Correction to: Multi-View Feature Transformation Based SVM+ for Computer-Aided Diagnosis of Liver Cancers With Ultrasound Image.

Presents corrections to the paper, Multi-View Feature Transformation Based SVM+ for Computer-Aided Diagnosis of Liver Cancers With Ultrasound Image.

ACG Clinical Guideline: Focal Liver Lesions.

Focal liver lesions (FLLs) have become an increasingly common finding on abdominal imaging, especially asymptomatic and incidental liver lesions. Gastroenterologists and hepatologists often see these patients in consultation and make recommendations for management of multiple types of liver lesions, including hepatocellular adenoma, focal nodular hyperplasia, hemangioma, and hepatic cystic lesions including polycystic liver disease. Malignancy is important to consider in the differential diagnosis of FLLs, and healthcare providers must be familiar with the diagnosis and management of FLLs. This American College of Gastroenterology practice guideline uses the best evidence available to make diagnosis and management recommendations for the most common FLLs.

[MRI manifestations of 40 cases with the hepatic epithelioid hemangioendothelioma classification based on the morphology and size].

Objective: To explore the MRI characteristics of the hepatic epithelioid hemangioendothelioma (HEHE) classification according to morphology and size. Methods: The clinical, pathological, and MRI imaging data of 40 cases with HEHE confirmed pathologically from December 2009 to September 2021 were retrospectively analyzed. A paired sample t-test was used for comparison between the two groups. Results: There were 40 cases (5 solitary, 24 multifocal, 9 local fusion, and 2 diffuse fusion) and 214 lesions (163 nodules, 31 masses, and 20 fusion foci). The most common features of lesions were subcapsular growth and capsular depression. The signal intensity of lesions ≤1cm was usually uniform with whole or ring enhancement. Nodules and mass-like lesions ≥1cm on a T1-weighted image had slightly reduced signal intensity or manifested as a halo sign. Target signs on a T2-weighted image were characterized by: target or centripetal enhancement; fusion-type lesions; irregular growth and hepatic capsular retraction, with ring or target-like enhancement in the early stage of fusion and patchy irregular enhancement in the late stage; blood vessels traversing or accompanied by malformed blood vessels; focal bleeding; an increasing proportion of extrahepatic metastases and abnormal liver function with the type of classified manifestation; primarily portal vein branches traversing; and reduced overall intralesional bleeding rate (17%). Lollipop signs were presented in 19 cases, with a high expression rate in mass-type lesions (42%). The fusion lesions were expressed, but the morphological manifestation was atypical. The diffusion-weighted imaging mostly showed high signal or target-like high signal. An average apparent diffusion coefficient of lesions was (1.56±0.36) ×10(-3)mm(2)/s, which was statistically significantly different compared with that of adjacent normal liver parenchyma (t=8.28, P<0.001). Conclusion: The MRI manifestations for the HEHE classification are closely related to the morphology and size of the lesions and have certain differences and characteristics that are helpful for the diagnosis of the disease when combined with clinical and laboratory examinations.

Myxoinflammatory fibroblastic sarcoma of the liver: Case report and literature review.

RATIONALE: Myxoinflammatory fibroblastic sarcoma (MIFS) is a rare low-grade malignant soft tissue sarcoma that primarily affects the distal extremities in adults, with the highest incidence in patients in their 40s and 50s. It has a high local recurrence rate and a low metastasis rate. Although MIFSs have been documented in other sites, an MIFS in the liver is highly unusual. Herein, we present a case of a patient with hepatic MIFS. PATIENT CONCERNS: The patient was a 58-year-old Chinese man with abdominal pain as the primary symptom. Abdominal computed tomography and magnetic resonance imaging revealed a mass in the right posterior lobe of the liver. The patient underwent surgical excision, and the excised specimen was identified as MIFS. Three years later, the patient returned to our hospital for abdominal pain. Computed tomography and magnetic resonance imaging revealed a mass in liver segments 2/3/4. DIAGNOSIS: Postoperative pathological examination of the tumor revealed the recurrence of MIFS. INTERVENTIONS: The patient underwent surgical resection of the MIFS. OUTCOMES: The patient received multiple pirarubicin-based chemotherapy treatments and an ALK inhibitor (anlotinib) within 6 months after surgery, but the tumor recurred. LESSONS: MIFS can not only occur in the proximal limbs, trunk, head, and neck but can also affect the abdominal organs. Surgical resection remains the primary treatment option for MIFS in the absence of any contraindications. Because the recurrence rate of MIFS is high, meticulous long-term monitoring is required.

Prediction power of radiomics in early recurrence of hepatocellular carcinoma: A systematic review and meta-analysis.

BACKGROUND: Raiomics is an emerging auxiliary diagnostic tool, but there are still differences in whether it can be applied to predict early recurrence of hepatocellular carcinoma (HCC). The purpose of this meta-analysis was to systematically evaluate the predictive power of radiomics in the early recurrence (ER) of HCC. METHODS: Comprehensive studies on the application of radiomics to predict ER in HCC patients after hepatectomy or curative ablation were systematically screened in Embase, PubMed, and Web of Science. RESULTS: Ten studies which is involving a total of 1929 patients were reviewed. The overall estimates of radiomic models for sensitivity and specificity in predicting the ER of HCC were 0.79 (95% confidence interval [CI]: 0.68-0.87) and 0.83 (95% CI: 0.73-0.90), respectively. The area under the summary receiver operating characteristic curve (SROC) was 0.88 (95% CI: 0.85-0.91). CONCLUSIONS: The imaging method is a reliable method for diagnosing HCC. Radiomics, which is based on medical imaging, has excellent power in predicting the ER of HCC. With the help of radiomics, we can predict the recurrence of HCC after surgery more effectively and provide a useful reference for clinical practice.

Diagnostic Performances of PET/CT Using Fibroblast Activation Protein Inhibitors in Patients with Primary and Metastatic Liver Tumors: A Comprehensive Literature Review.

PET/CT using radiolabeled fibroblast activation protein inhibitors (FAPIs) is a promising diagnostic tool in oncology, especially when non-increased and/or physiologically high [18F]FDG uptake (as in liver parenchyma) is observed. We aimed to review the role of PET/CT using radiolabeled FAPIs in primary and/or metastatic liver lesions, and to compare their performances with more "conventional" radiopharmaceuticals. A search algorithm based on the terms "FAPI" AND ("hepatic" OR "liver") was applied, with the last update on 1st January 2024. Out of 177 articles retrieved, 76 studies reporting on the diagnostic application of radiolabeled FAPI PET/CT in at least one patient harboring primary or metastatic liver lesion(s) were fully analyzed. Although there was some heterogeneity in clinical conditions and/or study methodology, PET/CT with radiolabeled FAPIs showed an excellent performance in common primary liver malignancies (hepatocarcinoma, intrahepatic cholangiocarcinoma) and liver metastases (mostly from the gastrointestinal tract and lungs). A higher tumor-to-background ratio for FAPIs than for [18F]FDG was found in primary and metastatic liver lesions, due to lower background activity. Despite limited clinical evidence, radiolabeled FAPIs may be used to assess the suitability and effectiveness of FAPI-derived therapeutic agents such as [177Lu]Lu-FAPI. However, future prospective research on a wider population is needed to confirm the excellent performance.

Solitary liver metastasis from adenoid cystic carcinoma of the submandibular gland.

Adenoid cystic carcinoma (ACC) is a rare tumour of the salivary glands characterised by distant metastases, mainly to lungs and bone. Isolated metastasis to the liver is unusual. We present the case of a woman with an ACC of the submandibular gland (pT1N0) who underwent radical submandibular gland excision and selective neck dissection. Preoperative imaging identified a liver lesion with features suggestive of a haemangioma. Two-year postoperatively, a surveillance CT neck/trunk showed an increase in size of the left liver lobe lesion. Subsequent MR liver and US-guided biopsy confirmed the lesion to be metastatic ACC. The patient underwent a successful left lateral liver sectionectomy. She remains disease-free 2.5 years after her liver resection. A literature search revealed only four other similar cases. This report highlights that even early-stage ACCs of the salivary gland may present with synchronous solitary liver metastasis which can be effectively treated with curative surgery.

Pretreatment CT-based machine learning radiomics model predicts response in unresectable hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors and interventional therapy.

BACKGROUND: Lenvatinib plus PD-1 inhibitors and interventional (LPI) therapy have demonstrated promising treatment effects in unresectable hepatocellular carcinoma (HCC). However, biomarkers for predicting the response to LPI therapy remain to be further explored. We aimed to develop a radiomics model to noninvasively predict the efficacy of LPI therapy. METHODS: Clinical data of patients with HCC receiving LPI therapy were collected in our institution. The clinical model was built with clinical information. Nine machine learning classifiers were tested and the multilayer perceptron classifier with optimal performance was used as the radiomics model. The clinical-radiomics model was constructed by integrating clinical and radiomics scores through logistic regression analysis. RESULTS: 151 patients were enrolled in this study (2:1 randomization, 101 and 50 in the training and validation cohorts), of which three achieved complete response, 69 showed partial response, 46 showed stable disease, and 33 showed progressive disease. The objective response rate, disease control rate, and conversion resection rates were 47.7, 78.1 and 23.2%. 14 features were selected from the initially extracted 1223 for radiomics model construction. The area under the curves of the radiomics model (0.900 for training and 0.893 for validation) were comparable to that of the clinical-radiomics model (0.912 for training and 0.892 for validation), and both were superior to the clinical model (0.669 for training and 0.585 for validation). Meanwhile, the radiomics model can categorize participants into high-risk and low-risk groups for progression-free survival (PFS) and overall survival (OS) in the training (HR 1.913, 95% CI 1.121 to 3.265, p=0.016 for PFS; HR 4.252, 95% CI 2.051 to 8.816, p=0.001 for OS) and validation sets (HR 2.347, 95% CI 1.095 to 5.031, p=0.012 for PFS; HR 2.592, 95% CI 1.050 to 6.394, p=0.019 for OS). CONCLUSION: The promising machine learning radiomics model was developed and validated to predict the efficacy of LPI therapy for patients with HCC and perform risk stratification, with comparable performance to clinical-radiomics model.

Predicting hepatocellular carcinoma: A new non-invasive model based on shear wave elastography.

BACKGROUND: Integrating conventional ultrasound features with 2D shear wave elastography (2D-SWE) can potentially enhance preoperative hepatocellular carcinoma (HCC) predictions. AIM: To develop a 2D-SWE-based predictive model for preoperative identification of HCC. METHODS: A retrospective analysis of 884 patients who underwent liver resection and pathology evaluation from February 2021 to August 2023 was conducted at the Oriental Hepatobiliary Surgery Hospital. The patients were divided into the modeling group (n = 720) and the control group (n = 164). The study included conventional ultrasound, 2D-SWE, and preoperative laboratory tests. Multiple logistic regression was used to identify independent predictive factors for malignant liver lesions, which were then depicted as nomograms. RESULTS: In the modeling group analysis, maximal elasticity (Emax) of tumors and their peripheries, platelet count, cirrhosis, and blood flow were independent risk indicators for malignancies. These factors yielded an area under the curve of 0.77 (95% confidence interval: 0.73-0.81) with 84% sensitivity and 61% specificity. The model demonstrated good calibration in both the construction and validation cohorts, as shown by the calibration graph and Hosmer-Lemeshow test (P = 0.683 and P = 0.658, respectively). Additionally, the mean elasticity (Emean) of the tumor periphery was identified as a risk factor for microvascular invasion (MVI) in malignant liver tumors (P = 0.003). Patients receiving antiviral treatment differed significantly in platelet count (P = 0.002), Emax of tumors (P = 0.033), Emean of tumors (P = 0.042), Emax at tumor periphery (P < 0.001), and Emean at tumor periphery (P = 0.003). CONCLUSION: 2D-SWE's hardness value serves as a valuable marker for enhancing the preoperative diagnosis of malignant liver lesions, correlating significantly with MVI and antiviral treatment efficacy.

Evaluation of a prototype metal artifact reduction algorithm for cone beam CT in patients undergoing radioembolization.

Metal artifacts notoriously pose significant challenge in computed tomography (CT), leading to inaccuracies in image formation and interpretation. Artifact reduction tools have been designed to improve cone beam computed tomography (CBCT) image quality by reducing artifacts caused by certain high-density materials. Metal artifact reduction (MAR) tools are specific algorithms that are applied during image reconstruction to minimize or eliminate artifacts degrading CBCT images. The purpose of the study is to evaluate the effect of a MAR algorithm on image quality in CBCT performed for evaluating patients before transarterial radioembolization (TARE). We retrospectively included 40 consecutive patients (aged 65 ± 13 years; 23 males) who underwent 45 CBCT examinations (Allura FD 20, XperCT Roll protocol, Philips Healthcare, Best, The Netherlands) in the setting of evaluation for TARE between January 2017 and December 2018. Artifacts caused by coils, catheters, and surgical clips were scored subjectively by four readers on a 5-point scale (1 = artifacts affecting diagnostic information to 5 = no artifacts) using a side-by-side display of uncorrected and MAR-corrected images. In addition, readers scored tumor visibility and vessel discrimination. MAR-corrected images were assigned higher scores, indicating better image quality. The differences between the measurements with and without MAR were most impressive for coils with a mean improvement of 1.6 points (95%CI [1.5 1.8]) on the 5-point likert scale, followed by catheters 1.4 points (95%CI [1.3 1.5]) and clips 0.7 points (95%CI [0.3 1.1]). Improvements for other artifact sources were consistent but relatively small (below 0.25 points on average). Interrater agreement was good to perfect (Kendall's W coefficient = 0.68-0.95) and was higher for MAR-corrected images, indicating that MAR improves diagnostic accuracy. A metal artifact reduction algorithm can improve diagnostic and interventional accuracy of cone beam CT in patients undergoing radioembolization by reducing artifacts caused by diagnostic catheters and coils, lowering interference of metal artifacts with adjacent major structures, and improving tumor visibility.

in vivo and in situ robust quantitative optical biopsy of hepatocellular carcinoma and metastasis based on two-photon autofluorescence imaging.

Two-photon autofluorescence (TPAF) imaging is able to offer precise cellular metabolic information with high spatiotemporal resolution, making it a promising biopsy tool. The technique is greatly hampered by the complexity of either the optical system or data processing. Here, the excitation wavelength was optimized to simultaneously excite both flavin adenine dinucleotide and nicotinamide adenine dinucleotide and eliminate the unexpected TPAF. The optical redox ratio (ORR) images were robustly achieved without additional calibration under the optimized single-wavelength excitation. The in vitro, ex vivo, and in vivo biopsy by the TPAF method were systematically studied and compared using hepato-cellular carcinoma and metastasis as examples. It was demonstrated that the proposed TPAF method simplified the optical system, improved the robustness of ORR, and enabled early-stage cancer diagnosis, showing distinguished advantages as compared with previous methods.

68Ga-NODAGA-Exendin-4 PET/CT Findings in a Case of Metastatic Insulinoma With Refractory Hypoglycemia Controlled by 90Y Transarterial Radioembolization.

ABSTRACT: Metastatic insulinomas can cause recurrent hypoglycemia requiring continuous IV glucose infusion. Various medical and chemotherapeutic treatment options are used to reduce the patient's risk of death due to hypoglycemia. Treatment-resistant hepatic metastatic insulinomas may benefit clinically from 90Y transarterial radioembolization therapy. In this case, we present a case of liver metastatic insulinoma that achieved clinical improvement after 2 cycles of 90Y microspheres transarterial radioembolization, and the presence of active metastases was demonstrated with 68Ga-NODAGA-exendin-4 PET/CT imaging.

Ultrasound-Responsive Nanodelivery System of GPC3-Targeting and Sonosensitizer for Visualized Hepatocellular Carcinoma Therapy.

Purpose: The incidence of hepatocellular carcinoma (HCC) is continuously increasing, and the mortality rate remains high. Thus, more effective strategies are needed to improve the treatment of HCC. Methods: In this study, we report the use of a visualized glypican-3 (GPC3)-targeting nanodelivery system (named GC-NBs) in combination with sonodynamic therapy (SDT) to enhance the therapeutic efficacy for treating HCC. The obtained nanodelivery system could actively target hepatocellular carcinoma cells and achieve ultrasound imaging through phase changes into nanobubbles under low-intensity ultrasound irradiation. Meanwhile, the released chlorine e6 (Ce6) after the nanobubbles collapse could lead to the generation of reactive oxygen species (ROS) under ultrasound irradiation to induce SDT. Results: Both in vitro and in vivo experiments have shown that GC-NBs can accumulate in tumour areas and achieve sonodynamic antitumour therapy under the navigation action of glypican-3-antibody (GPC3-Ab). Furthermore, in vitro and in vivo experiments did not show significant biological toxicity of the nanodelivery system. Moreover, GC-NBs can be imaged with ultrasound, providing personalized treatment monitoring. Conclusion: GC-NBs enable a visualized antitumour strategy from a targeted sonodynamic perspective by combining tumour-specific targeting and stimuli-responsive controlled release into a single system.

Beyond pixels: Graph filtration learning unveils new dimensions in hepatocellular carcinoma imaging.

This editorial explores the emerging role of Graph Filtration Learning (GFL) in revolutionizing Hepatocellular carcinoma (HCC) imaging analysis. As traditional pixel-based methods reach their limits, GFL offers a novel approach to capture complex topological features in medical images. By representing imaging data as graphs and leveraging persistent homology, GFL unveils new dimensions of information that were previously inaccessible. This paradigm shift holds promise for enhancing HCC diagnosis, treatment planning, and prognostication. We discuss the principles of GFL, its potential applications in HCC imaging, and the challenges in translating this innovative technique into clinical practice.

Multi-phase features interaction transformer network for liver tumor segmentation and microvascular invasion assessment in contrast-enhanced CT.

Precise segmentation of liver tumors from computed tomography (CT) scans is a prerequisite step in various clinical applications. Multi-phase CT imaging enhances tumor characterization, thereby assisting radiologists in accurate identification. However, existing automatic liver tumor segmentation models did not fully exploit multi-phase information and lacked the capability to capture global information. In this study, we developed a pioneering multi-phase feature interaction Transformer network (MI-TransSeg) for accurate liver tumor segmentation and a subsequent microvascular invasion (MVI) assessment in contrast-enhanced CT images. In the proposed network, an efficient multi-phase features interaction module was introduced to enable bi-directional feature interaction among multiple phases, thus maximally exploiting the available multi-phase information. To enhance the model's capability to extract global information, a hierarchical transformer-based encoder and decoder architecture was designed. Importantly, we devised a multi-resolution scales feature aggregation strategy (MSFA) to optimize the parameters and performance of the proposed model. Subsequent to segmentation, the liver tumor masks generated by MI-TransSeg were applied to extract radiomic features for the clinical applications of the MVI assessment. With Institutional Review Board (IRB) approval, a clinical multi-phase contrast-enhanced CT abdominal dataset was collected that included 164 patients with liver tumors. The experimental results demonstrated that the proposed MI-TransSeg was superior to various state-of-the-art methods. Additionally, we found that the tumor mask predicted by our method showed promising potential in the assessment of microvascular invasion. In conclusion, MI-TransSeg presents an innovative paradigm for the segmentation of complex liver tumors, thus underscoring the significance of multi-phase CT data exploitation. The proposed MI-TransSeg network has the potential to assist radiologists in diagnosing liver tumors and assessing microvascular invasion.

Comparison of CT and MRI in the Diagnosis of Liver Tumors: A Retrospective Case-Control Analysis.

OBJECTIVE: To compare the diagnostic value of multi-slice computed tomography (CT) and magnetic resonance imaging (MRI) in liver tumors. METHODS: Retrospective selection of CT and MRI imaging data from 109 cases of liver tumors treated in our hospital from January 2020 to March 2023. The selection was determined through pathological examination. RESULTS: According to the pathological examination results, 61 cases were benign tumors, and 48 cases were malignant tumors. The hepatic portal flow (HPF), hepatic artery perfusion index (HPI) and hepatic artery perfusion (HAF) of malignant tumors were significantly lower than in benign tumors (P<0.05). The signal enhancement ratio of malignant tumors was significantly higher than in benign tumors, and the peak time was significantly lower than in benign tumors (P<0.05). The sensitivity (97.92%) and accuracy (97.25%) of the combined examination were significantly higher than those of MRI (83.33%, 90.83%) or CT alone (81.25%, 88.99%) (P<0.05). CONCLUSION: CT and MRI have high application value in the diagnosis and evaluation of liver tumors, and the combination of these two methods can further improve diagnostic sensitivity and accuracy, providing an objective reference for early diagnosis and treatment of liver cancer.

Prognostic value of the tumor-to-liver density ratio in patients with metastatic colorectal cancer treated with bevacizumab-based chemotherapy. A post-hoc study of the STIC-AVASTIN trial.

BACKGROUND: The Response Evaluation Criteria in Solid Tumors (RECIST) are often inadequate for the early assessment of the response to cancer therapy, particularly bevacizumab-based chemotherapy. In a first cohort of patients with colorectal cancer liver metastases (CRLM), we showed that variations of the tumor-to-liver density (TTLD) ratio and modified size-based criteria determined using computed tomography (CT) data at the first restaging were better prognostic criteria than the RECIST. The aims of this study were to confirm the relevance of these radiological biomarkers as early predictors of the long-term clinical outcome and to assess their correlation with contrast-enhanced ultrasound (CEUS) parameters in a new patient cohort. METHODS: In this post-hoc study of the multicenter STIC-AVASTIN trial, we retrospectively reviewed CT data of patients with CRLM treated with bevacizumab-based regimens. We determined the size, density and TTLD ratio of target liver lesions at baseline and at the first restaging and also performed a morphologic evaluation according to the MD Anderson criteria. We assessed the correlation of these parameters with progression-free survival (PFS) and overall survival (OS) using the log-rank test and a Cox proportional hazard model. We also examined the association between TTLD ratio and quantitative CEUS parameters. RESULTS: This analysis concerned 79 of the 137 patients included in the STIC-AVASTIN trial. PFS and OS were significantly longer in patients with tumor size reduction > 15% at first restaging, but were not correlated with TTLD ratio variations. However, PFS was longer in patients with TTLD ratio > 0.6 at baseline and first restaging than in those who did not reach this threshold. In the multivariate analysis, only baseline TTLD ratio > 0.6 was a significant survival predictor. TTLD ratio > 0.6 was associated with improved perfusion parameters. CONCLUSIONS: Although TTLD ratio variations did not correlate with the long-term clinical outcomes, TTLD absolute values remained a good predictor of survival at baseline and first restaging, and may reflect tumor microvascular features that might influence bevacizumab-based treatment efficiency. TRIAL REGISTRATION: NCT00489697, registration number of the STIC-AVASTIN trial.

Design of Path-Planning System for Interventional Thermal Ablation of Liver Tumors Based on CT Images.

OBJECTIVE: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors' puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. METHODS: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. RESULTS: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors' planning efficiency. CONCLUSION: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value.

Adjusted Tumor Enhancement on Dual-Phase Cone-Beam CT: Predictor of Response and Overall Survival in Patients with Liver Malignancies Treated with Hepatic Artery Embolization.

The aim of this study was to examine the value of tumor enhancement parameters on dual-phase cone-beam CT (CBCT) in predicting initial response, local progression-free survival (L-PFS) and overall survival (OS) following hepatic artery embolization (HAE). Between Feb 2016 and Feb 2023, 13 patients with 29 hepatic tumors treated with HAE were analyzed. Pre- and post-embolization, subtracted CBCTs were performed, and tumor enhancement parameters were measured, resulting in three parameters: pre-embolization Adjusted Tumor Enhancement (pre-ATE), post-embolization ATE and the difference between pre- and post-ATE (∆ATE). Treatment response was evaluated using the mRECIST criteria at 1 month. Tumors were grouped into complete response (CR) and non-complete response (non-CR) groups. To account for the effect of multiple lesions per patient, a cluster data analytic method was employed. The Kaplan-Meier method was utilized for survival analysis using the lesion with the lowest ∆ATE value in each patient. Seventeen (59%) tumors showed CR and twelve (41%) showed non-CR. Pre-ATE was 38.5 ± 10.6% in the CR group and 30.4 ± 11.0% in the non-CR group (p = 0.023). ∆ATE in the CR group was 39 ± 12 percentage points following embolization, compared with 29 ± 11 in the non-CR group (p = 0.009). Patients with ∆ATE > 33 had a median L-PFS of 13.1 months compared to 5.7 in patients with ∆ATE ≤ 33 (95% CI = 0.038-0.21) (HR, 95% CI = 0.45, 0.20-0.9, p = 0.04). Patients with ∆ATE ≤ 33 had a median OS of 19.7 months (95% CI = 3.77-19.8), while in the ∆ATE > 33 group, median OS was not reached (95% CI = 20.3-NA) (HR, 95% CI = 0.15, 0.018-1.38, p = 0.04). CBCT-derived ATE parameters can predict treatment response, L-PFS and OS following HAE.