Comparison of different 4D CT-Perfusion algorithms to visualize lesions after microwave ablation in an in vivo porcine model

Imaging in interventional oncology, the better you see, the better you treat

Imaging and image processing is the fundamental pillar of interventional oncology in which diagnostic, procedure planning, treatment and follow-up are sustained. Knowing all the possibilities that the different image modalities can offer is capital to select the most appropriate and accurate guidance for interventional procedures. Despite there is a wide variability in physicians preferences and availability of the different image modalities to guide interventional procedures, it is important to recognize the advantages and limitations for each of them. In this review, we aim to provide an overview of the most frequently used image guidance modalities for interventional procedures and its typical and future applications including angiography, computed tomography (CT) and spectral CT, magnetic resonance imaging, Ultrasound and the use of hybrid systems. Finally, we resume the possible role of artificial intelligence related to image in patient selection, treatment and follow-up.

Short-term PET-derived kinetic estimation for the diagnosis of hepatocellular carcinoma: a combination of the maximum-slope method and dual-input three-compartment model

BACKGROUND

Kinetic estimation provides fitted parameters related to blood flow perfusion and fluorine-18-fluorodeoxyglucose (¹⁸F-FDG) transport and intracellular metabolism to characterize hepatocellular carcinoma (HCC) but usually requires 60 min or more for dynamic PET, which is time-consuming and impractical in a busy clinical setting and has poor patient tolerance.

METHODS

This study preliminarily evaluated the equivalence of liver kinetic estimation between short-term (5-min dynamic data supplemented with 1-min static data at 60 min postinjection) and fully 60-min dynamic protocols and whether short-term ¹⁸F-FDG PET-derived kinetic parameters using a three-compartment model can be used to discriminate HCC from the background liver tissue. Then, we proposed a combined model, a combination of the maximum-slope method and a three-compartment model, to improve kinetic estimation.

RESULTS

There is a strong correlation between the kinetic parameters K₁ ~ k₃, HPI and [Formula: see text] in the short-term and fully dynamic protocols. With the three-compartment model, HCCs were found to have higher k₂, HPI and k₃ values than background liver tissues, while K₁, k₄ and [Formula: see text] values were not significantly different between HCCs and background liver tissues. With the combined model, HCCs were found to have higher HPI, K₁ and k₂, k₃ and [Formula: see text] values than background liver tissues; however, the k₄ value was not significantly different between HCCs and the background liver tissues.

CONCLUSIONS

Short-term PET is closely equivalent to fully dynamic PET for liver kinetic estimation. Short-term PET-derived kinetic parameters can be used to distinguish HCC from background liver tissue, and the combined model improves the kinetic estimation.

CLINICAL RELEVANCE STATEMENT

Short-term PET could be used for hepatic kinetic parameter estimation. The combined model could improve the estimation of liver kinetic parameters.

Making timely remedial measures after TACE based on the results of cone-beam CT liver perfusion

OBJECTIVE

To evaluate the feasibility and safety of using cone-beam CT (CBCT) to measure changes in parenchymal blood volume (PBV) of patients with hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) and to guide microwave ablation (MWA) for residual tumors.

METHODS

A retrospective study was performed on 42 patients with HCC who completed TACE and received CBCT-guided perfusion imaging. The residual active lesions after TACE were supplemented with MWA to complete the treatment process according to the residual PBV. The outcomes were analyzed, including PBV changes, interventional-related complications, local tumor progression (LTP) and overall survival (OS).

RESULTS

Technical success was achieved in all lesions. Correlation analysis revealed that greater volume of residual PBV after MWA is negatively correlated with LTP. (p = .000); and the decrease of PBV was positively correlated with LTP (p = .000). All adverse events and complications were CTCAE Grade 1/2. After combination treatment, the 1-, 3-, and 5-year LTP-free survival were 97.6%, 69.0% and 15.1%, respectively, with a median LTP of 49.0 months (95% CI:43.129,54.871). Multivariate Cox regression revealed that the residual PBV > 13 ml/1000 was an independent factor predicting a shorter OS and LTP (Both p< .05). For LTP, multivariate Cox regression showed that a tumor in a single lesion were independently predicted to have a longer LTP in patients with HCC (p = .033).

CONCLUSION

CBCT is feasible and safe to use to measure changes in the PBV before and after TACE treatment, while it can also guide MWA for the treatment of residual tumors in one session.

The diagnostic performance of perfusion CT in the detection of local tumor recurrence in head and neck cancer

BACKGROUND

Detecting local tumor recurrence from post-treatment changes in head and neck cancer (HNC) remains a challenge. Based on the hypothesis that post-therapeutically altered tissue is bradytroph, lower perfusion values are expected in perfusion CT (PCT) while higher perfusion values are expected in recurrent malignant tissue.

OBJECTIVES

This prospective study investigates PCT for post-treatment recurrent HNC detection with a maximum slope algorithm.

METHODS

A total of 80 patients who received PCT of the head and neck for post-therapy follow-up, of which 63 had no tumor recurrence and 17 presented a histopathologically confirmed recurrence were examined. Regions of interest were placed in the location of the initial tumor, in reference ipsilateral nuchal muscle tissue and the corresponding internal carotid artery. Perfusion was calculated using a single-input maximum slope algorithm.

RESULTS

With PCT, recurrent HNC can be differentiated from post-treatment tissue (p < 0.05). It further allows delineating recurrent tumor tissue from benign nuchal tissue of reference (p < 0.05). PCT data of patients with and without recurrent HNC are comparable as perfusion values of reference tissues in patients with and without HNC do not differ (p > 0.05).

CONCLUSIONS

PCT in combination with a commercially available maximum slope algorithm offers radiologists a reliable imaging tool to detect recurrent head and neck cancer within post-therapeutically altered tissue.