Fusion imaging techniques and contrast-enhanced ultrasound for thermal ablation of hepatocellular carcinoma - A prospective randomized controlled trial

3D-CEUS/MRI-CEUS fusion imaging vs 2D-CEUS after locoregional therapies for hepatocellular carcinoma: a multicenter prospective study of therapeutic response evaluation

OBJECTIVES

To compare the diagnostic accuracy of 3D contrast-enhanced ultrasound (CEUS)/MRI-CEUS fusion imaging with 2D-CEUS in assessing the response of hepatocellular carcinoma (HCC) to locoregional therapies in a multicenter prospective study.

MATERIALS AND METHODS

A consecutive series of patients with HCC scheduled for locoregional treatment were enrolled between April 2021 and March 2023. Patients were randomly divided into 3D-CEUS/MRI-CEUS fusion imaging group (3D/fusion group) or 2D-CEUS group (2D group). CEUS was performed 1 week before and 4-6 weeks after locoregional treatment. Contrast-enhanced MRI (CE-MRI) 4-6 weeks after treatment was set as the reference standard. CEUS images were evaluated for the presence or absence of viable tumors. Diagnostic performance criteria, including sensitivity, specificity, accuracy, and area under the curve (AUC), were determined for each modality.

RESULTS

A total of 140 patients were included, 70 patients in the 2D group (mean age, 60.2 ± 10.4 years) and 70 patients in the 3D/fusion group (mean age, 59.8 ± 10.6 years). The sensitivity of the 3D/fusion group was 100.0% (95% CI: 75.9, 100.0), higher than that of the 2D group (55.6%, 95% CI: 22.7, 84.7; p = 0.019). The specificity of the 3D/fusion group was 96.3% (95% CI: 86.2, 99.4), which was comparable to that of the 2D group (98.4%, 95% CI: 90.0, 99.9; p = 0.915). The AUC of the 3D/fusion group was 0.98 (95% CI: 0.95, 1.00), higher than that of the 2D group (0.77, 95% CI: 0.56, 0.98; p = 0.020).

CONCLUSION

3D-CEUS/MRI-CEUS fusion imaging exhibits superior diagnostic accuracy in evaluating the treatment response to locoregional therapies for HCC.

CLINICAL RELEVANCE STATEMENT

3D-CEUS/MRI-CEUS fusion imaging can be applied for post-treatment assessment of residual tumors in HCC undergoing locoregional treatment, offering potential benefits in terms of accurate diagnosis and clinical management.

KEY POINTS

Evaluating for HCC recurrence following locoregional therapy is important. 3D-CEUS/MRI-CEUS fusion imaging achieved a higher sensitivity than 2D-CEUS in assessing residual tumors after locoregional therapies. 3D-CEUS/MRI-CEUS fusion imaging can help clinicians intervene early in residual HCC lesions after locoregional treatment.

Three-dimensional ultrasound fusion imaging in precise needle placement for thermal ablation of hepatocellular carcinoma

PURPOSE

To investigate the value of three-dimensional ultrasound fusion imaging (3DUS FI) technique for guiding needle placement in hepatocellular carcinoma (HCC) thermal ablation.

METHODS

A total of 57 patients with 60 HCCs with 3DUS FI-guided thermal ablation were retrospectively included in the study. 3DUS volume data of liver were acquired preoperatively by freehand scanning with the tumor and predetermined 5 mm ablative margin automatically segmented. Plan of needle placement was made through a predetermined simulated ablation zone to ensure a 5 mm ablative margin with the coverage rate toward tumor and ablative margin. With real-time ultrasound and 3DUS fusion imaging, ablation needles were placed according to the plan. After ablation, the ablative margin was immediately evaluated by contrast-enhanced ultrasound and 3DUS fusion imaging. The rate of adequate ablative margin, complete response (CR), local tumor progression (LTP), disease-free survival (DFS), and overall survival (OS) was evaluated.

RESULTS

According to postoperative contrast-enhanced CT or MR imaging, the complete response rate was 100% (60/60), and 83% of tumors (30/36) achieved adequate ablative margin (>5 mm) three-dimensionally. During the follow-up period of 6.0-42.6 months, LTP occurred in 5 lesions, with 1- and 2-year LTP rates being 7.0% and 9.4%. The 1- and 2-year DFS rates were 76.1% and 65.6%, and 1- and 2-year OS rates were 98.1% and 94.0%. No major complications or ablation-related deaths were observed in any patients.

CONCLUSIONS

Three-dimensional ultrasound fusion imaging technique may improve the needle placement of thermal ablation for HCC and reduce the rate of LTP.

Enhanced Precision and Safety in Thermal Ablation: O-Arm Cone Beam Computed Tomography with Magnetic Resonance Imaging Fusion for Spinal Column Tumor Targeting

Spinal metastatic tumors are common and often cause debilitating symptoms. Image-guided percutaneous thermal ablation (IPTA) has gained significant recognition in managing spinal column tumors due to its exceptional precision and effectiveness. Conventional guidance modalities, including computed tomography, fluoroscopy, and ultrasound, have been important in targeting spinal column tumors while minimizing harm to adjacent critical structures. This study presents a novel approach utilizing a fusion of cone beam computed tomography with magnetic resonance imaging to guide percutaneous thermal ablation for four patients with secondary spinal column tumors. The visual analog scale (VAS) evaluated the procedure effectiveness during an 18-month follow-up. Percutaneous vertebroplasty was performed in two cases, and a thermostat was used during all procedures. Imaging was performed using the Stealth Station navigation system Spine 8 (SSS8) and a 1.5T MRI machine. The fusion of CBCT with MRI allowed for precise tumor localization and guidance for thermal ablation. Initial results indicate successful tumor ablation and symptom reduction, emphasizing the potential of CBCT-MRI fusion in spinal column tumor management. This innovative approach is promising in optimizing therapy for secondary spinal column tumors. Further studies are necessary to validate its efficacy and applicability.

High-security automatic path planning of radiofrequency ablation for liver tumors

BACKGROUND AND OBJECTIVE

Radiofrequency ablation (RFA) is an effective method for the treatment of liver tumors. Preoperative path planning, which plays a crucial role in RFA treatment, requires doctors to have significant experience and ability. Specifically, correct and highly active preoperative path planning should ensure the safety of the whole puncturing process, complete ablation of tumors and minimal damage to healthy tissues.

METHODS

In this paper, a high-security automatic multiple puncture path planning method for liver tumors is proposed, in which the optimization of the ablation number, puncture number, target positions and puncture point positions subject to comprehensive clinical constraints are studied. In particular, both the safety of the puncture path and the distribution of ablation ellipsoids are taken into consideration. The influence of each constraint on the safety of the whole puncturing process is discussed in detail. On this basis, the efficiency of the planning method is obviously improved by simplifying the computational data and optimized variables. In addition, the performance and adaptability of the proposed method to large and small tumors are compared and summarized.

RESULTS

The proposed method is evaluated on 10 liver tumors of various geometric characteristics from 7 cases. The test results show that the average path planning time and average ablation efficiency are 41.4 s and 60.19%, respectively. For tumors of different sizes, the planning results obtained from the proposed method have similar healthy tissue coverage. Through the clinical evaluation of doctors, the planning results meet the needs of RFA for liver tumors.

CONCLUSIONS

The proposed method can provide reasonable puncture paths in RFA planning, which is beneficial to ensure the safety and efficiency of liver tumor ablation.

Fusion imaging versus ultrasound-guided percutaneous thermal ablation of liver cancer: a meta-analysis

BACKGROUND

Ultrasound-guided percutaneous thermal ablation has become an alternative treatment for small hepatocellular carcinoma (HCC). Recent evidence suggests that fusion imaging (FI) may improve the feasibility and efficacy of thermal ablation for HCC, while the clinical evidence remains limited.

PURPOSE

To compare FI versus ultrasound-guided thermal ablation for HCC.

MATERIAL AND METHODS

Relevant cohort or randomized controlled trials were found by searching Medline, Web of Science, Cochrane Library, and Embase. The pooling of results was performed using a random-effects model incorporating heterogeneity.

RESULTS

In this meta-analysis, 15 studies involving 1472 patients (1831 tumors) for FI-guided ablation and 1380 patients (1864 tumors) for ultrasound-guided ablation were included. Pooled results showed that compared to conventional HCC ablation guided by ultrasound, the FI-guided procedure showed a similar technique efficacy rate (risk ratio [RR] = 1.01, 95% confidence interval [CI] = 1.00-1.02, P = 0.25; I2 = 30%). However, FI-guided tumor ablation was associated with a lower incidence of overall complications (RR = 0.70, 95% CI = 0.50-0.97, P = 0.03; I2 = 0%). Moreover, patients receiving FI-guided tumor ablation had a lower risk of local tumor progression during follow-up than those with ultrasound-guided ablation (RR = 0.61, 95% CI = 0.47-0.78, P < 0.001; I2 = 13%). Subgroup analysis according to FI strategy, imaging techniques in controls, and tumor diameter showed consistent results (p for subgroup difference all >0.05).

CONCLUSION

FI-guided thermal ablation may be more effective and safer than ultrasound-guided ablation for patients with HCC.

Efficacy of fusion imaging for immediate post-ablation assessment of malignant liver neoplasms: A systematic review

BACKGROUND

Percutaneous thermal ablation has become the preferred therapeutic treatment option for liver cancers that cannot be resected. Since ablative zone tissue changes over time, it becomes challenging to determine therapy effectiveness over an extended period. Thus, an immediate post-procedural evaluation of the ablation zone is crucial, as it could influence the need for a second-look treatment or follow-up plan. Assessing treatment response immediately after ablation is essential to attain favorable outcomes. This study examines the efficacy of image fusion strategies immediately post-ablation in liver neoplasms to determine therapeutic response.

METHODOLOGY

A comprehensive systematic search using PRISMA methodology was conducted using EMBASE, MEDLINE (via PUBMED), and Cochrane Library Central Registry electronic databases to identify articles that assessed the immediate post-ablation response in malignant hepatic tumors with fusion imaging (FI) systems. The data were retrieved on relevant clinical characteristics, including population demographics, pre-intervention clinical history, lesion characteristics, and intervention type. For the outcome metrics, variables such as average fusion time, intervention metrics, technical success rate, ablative safety margin, supplementary ablation rate, technical efficacy rate, LTP rates, and reported complications were extracted.

RESULTS

Twenty-two studies were included for review after fulfilling the study eligibility criteria. FI's immediate technical success rate ranged from 81.3% to 100% in 17/22 studies. In 16/22 studies, the ablative safety margin was assessed immediately after ablation. Supplementary ablation was performed in 9 studies following immediate evaluation by FI. In 15/22 studies, the technical effectiveness rates during the first follow-up varied from 89.3% to 100%.

CONCLUSION

Based on the studies included, we found that FI can accurately determine the immediate therapeutic response in liver cancer ablation image fusion and could be a feasible intraprocedural tool for determining short-term post-ablation outcomes in unresectable liver neoplasms. There are some technical challenges that limit the widespread adoption of FI techniques. Large-scale randomized trials are warranted to improve on existing protocols. Future research should emphasize improving FI's technological capabilities and clinical applicability to a broader range of tumor types and ablation procedures.

Ultrasound fusion imaging for improving diagnostic and therapeutic strategies of focal liver lesions: A preliminary study

PURPOSE

To assess the effect of ultrasound (US) fusion imaging on the clinical diagnostic and therapeutic strategies of focal liver lesions, which are difficult to detect or diagnose by conventional US.

METHODS

From November 2019 to June 2022, 71 patients with invisible or undiagnosed focal liver lesions who underwent fusion imaging combining US with CT or MR were included in this retrospective study. The reasons for US fusion imaging were as follows: (1) lesions that were undetectable or inconspicuous on B-mode US; (2) post-ablation lesions that could not be assessed accurately by B-mode US; (3) to evaluate whether the lesions detected by B-mode US that were consistent with those presented on MRI/CT images.

RESULTS

Of the 71 cases, 43 cases were single lesions, and 28 cases were multiple lesions. Among the 46 cases which were invisible on conventional US, the display rate of lesions using US-CT/MRI fusion imaging was 30.8%, and that combined with CEUS was 76.9%. US-guided biopsy was performed in 30 patients after the detection and localization determined by fusion imaging, with a positive rate of 73.3%. Six patients with recurrence after ablation therapy were all detected and located accurately after fusion imaging, and 4 of them successfully underwent ablation therapy again.

CONCLUSION

Fusion imaging contributes to the understanding of the anatomical relationship between lesion location and blood vessels. Additionally, fusion imaging can improve the diagnostic confidence, be helpful to guide interventional operations, and hence be conducive to clinical therapeutic strategies.

The value of contrast-enhanced ultrasound quantitative parameters in the prognosis prediction of hepatocellular carcinoma after thermal ablation: a retrospective cohort study

BACKGROUND

The postoperative recurrence rate is the main factor affecting the prognosis of hepatocellular carcinoma (HCC) patients, this study sought to investigate the value of contrast-enhanced ultrasound (CEUS) quantitative parameters in predicting the recurrence and the survival of HCC patients after thermal ablation.

METHODS

The data of 97 patients with pathologically diagnosed HCC who underwent thermal ablation were retrospectively included in this study. The patients had an average age of 46.6 years (range, 23-79 years), and 79 were male and 18 were female. CEUS follow-up was performed at 1- and 3-month after thermal ablation, then at 6-month intervals thereafter for 5 years. CEUS was performed before thermal ablation, and the results were analyzed quantitatively using CEUS perfusion software (VueBox^®, Bracco, Italy). The ratios of the CEUS quantitative parameters between the HCC lesions and reference liver parenchyma were calculated. The parameters included the average contrast signal intensity (MeanLin), peak enhancement (PE), rising time (RT), fall time (FT), time to peak (TTP), mean transit time (mTT), perfusion index (PI), Wash-in Area Under the Curve (WiAUC), Wash-in Rate (WiR), Wash-in Perfusion Index (WiPI), Wash-out Area Under the Curve (WoAUC), Wash-out Rate (WoR), and WiAUC + WoAUC (WiWoAUC). The correlations between the preoperative CEUS quantitative parameter ratios, the blood laboratory indexes, postoperative recurrence, and survival were analyzed using log-rank tests and a Cox regression model.

RESULTS

The average follow-up duration period was 79 months (range, 5-145 months). The average recurrence time after ablation was 1-127 months, and the median disease-free survival time was 21 months. The 1-, 3- and 5-year survival rates were 96.9%, 92.3%, and 80.6%, respectively. The log-rank tests showed that tumor size, prothrombin time, and WiAUC, WoAUC, and WiWoAUC ratios were predictors of survival, and aspartate aminotransferase was a predictor of recurrence. The Cox regression analysis showed that tumor size [odds ratio (OR): 6.421; 95% CI: 1.434-28.761] and alanine transaminase (OR: 0.88; 95% CI: 0.010-0.742) were predictors of a poor prognosis.

CONCLUSIONS

CEUS quantitative parameters before thermal ablation and blood laboratory indexes provide potential clinical value for predicting the postoperative recurrence and survival of HCC patients.

Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel on Artificial Intelligence in Interventional Radiology: From Code to Bedside

Artificial intelligence (AI)-based technologies are the most rapidly growing field of innovation in healthcare with the promise to achieve substantial improvements in delivery of patient care across all disciplines of medicine. Recent advances in imaging technology along with marked expansion of readily available advanced health information, data offer a unique opportunity for interventional radiology (IR) to reinvent itself as a data-driven specialty. Additionally, the growth of AI-based applications in diagnostic imaging is expected to have downstream effects on all image-guidance modalities. Therefore, the Society of Interventional Radiology Foundation has called upon 13 key opinion leaders in the field of IR to develop research priorities for clinical applications of AI in IR. The objectives of the assembled research consensus panel were to assess the availability and understand the applicability of AI for IR, estimate current needs and clinical use cases, and assemble a list of research priorities for the development of AI in IR. Individual panel members proposed and all participants voted upon consensus statements to rank them according to their overall impact for IR. The results identified the top priorities for the IR research community and provide organizing principles for innovative academic-industrial research collaborations that will leverage both clinical expertise and cutting-edge technology to benefit patient care in IR.

Artificial intelligence: Emerging player in the diagnosis and treatment of digestive disease

Given the breakthroughs in key technologies, such as image recognition, deep learning and neural networks, artificial intelligence (AI) continues to be increasingly developed, leading to closer and deeper integration with an increasingly data-, knowledge- and brain labor-intensive medical industry. As society continues to advance and individuals become more aware of their health needs, the problems associated with the aging of the population are receiving increasing attention, and there is an urgent demand for improving medical technology, prolonging human life and enhancing health. Digestive system diseases are the most common clinical diseases and are characterized by complex clinical manifestations and a general lack of obvious symptoms in the early stage. Such diseases are very difficult to diagnose and treat. In recent years, the incidence of diseases of the digestive system has increased. As AI applications in the field of health care continue to be developed, AI has begun playing an important role in the diagnosis and treatment of diseases of the digestive system. In this paper, the application of AI in assisted diagnosis and the application and prospects of AI in malignant and benign digestive system diseases are reviewed.

Image-Guided Percutaneous Ablation for Primary and Metastatic Tumors

Image-guided percutaneous ablation methods have been further developed during the recent two decades and have transformed the minimally invasive and precision features of treatment options targeting primary and metastatic tumors. They work by percutaneously introducing applicators to precisely destroy a tumor and offer much lower risks than conventional methods. There are usually shorter recovery periods, less bleeding, and more preservation of organ parenchyma, expanding the treatment options of patients with cancer who may not be eligible for resection. Image-guided ablation techniques are currently utilized for the treatment of primary and metastatic tumors in various organs including the liver, pancreas, kidneys, thyroid and parathyroid, prostate, lung, bone, and soft tissue. This article provides a brief review of the various imaging modalities and available ablation techniques and discusses their applications and associated complications in various organs.

A Hybrid Machine Learning Model Based on Semantic Information Can Optimize Treatment Decision for Naïve Single 3-5-cm HCC Patients

BACKGROUND

Tumor recurrence is an abomination for hepatocellular carcinoma (HCC) patients receiving local treatment.

PURPOSE

The aim of the study was to build a hybrid machine learning model to recommend optimized first treatment (laparoscopic hepatectomy [LH] or microwave ablation [MWA]) for naïve single 3-5-cm HCC patients based on early recurrence (ER, ≤2 years) probability.

METHODS

This retrospective study collected 20 semantic variables of 582 patients (LH: 300, MWA: 282) from 13 hospitals with at least 24 months follow-up. Both groups were divided into training, validation, and test set, respectively. Five algorithms (logistics regression, random forest, neural network, stochastic gradient boosting, and eXtreme Gradient Boosting [XGB]) were used for model building. A model with highest area under the receiver operating characteristic curve (AUC) in a validation set of LH and MWA was selected to connect as a hybrid model which made decision based on ER probability. Model testing was performed in a comprehensive set comprising LH and MWA test sets.

RESULTS

Four variables in each group were selected to build LH and MWA models, respectively. LH-XGB model (AUC = 0.744) and MWA-stochastic gradient method (AUC = 0.750) model were selected for model building. In the comprehensive set, a treatment confusion matrix was established based on recommended and actual treatment. The predicted ER probabilities were comparable with the actual ER rates for various types of patients in matrix (p > 0.05). ER rate of patients whose actual treatment consistent with recommendation was lower than that of inconsistent patients (LH: 21.2% vs. 46.2%, p = 0.042; MWA: 26.3% vs. 54.1%, p = 0.048). By recommending optimal treatment, the hybrid model can significantly reduce ER probability from 38.2% to 25.6% for overall patients (p < 0.001).

CONCLUSIONS

The hybrid model can accurately predict ER probability of different treatments and thereby provide reliable evidence to make optimal treatment decision for patients with single 3-5-cm HCC.

Efficacy and Safety of Fusion Imaging in Radiofrequency Ablation of Hepatocellular Carcinoma Compared to Ultrasound: A Meta-Analysis

Background: Radiofrequency ablation (RFA), generally performed under real-time guidance of ultrasound which is safe and effective, is a common minimally invasive therapy for treating hepatocellular carcinoma. Fusion imaging (FI) is a newly developed imaging method, which integrates CT/MRI accurate imaging and matches the characteristics of real-time ultrasound imaging, thereby providing a new approach to guide tumor ablation therapy. However, the efficacy and safety of FI as opposed to ultrasound in tumor ablation remains unclear.

Objective: The present study sought to evaluate the difference in the efficacy and safety between FI and ultrasound in radiofrequency surgery for the treatment of hepatocellular carcinoma through a metaanalysis.

Materials and Methods: Searching for studies comparing the efficacy and safety of FI and ultrasound in radiofrequency of hepatocellular carcinoma in PubMed, Embase, and Cochrane Library databases for articles published until April 2021. Random or fixed effect models were used for statistical analysis. Metaanalysis and sensitivity analysis were used on the included studies.

Results: A total of six studies met predefined inclusion criteria, and were finally included in the analysis. Sensitivity and subgroup analyses, based on predetermined patient characteristics, allowed minimization of bias. In the RFA of hepatocellular carcinoma, FI decreased 1-year overall survival (OS) when compared with ultrasound. But FI was not significantly different from ultrasound in terms of technical efficiency, 1-, 2-, and 3-year local tumor progression (LTP), complications, as well as 2-year OS. Subgroup analysis, based on tumor mean diameter, showed that FI reduced the rate of 1- and 2-year LTP in patients with tumors of mean diameter ≥15 mm when compared with ultrasound. Moreover, operative complications could be reduced in patients with tumor mean diameter <15 mm using FI, compared with ultrasound.

Conclusion: Overall, these results showed that FI may have some effects on improving efficacy and safety of thermal ablation in HCC patients, relative to ultrasound. However, it may be a more effective method for managing large lesions, as well as those that are difficult to ablate. Further large-scale and well-designed randomized controlled trials are needed to validate these findings.

Application of artificial intelligence in liver diseases: From diagnosis to treatment

Infectious or noninfectious liver disease has inexorably risen as one of the leading causes of global death and disease burden. There were an estimated 2.14 million liver-related deaths in 2017, representing an 11.4% increase since 2012. Traditional diagnosis and treatment methods have various dilemmas in different causes of liver disease. As a hot research topic in recent years, the application of artificial intelligence (AI) in different fields has attracted extensive attention, and new technologies have brought more ideas for the diagnosis and treatment of some liver diseases. Machine learning (ML) is the core of AI and the basic way to make a computer intelligent. ML technology has many potential uses in hepatology, ranging from exploring new noninvasive means to predict or diagnose different liver diseases to automated image analysis. The application of ML in liver diseases can help clinical staff to diagnose and treat different liver diseases quickly, accurately and scientifically, which is of importance for reducing the incidence and mortality of liver diseases, reducing medical errors, and promoting the development of medicine. This paper reviews the application and prospects of AI in liver diseases, and aims to improve clinicians’ awareness of the importance of AI in the diagnosis and treatment of liver diseases.

CEUS-Based Radiomics Can Show Changes in Protein Levels in Liver Metastases After Incomplete Thermal Ablation

Objective

To investigate the ability of contrast-enhanced ultrasound (CEUS)-based radiomics combined with machine learning to detect early protein changes after incomplete thermal ablation.

Methods

HCT-26 colorectal adenoma cells were engrafted into the livers of 80 mice, which were randomly divided into 4 groups for palliative laser ablation. Changes in heat shock protein (HSP) and apoptosis-related protein expression in the tumors were assessed. SCID mice subjected to CEUS and ultrasonography were divided into training (n=56) and test (n=24) datasets. Then, 102 features from seven feature groups were extracted. We use the least absolute shrinkage and selection operator (LASSO) feature selection method to fit the machine learning classifiers. The feature selection methods and four classifiers were combined to determine the best prediction model.

Results

The areas under the receiver-operating characteristic curves (AUCs) of the classifiers in the test dataset ranged from 0.450 to 0.932 (median: 0.721). The best score was obtained from the model in which the omics data of CEUS was analyzed in the arterial phase by random forest (RF) classification.

Conclusions

A machine learning model, in which radiomics characteristics are extracted by multimodal ultrasonography, can accurately, rapidly and noninvasively identify protein changes after ablation.

Role of Machine Learning and Artificial Intelligence in Interventional Oncology

PURPOSE OF REVIEW

The purpose of this review is to highlight the current role of machine learning and artificial intelligence and in the field of interventional oncology.

RECENT FINDINGS

With advancements in technology, there is a significant amount of research regarding the application of artificial intelligence and machine learning in medicine. Interventional oncology is a field that can benefit greatly from this research through enhanced image analysis and intraprocedural guidance. These software developments can increase detection of cancers through routine screening and improve diagnostic accuracy in classifying tumors. They may also aid in selecting the most effective treatment for the patient by predicting outcomes based on a combination of both clinical and radiologic factors. Furthermore, machine learning and artificial intelligence can advance intraprocedural guidance for the interventional oncologist through more accurate needle tracking and image fusion technology. This minimizes damage to nearby healthy tissue and maximizes treatment of the tumor. While there are several exciting developments, this review also discusses limitations before incorporating machine learning and artificial intelligence in the field of interventional oncology. These include data capture and processing, lack of transparency among developers, validating models, integrating workflow, and ethical challenged. In summary, machine learning and artificial intelligence have the potential to positively impact interventional oncologists and how they provide cancer care treatments.

Role of Fusion Imaging in Image-Guided Thermal Ablations

Thermal ablation (TA) procedures are effective treatments for several kinds of cancers. In the recent years, several medical imaging advancements have improved the use of image-guided TA. Imaging technique plays a pivotal role in improving the ablation success, maximizing pre-procedure planning efficacy, intraprocedural targeting, post-procedure monitoring and assessing the achieved result. Fusion imaging (FI) techniques allow for information integration of different imaging modalities, improving all the ablation procedure steps. FI concedes exploitation of all imaging modalities’ strengths concurrently, eliminating or minimizing every single modality’s weaknesses. Our work aims to give an overview of FI, explain and analyze FI technical aspects and its clinical applications in ablation therapy and interventional oncology.

Diagnosis of Chronic Kidney Disease by Three-Dimensional Contrast-Enhanced Ultrasound Combined with Augmented Reality Medical Technology

Chronic kidney disease is a worldwide clinical and public health problem. As a risk factor for cardiovascular and cerebrovascular diseases, the disease has gradually become one of the causes of morbidity and death. As a routine method of screening for kidney disease, ultrasound is very important in improving the rate of early detection and accuracy of chronic kidney disease. This article explores the value of applying 3D ultrasound in conjunction with augmented reality medical technology in chronic kidney disease, observing changes in kidney tumor at different stages with percutaneous 3D ultrasound in patients with chronic kidney disease. Volunteers with chronic kidney disease were selected for this experiment. Among them, 160 males and 140 females were diagnosed as chronic kidney disease by clinical or renal pathological biopsy, and they all met the K/DOQI diagnostic criteria for chronic kidney disease. The selected subjects met the criteria and were divided into 5 groups, each with 60 patients, to explore the correlation of properties such as three-dimensional ultrasound kidney volume in different stages of chronic kidney disease. Experiments have shown that, with the increase in the stages of chronic kidney disease, the elasticity and volume of the renal parenchyma decrease, and the resistance index of the renal artery becomes larger, P < 0.05; the difference is statistically significant, indicating that the elasticity of the renal parenchyma is associated with chronic kidney disease. The stage is negatively correlated, and the resistance index of the renal artery is positively correlated with the stage of chronic kidney disease. That is, as the stage of chronic kidney disease increases, the three-dimensional volume of the kidney shows a decreasing trend and the resistance index of the renal artery shows an increasing trend. Speed shows a declining trend and there is some correlation between the three.

The Learning Curve for Thermal Ablation of Liver Cancers: 4,363-Session Experience for a Single Central in 18 Years

This study aimed to explore the special efforts required to achieve proficiency in performing thermal ablation of liver cancers, including tumors in difficult locations, and clarify the effects of handing-down teaching on the corresponding process. Major complications of patients receiving percutaneous thermal ablation of liver cancer were analyzed. Polynomial fitting was used to describe the connection between major complication rates and special experience. Learning curve of major complications was plotted both for the whole group and for each operator, respectively. Tumors in difficult locations were further studied. A total of 4,363 thermal ablation sessions were included in this study. 143 of 4,363 patients had major complications, corresponding to an incidence rate of 3.27%. 806 thermal ablation sessions were performed for tumors in difficult locations. The major complication rate of these sessions is 6.33%. According to the trend of the learning curve of the 4363 patients, the experience of the whole group can be classified into five stages, that is, the high-risk, relatively stable, unstable, proficient and stable periods. A learning curve for an individual operator can be classified into the high-risk, proficient and stable periods. The major complication rates for the chronologically first, second and third operator of the group are 3.23, 3.35, and 3.31%, respectively. The special experience needed to bypass the first stage corresponds to 410, 510, and 440 sessions, the second stage, 1850, 850, and 870 sessions, by the three operators, respectively. The major complication rates for the tumors in difficult locations for the first, second and third operator were 7.04, 5.53, and 5.98%, respectively. For the tumors in difficult locations, the special experience needed to bypass the first stage corresponds to 150, 130, and 140 sessions, the second stage, 290, 175, and 185 sessions, by the three operators, respectively. In conclusion, the learning process of an operator percutaneous thermal ablation for liver cancer can be classified into three stages. The major complication rate for tumors in difficult locations were higher than that for all tumors. Handing-down teaching can make an operator arrive at the third stage earlier but not the second stage.

Neutrophil to lymphocyte ratio and albumin bilirubin grade in hepatocellular carcinoma: A systematic review

BACKGROUND

Hepatocellular carcinoma (HCC) is a frequent cause of cancer related death globally. Neutrophil to lymphocyte ratio (NLR) and albumin bilirubin (ALBI) grade are emerging prognostic indicators in HCC.

AIM

To study published literature of NLR and ALBI over the last five years, and to validate NLR and ALBI locally in our centre as indicators of HCC survival.

METHODS

A systematic review of the published literature on PubMed of NLR and ALBI in HCC over the last five years. The search followed the guidelines of the preferred reporting items for systematic reviews and meta-analyses. Additionally, we also investigated HCC cases between December 2013 and December 2018 in our centre.

RESULTS

There were 54 studies describing the relation between HCC and NLR and 95 studies describing the relation between HCC and ALBI grade over the last five years. Our local cohort of patients showed NLR to have a significant negative relationship to survival (P = 0.011). There was also significant inverse relationship between the size of the largest HCC nodule and survival (P = 0.009). Median survival with alpha fetoprotein (AFP) < 10 KU/L was 20 mo and with AFP > 10 KU/L was 5 mo. We found that AFP was inversely related to survival, this relationship was not statically significant (P = 0.132). Mean survival for ALBI grade 1 was 37.7 mo, ALBI grade 2 was 13.4 months and ALBI grade 3 was 4.5 mo. ALBI grades performed better than Child Turcotte Pugh score in detecting death from HCC.

CONCLUSION

NLR and ALBI grade in HCC predict survival better than the conventional alpha fetoprotein. ALBI grade performs better than Child Turcotte Pugh score. These markers are done as part of routine clinical care and in cases of normal alpha fetoprotein, these markers could give a better understanding of the patient disease progression. NLR and ALBI grade could have a role in modified easier to learn staging and prognostic systems for HCC.

Value of artificial ascites to assist thermal ablation of liver cancer adjacent to the gastrointestinal tract in patients with previous abdominal surgery

Background

To evaluate the feasibility and effectiveness of artificial ascites to assist thermal ablation of liver cancer adjacent to the gastrointestinal tract in patients with previous abdominal surgery.

Methods

Thirty-nine patients with a total of 40 liver malignant tumors were enrolled between January 2016 and June 2019. All had histories of hepatectomy, splenectomy, cholecystectomy, and intestinal surgery. The distance between the tumor and the gastrointestinal tract was < 5 mm. Normal saline was used as artificial ascites to protect the gastrointestinal tract during thermal ablation. The success rate of the procedure, incidence of major complications, and the technical efficacy of ablation were recorded. Patients were followed for local tumor progression (LTP), and overall survival (OS).

Results

The use of artificial ascites was successful in 38 of the 40 procedures (95%). Major complications occurred in two of the 39 patients (5.1%) following the procedure. One was an intestinal fistula that occurred in a failed case and was associated with an infection. The other was a liver abscess that occurred in a successful case. The technical efficacy of ablation was 100% (40/40 procedures). The median follow-up was 16 months. The 1-, 2-, and 3-year LTP rates were 2.9, 5.7 and 5.7%. The 1-, 2-, and 3-year OS rates were 97.1, 86.8 and 69.5%.

Conclusion

In patients with previous abdominal surgery, artificial ascites is feasible and effective for assisting thermal ablation of liver cancer adjacent to the gastrointestinal tract.