in survival between patients in different groups. Univariate Cox regression analyses and multivariate proportional hazards regression model were carried out to identify independent prognostic factors.

Results

Different imaging modalities were used to diagnose HEHE with various presentations. Liver resection (LR), liver transplantation (LT), systemic treatment (ST), and surveillance had been used in our study. A significant difference was noted between the LR group and the surveillance group with respect to mean survival (p = 0.006), as was in the LR group and the ST group (p = 0.036), and in surgical approach (LR and LT) and nonsurgical approach (ST and surveillance) (p = 0.008). The mean survival between the ST group and the surveillance group was not significantly different (p = 0.851). LR (p = 0.010) and surgical approach (p = 0.014) were favorable predictors of outcome, while macrovascular invasion (MaVI) (p = 0.037), lung metastasis (p = 0.040), and surveillance (p = 0.033) were poor prognostic factors in univariate analysis. Multivariate analysis showed that LR (p = 0.010) and surgical approach (p = 0.014) were independently associated with good OS, while surveillance (p = 0.033) was independently associated with poor OS. After adjusting for confounding factors, patients in the LR group have much better OS than those in the surveillance group (p = 0.013). However, there was no significant difference in OS between the LR group and ST group (p = 0.254), as was in the ST group and the surveillance group (p = 0.857).

Conclusions

The definitive diagnosis of HEHE was dependent on histopathology, and it was not possible to make a specific diagnosis without biopsy because the radiological findings were similar to those in some hepatic malignancies. ST was not recommended for patients who were not candidates for surgical approaches, and surgical approaches should be warranted regardless of disease stage. The retrospective nature and the small size of the data limited the generalizability of the study, designing a worldwide database that contains all data about patients with HEHE independent of their therapy, which was highly recommended.

CT-based clinico-radiological nomograms for prognosis prediction in patients with intrahepatic mass-forming cholangiocarcinoma: a multi-institutional study

OBJECTIVES

To establish prognostic nomograms based on CT imaging features for predicting the prognosis in patients with intrahepatic mass-forming cholangiocarcinoma (IMCC) before and after surgery.

METHODS

Two models were established for overall survival (OS) prediction in a training set (179 IMCC patients underwent surgery at institution 1 from 2009 to 2019): imaging-based nomogram included imaging features and clinical characteristics acquired before surgery; postoperative nomogram included imaging-based score, equal to the linear predictor of the imaging-based nomogram, and pathological parameters. Both prognostic nomograms were validated in an independent external dataset (103 IMCC patients received surgical treatment at two independent institutions from 2009 to 2019). Predictive performance and discrimination were evaluated and compared with the common prognostic models.

RESULTS

The imaging-based nomogram was developed according to preoperative serum carbohydrate antigen 19-9 and four imaging features including multiple nodules, arterial enhancement pattern, CT-reported lymph node (LN) metastasis, and capsular retraction; the postoperative nomogram was built based on the imaging-based score and three pathological parameters including tumor differentiation grade, capsular invasion, and LN status. Both nomograms presented improved prognostic performance and discrimination (concordance index, 0.770-0.812; integrated Brier score, 0.120-0.138) compared with the common prognostic models in the training and external validation datasets. Besides, the nomograms stratified IMCC patients into two risk strata for OS.

CONCLUSIONS

Nomograms based on CT imaging features can provide accurate individual survival prediction for IMCC patients before and after surgery, which may help to improve personalized treatment.

KEY POINTS

• Imaging features including multiple nodules, arterial enhancement pattern, CT-reported LN metastasis, and capsular retraction were poor independent prognostic factors for IMCC patients. • The imaging-based nomograms presented improved prognostic performance and discrimination compared with the common prognostic models. • The nomograms can provide accurate individual survival prediction for IMCC patients before and after surgery.

Imaging of hepatic hemangioma: from A to Z

The hemangioma is the most common solid lesion of the liver. Therefore, radiologists must know the typical and atypical imaging findings of this lesion in order to reach a correct diagnosis and avoid diagnostic errors. However, only few papers have comprehensively described the entire spectrum of atypical and uncommon imaging features. In this updated review, we provide the imaging features of hepatic hemangioma, in both typical and atypical forms, as well as its association with abnormalities in the adjacent hepatic parenchyma and other hepatic lesions, and its complications.