Combined DCE-MRI- and FDG-PET enable histopathological grading prediction in a rat model of hepatocellular carcinoma

Conversion therapy for advanced hepatocellular carcinoma in the era of precision medicine: Current status, challenges and opportunities

Hepatocellular carcinoma (HCC), the most prevalent malignancy of the digestive tract, is characterized by a high mortality rate and poor prognosis, primarily due to its initial diagnosis at an advanced stage that precludes any surgical intervention. Recent advancements in systemic therapies have significantly improved oncological outcomes for intermediate and advanced-stage HCC, and the combination of locoregional and systemic therapies further facilitates tumor downstaging and increases the likelihood of surgical resectability for initially unresectable cases following conversion therapies. This shift toward high conversion rates with novel, multimodal treatment approaches has become a principal pathway for prolonged survival in patients with advanced HCC. However, the field of conversion therapy for HCC is marked by controversies, including the selection of potential surgical candidates, formulation of conversion therapy regimens, determination of optimal surgical timing, and application of adjuvant therapy post-surgery. Addressing these challenges and refining clinical protocols and research in HCC conversion therapy is essential for setting the groundwork for future advancements in treatment strategies and clinical research. This narrative review comprehensively summarizes the current strategies and clinical experiences in conversion therapy for advanced-stage HCC, emphasizing the unresolved issues and the path forward in the context of precision medicine. This work not only provides a comprehensive overview of the evolving landscape of treatment modalities for conversion therapy but also paves the way for future studies and innovations in this field.

Dynamic 2-deoxy-D-glucose-enhanced multispectral optoacoustic tomography for assessing metabolism and vascular hemodynamics of breast cancer

Clinical tools for measuring tumor vascular hemodynamics, such as dynamic contrast-enhanced MRI, are clinically important to assess tumor properties. Here we explored the use of multispectral optoacoustic tomography (MSOT), which has a high spatial and temporal resolution, to measure the intratumoral pharmacokinetics of a near-infrared-dye-labeled 2-Deoxyglucose, 2-DG-800, in orthotropic 2-LMP breast tumors in mice. As uptake of 2-DG-800 is dependent on both vascular properties, and glucose transporter activity - a widely-used surrogate for metabolism, we evaluate hemodynamics of 2-DG-MP by fitting the dynamic MSOT signal of 2-DG-800 into two-compartment models including the extended Tofts model (ETM) and reference region model (RRM). We showed that dynamic 2-DG-enhanced MSOT (DGE-MSOT) is powerful in acquiring hemodynamic rate constants, including Ktrans and Kep, via systemically injecting a low dose of 2-DG-800 (0.5 µmol/kg b.w.). In our study, both ETM and RRM are efficient in deriving hemodynamic parameters in the tumor. Area-under-curve (AUC) values (which correlate to metabolism), and Ktrans and Kep values, can effectively distinguish tumor from muscle. Hemodynamic parameters also demonstrated correlations to hemoglobin, oxyhemoglobin, and blood oxygen level (SO2) measurements by spectral unmixing of the MSOT data. Together, our study for the first time demonstrated the capability of DGE-MSOT in assessing vascular hemodynamics of tumors.

Preoperative determination of pathological grades of primary single HCC: development and validation of a scoring model

PURPOSE

This study aimed to establish a reliable diagnostic score model for the preoperative determination of pathological grade in HCC based on gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI and biochemical indicators.

METHODS

In this retrospective study, we analyzed 139 patients with HCC who underwent Gd-EOB-DTPA MRI between 2014 and 2020, including an establishment cohort of 76 patients and a validation cohort of 63 patients. Based on the imaging features demonstrated on Gd-EOB-DTPA MRI images and biochemical indicators of the establishment cohort, a scoring model based on logistic regression was developed, and compared with postoperative pathological findings in terms of effective determination of pathological grade. The validity of the scoring model was assessed by ROC curves and an independent external validation cohort.

RESULTS

Three parameters related to pathological grades were identified, including maximum diameter of the tumor, peritumoral hypointensity in the hepatobiliary phase, and [alkaline phosphatase (U/L) + gamma glutamyl transpeptidase (U/L)]/ lymphocyte count (× 10⁹/L) (AGLR) ratios. Based on these three parameters, a scoring model was developed. ROC curve showed that a score of > 5 was set as the threshold for determining pathological grades with accuracy, sensitivity, specificity, PPV, and NPV of 89.5%, 75.0%, 95.1%, 85.7%, and 90.7%, respectively.

CONCLUSION

The study provided the groundwork for a promising and easily implementable scoring model for preoperative determination of HCC pathological grades, for which further validation should be pursued.

Radiomics for the detection of microvascular invasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, accounting for about 90% of liver cancer cases. It is currently the fifth most common cancer in the world and the third leading cause of cancer-related mortality. Moreover, recurrence of HCC is common. Microvascular invasion (MVI) is a major factor associated with recurrence in postoperative HCC. It is difficult to evaluate MVI using traditional imaging modalities. Currently, MVI is assessed primarily through pathological and immunohistochemical analyses of postoperative tissue samples. Needle biopsy is the primary method used to confirm MVI diagnosis before surgery. As the puncture specimens represent just a small part of the tumor, and given the heterogeneity of HCC, biopsy samples may yield false-negative results. Radiomics, an emerging, powerful, and non-invasive tool based on various imaging modalities, such as computed tomography, magnetic resonance imaging, ultrasound, and positron emission tomography, can predict the HCC-MVI status preoperatively by delineating the tumor and/or the regions at a certain distance from the surface of the tumor to extract the image features. Although positive results have been reported for radiomics, its drawbacks have limited its clinical translation. This article reviews the application of radiomics, based on various imaging modalities, in preoperative evaluation of HCC-MVI and explores future research directions that facilitate its clinical translation.

Early Diagnosis Value of DCE-MRI Hemodynamic Parameters in Hepatocellular Carcinoma

Objective

To probe into the early diagnosis value of transfer coefficient (K^trans) and rate constant (K_ep) of the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) hemodynamic parameters in patients with hepatocellular carcinoma (HCC).

Methods

Fifty patients with HCC diagnosed in our hospital from May 2017 to May 2020 were studied retrospectively as the patient group (PG), and 45 cases with benign liver nodules diagnosed in our hospital during the same period were collected as the control group (CG). K^trans, K_ep, and AFP levels were compared between PG and CG. The diagnostic value of K^trans and K_ep in HCC were observed, and their correlations with patient clinical data were analyzed. The diagnostic value of K^trans and K_ep combined with AFP in clinical staging, differentiation degree, and distant metastasis was compared.

Results

K^trans, K_ep, and AFP were notably higher in cases than in controls (P < 0.05), indicating their high diagnostic value in HCC. K^trans and K_ep present elevated expression in HCC patients with clinical stage III-IV, low differentiation, and distant metastasis (P < 0.05). Furthermore, it is found that the combined detection with either K^trans or K_ep can improve the clinical diagnostic value of AFP in the clinical stage and differentiation of HCC. However, the combined diagnosis showed little effect in raising the sensitivity of AFP in distant metastasis.

Conclusion

DCE-MRI hemodynamic parameters K^trans and K_ep have high clinical value in early diagnosis and differentiation of HCC patients.

Correlation of in vivo imaging to morphomolecular pathology in translational research: challenge accepted

Correlation of in vivo imaging to histomorphological pathology in animal models requires comparative interdisciplinary expertise of different fields of medicine. From the morphological point of view, there is an urgent need to improve histopathological evaluation in animal model-based research to expedite translation into clinical applications. While different other fields of translational science were standardized over the last years, little was done to improve the pipeline of experimental pathology to ensure reproducibility based on pathological expertise in experimental animal models with respect to defined guidelines and classifications. Additionally, longitudinal analyses of preclinical models often use a variety of imaging methods and much more attention should be drawn to enable for proper co-registration of in vivo imaging methods with the ex vivo morphological read-outs. Here we present the development of the Comparative Experimental Pathology (CEP) unit embedded in the Institute of Pathology of the Technical University of Munich during the Collaborative Research Center 824 (CRC824) funding period together with selected approaches of histomorphological techniques for correlation of in vivo imaging to morphomolecular pathology.

Respiratory motion correction for enhanced quantification of hepatic lesions in simultaneous PET and DCE-MR imaging

Simultaneous positron-emission tomography (PET)-magnetic resonance (MR) imaging is a hybrid technique in oncological hepatic imaging combining soft-tissue and functional contrast of dynamic contrast enhanced MR (DCE-MR) with metabolic information from PET. In this context, respiratory motion represents a major challenge by introducing blurring, artifacts and misregistration in the liver. In this work, we propose a free-breathing 3D non-rigid respiratory motion correction framework for simultaneously acquired DCE-MR and PET data, which makes use of higher spatial resolution MR data to derive motion information used directly during image reconstruction to minimize image blurring and motion artifacts. The main aim was to increase contrast of hepatic metastases to improve their detection and characterization. DCE-MR data were acquired at 3T through a golden radial phase encoding scheme, enabling derivation of motion fields. These were used in the motion compensated image reconstruction of DCE-MR time-series (48 time-points, 6 s temporal resolution, 1.5 mm isotropic spatial resolution) and 3D PET activity map, which was subsequently interpolated to the DCE-MR resolution. The extended Tofts model was fitted to DCE-MR data, obtaining functional parametric maps related to perfusion such as the endothelial permeability (Kt). Fifty-seven hepatic metastases were identified and analyzed. Quantitative evaluations of motion correction in PET images demonstrated average percentage increases of 16% ± 5% (mean ± SD) in Contrast (C), 18% ± 6% in SUV_meanand 14% ± 2% in SUV_max, while DCE-MR andKtscored contrast-to-noise-ratio increases of 64% ± 3% and 90% ± 6%, respectively. Motion-corrected data visually showed improved image contrast of hepatic metastases and effectively reduced blurring and motion artefacts. Scatter plots of SUV_meanversusKtsuggested that the proposed framework improved differentiation ofKtmeasurements. The presented motion correction framework for simultaneously acquired PET-DCE-MR data provides accurately aligned images with increased contrast of hepatic lesions allowing for improved detection and characterization.

Hyperpolarized 13C pyruvate magnetic resonance spectroscopy for in vivo metabolic phenotyping of rat HCC

The in vivo assessment of tissue metabolism represents a novel strategy for the evaluation of oncologic disease. Hepatocellular carcinoma (HCC) is a high-prevalence, high-mortality tumor entity often discovered at a late stage. Recent evidence indicates that survival differences depend on metabolic alterations in tumor tissue, with particular focus on glucose metabolism and lactate production. Here, we present an in vivo imaging technique for metabolic tumor phenotyping in rat models of HCC. Endogenous HCC was induced in Wistar rats by oral diethyl-nitrosamine administration. Peak lactate-to-alanine signal ratios (L/A) were assessed with hyperpolarized magnetic resonance spectroscopic imaging (HPMRSI) after [1-¹³C]pyruvate injection. Cell lines were derived from a subset of primary tumors, re-implanted in nude rats, and assessed in vivo with dynamic hyperpolarized magnetic resonance spectroscopy (HPMRS) after [1-¹³C]pyruvate injection and kinetic modelling of pyruvate metabolism, taking into account systemic lactate production and recirculation. For ex vivo validation, enzyme activity and metabolite concentrations were spectroscopically quantified in cell and tumor tissue extracts. Mean peak L/A was higher in endogenous HCC compared to non-tumorous tissue. Dynamic HPMRS revealed higher pyruvate-to-lactate conversion rates (k_pl) and lactate signal in subcutaneous tumors derived from high L/A tumor cells, consistent with ex vivo measurements of higher lactate dehydrogenase (LDH) levels in these cells. In conclusion, HPMRS and HPMRSI reveal distinct tumor phenotypes corresponding to differences in glycolytic metabolism in HCC tumor tissue.