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European Radiology Experimental
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A novel method for predicting hepatocellular carcinoma response to chemoembolization using an intraprocedural CT hepatic arteriography-based enhancement mapping: a proof-of-concept analysis

European Radiology Experimental volume 7, Article number: 4 (2023) Cite this article

Abstract

Background

To evaluate the feasibility of a novel approach for predicting hepatocellular carcinoma (HCC) response to drug-eluting beads transarterial chemoembolization (DEB-TACE) using computed tomography hepatic arteriography enhancement mapping (CTHA-EM) method.

Methods

This three-institution retrospective study included 29 patients with 46 HCCs treated with DEB-TACE between 2017 and 2020. Pre- and posttreatment CTHA-EM images were generated using a prototype deformable registration and subtraction software. Relative tumor enhancement (TPost/pre-RE) defined as the ratio of tumor enhancement to normal liver tissue was calculated to categorize tumor response as residual (TPost-RE > 1) versus non-residual (TPost-RE ≤ 1) enhancement, which was blinded compared to the response assessment on first follow-up imaging using modified RECIST criteria. Additionally, for tumors with residual enhancement, CTHA-EM was evaluated to identify its potential feeding arteries.

Results

CTHA-EM showed residual enhancement in 18/46 (39.1%) and non-residual enhancement in 28/46 (60.9%) HCCs, with significant differences on TPost-RE (3.05 ± 2.4 versus 0.48 ± 0.23, respectively; p < 0.001). The first follow-up imaging showed non-complete response (partial response or stable disease) in 19/46 (41.3%) and complete response in 27/46 (58.7%) HCCs. CTHA-EM had a response prediction sensitivity of 94.7% (95% CI, 74.0–99.9) and specificity of 100% (95% CI, 87.2–100). Feeding arteries to the residual enhancement areas were demonstrated in all 18 HCCs (20 arteries where DEB-TACE was delivered, 2 newly developed collaterals following DEB-TACE).

Conclusion

CTHA-EM method was highly accurate in predicting initial HCC response to DEB-TACE and identifying feeding arteries to the areas of residual arterial enhancement.

Keypoints

  • Computed tomography hepatic arteriography enhancement mapping (CTHA-EM) correlated with initial hepatocellular carcinoma response to drug-eluting beads transarterial chemoembolization (DEB-TACE).

  • CTHA-EM provided quantitative evaluation of residual arterial tumor enhancement after DEB-TACE.

  • CTHA-EM identified feeding arteries to areas of residual tumor enhancement.

  • CTHA-EM might be used to guide treatment delivery and determine treatment endpoint.

Background

Transarterial chemoembolization (TACE) is a standard treatment for patients with intermediate-stage hepatocellular carcinoma (HCC) [1, 2]. Its oncological effects are related to tumor arterial devascularization and necrosis, which do not prompt immediate changes in overall tumor size. Consequently, arterial enhancement-based treatment response criteria are considered to be the reference standard for TACE response evaluation [3,4,5] and have demonstrated superiority over size-based criteria for predicting pathological response and survival [4, 6,7,8].

In lipiodol-based TACE, the degree of intratumoral lipiodol accumulation can be utilized as a surrogate for treatment response and can be assessed by intraprocedural computed tomography (CT) or cone-beam CT (CBCT) [9,10,11,12]. In drug-eluting beads TACE (DEB-TACE), tumor response can be estimated to a certain extent by the degree of contrast agent accumulated within the tumor during the delivery of DEB-TACE on native CT or CBCT acquired immediately after treatment [13]. Nevertheless, as opposed to lipiodol, such contrast agent retention occurs only transiently and may not be a reliable surrogate for assessing embolization endpoint and predicting treatment response. Furthermore, in the event of acquiring a contrast-enhanced CT/CBCT arteriography after DEB-TACE, contrast agent retained in the tumor might obscure areas of residual tumor enhancement making it hard to identify true residual tumor enhancement. The use of dual-phase CBCT with perfusion blood volume imaging for response prediction has been reported for patients undergoing DEB-TACE [14,15,16]. However, its use in clinical practice is limited due to the lack of a reliable and reproducible method to assess residual tumor enhancement, often attributed to the complexity of acquiring CBCT images, lack of standardization of gray scale values, and the sensitivity of CBCT acquisition to motion and breathing artifacts. Finally, none of those reported methods identifies the putative artery responsible for residual tumor enhancement, limiting its application for intra-procedure decision-making. Therefore, two-dimensional digital subtraction angiography (DSA) remains to be the primary method of subjectively assessing DEB-TACE treatment endpoint.

Advanced algorithms that apply deep learning methods on DSA image sequence are being developed to predict treatment response [17]. However, DSA imaging due to its inherent projection geometry poses many challenges in identifying residual tumor enhancement depending on the amount and location of the residual tumor, number of hepatic arteries supplying it, subtraction artifacts from respiratory and cardiac motion, and end point assessment has been reported to be highly variable between operators [18,19,20]. Several studies have demonstrated the importance of achieving adequate embolization during TACE and its correlation to improved survival outcomes, with emphasis on achieving complete response at first TACE session [18, 21, 22] and CT-based texture analysis predictive modeling to select optimal patients for TACE intervention upfront [23]. Hence, a robust, accurate, and objective method of predicting early treatment response to TACE remains the most desirable need.

CT hepatic arteriography (CTHA) has proved to be superior to CBCT for TACE planning because of its better contrast resolution, comparable spatial resolution, and minimal artifacts caused by motion and beam hardening [24]. CTHA also permits reliable quantification of parenchymal enhancement in Hounsfield units (HU), potentially allowing an objective and reproducible method for assessing TACE treatment endpoint. Several angiography/CT users have been using repeated CTHA imaging to identify tumor feeding arteries as well as residual tumor areas [25]. However, it is often difficult to delineate contrast stasis and residual tumor.

The aim of this study was to evaluate the feasibility of a novel approach to predict HCC response to DEB-TACE using CTHA enhancement mapping (CTHA-EM) through image subtraction.

Methods

Study population

This three-institution retrospective study was compliant with the Health Insurance Portability and Accountability Act and approved by each institutional review board with a waiver of informed consent. Between November 2017 and November 2020, the prospectively compiled DEB-TACE registries were searched to identify patients who met the following inclusion criteria: (1) treatment-naïve HCC without extrahepatic arterial tumor supply, (2) who were treated with DEB-TACE and had a dual-phase CTHA images (native and contrast-enhanced arterial phases) acquired before and after DEB-TACE delivery (n = 33 patients), (3) who were deemed to have achieved complete response (CR) by intra-procedural DSA and CT (n = 30 patients), and (4) who had at least one follow-up CT or magnetic resonance imaging following DEB-TACE (Fig. 1).

Fig. 1
figure 1

Participant flowchart for inclusion

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DEB-TACE protocol

Six interventional radiologists (B.C.O., A.M., S.T., T.M., H.N., and C.A.L.), with 9, 15, 8, 9, 18, and 11 years of experience, respectively, performed DEB-TACE in an angio/CT suite. After conscious sedation, transarterial access was obtained with femoral artery puncture, and the target tumor(s) and respective feeding hepatic arteries were identified by DSA and CTHA. The feeding arteries were selected on a segmental or subsegmental level with a 1.1–2.4-Fr microcatheter (Progreat, Terumo, Japan; PIXIE, Tokai, Japan, or Parkway, Asahi, Japan). DEB-TACE was performed with 70−150 or 100−300 μm particles (LC Bead M1, Boston Scientific, USA, or DC Beads, Eisai, Japan) loaded with doxorubicin (25 mg/mL, 50 mg total) or epirubicin (50 mg/mL, 75 mg total) and mixed with 12, 15, or 19 mL of nonionic contrast medium and 6, 5, or 10 mL of 0.9% saline, respectively. The solution was injected manually at a rate of approximately 1 mL/min until complete tumor devascularization and near stasis of the feeding artery was documented on DSA images. All DEB-TACE were performed with the goal of achieving CR per modified response evaluation criteria in solid tumors (mRECIST) [4].

Intraprocedural CTHA imaging protocol

A dual-phase CTHA (native CT and intra-arterial CT during hepatic arteriography) was routinely acquired for DEB-TACE planning to evaluate the presence of additional tumors, identify target tumor(s) and their feeding arteries, and rule out the presence of extrahepatic feeding arteries. CTHA was performed using contrast agent (Omnipaque 300, General Electric Healthcare, Chalfont, St. Gille, UK) injected at 2 mL/s (average total volume 22 mL) with an acquisition delay of 4 or 8 s for arterial phase using a 5-Fr catheter placed in the celiac artery, common hepatic artery, or left gastric artery, or a 1.1−2.4-Fr coaxial microcatheter placed in the common hepatic artery or proper hepatic artery (Supplementary Table 1). Immediate CTHA after treatment was acquired at the discretion of the interventional radiologists to complement subjective assessment of the treatment using DSA images in cases where DSA images were not adequate to determine the treatment endpoint.

CTHA-EM imaging processing

A CTHA-EM algorithm was applied to pre- and posttreatment CTHA images with an offline prototype software (Hepacare, Siemens Healthineers, Germany). CTHA-EM analysis was not performed at the time of the procedure and was not used for intraprocedural decision-making. First, automatic registration using a deformable registration algorithm (Fig. 2) [26,27,28,29] was performed to establish a voxel-level mapping between the non-contrast and arterial phase CTHA images. Registration accuracy assessment of this algorithm was reported to be 1.3 ± 1.1 mm on average, with larger errors (1.9 ± 1.7 mm) seen on the periphery of the liver. We did not assess the registration accuracy of the algorithm as it was beyond the scope of this paper, and our datasets were acquired back to back with exact imaging acquisition settings, less prone to artifacts from breathing/cardiac motion, and very minimal liver deformation. Second, registered images were subtracted to uncover true tumor enhancement. These two steps took less than 30 s and were performed on pre- and post-images separately to create pre- and posttreatment CTHA-EM images, respectively. Third, pre- and posttreatment CTHA-EM images were co-registered to facilitate voxel-based comparison and to segment HCC on the posttreatment CTHA-EM images. Processing was done on the full quasi-isotropic high-resolution data (voxel size, 0.6 mm3) without any smoothing to retain full vascular contrast.

Fig. 2
figure 2

Schematic illustration of proposed CTHA-EM method to predict hepatocellular carcinoma response to DEB-TACE. a CTHA image acquisition during DEB-TACE consists of dual-phase CT (native- and contrast-enhanced arterial phases) acquired before and after DEB-TACE. Pre-treatment CTHA showed hypervascular tumor in segment 8 (white arrow). Posttreatment CTHA showed contrast agent accumulation within the tumor from DEB-TACE along with arterial supply (black arrow), making it difficult to delineate contrast stasis from residual tumor blush. b Pre- and posttreatment dual-phase CTHA images were loaded into a workstation, and software was used to generate CTHA-EM images with deformable registration and subtraction to assess residual tumor enhancement. The tumor was highlighted on pre-treatment CTHA enhancement mapping (white arrow), and no residual tumor enhancement was depicted on the posttreatment CTHA enhancement mapping (dotted circle). Contrast stasis from the posttreatment native CT was subtracted from the arterial phase to show potential residual tumor arterial enhancement. c First follow-up computed tomography imaging after DEB-TACE was used to predict the treatment response accordingly to mRECIST, confirming complete response in this case. CTHA, Computed tomography hepatic arteriography; CTHA-EM CTHA, enhancement mapping; DEB-TACE, Drug-eluting beads transarterial chemoembolization; mRECIST, Modified Response Evaluation Criteria in Solid Tumors

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CTHA-EM analysis and interpretation

CTHA-EM analysis was conducted by a computer scientist (G.C.) and an imaging physicist (E.K.), independent of any interventional radiologists. Furthermore, such analysis was subsequently verified by an interventional radiologist board-certified in diagnostic and interventional radiology (B.C.O.) prior to the first follow-up imaging. Quantitative assessment was made by measuring the mean HU values in regions of interest (ROIs) on CTHA-EM images (Fig. 3). ROIs were drawn on pre-treatment CTHA-EM images (ROITumor — largest tumor cross-sectional area as seen on either axial or coronal plane; ROINormal — normal liver parenchyma in the contralateral hepatic lobe, excluding blood vessels) and transferred to posttreatment CTHA-EM image. Tumor relative enhancement on pre-(TPre-RE) and post-(TPost-RE) DEB-TACE CTHA-EM images was calculated as the ratio of HU values of tumor enhancement to the normal non-embolized liver parenchyma (ROITumor/ROINormal). Tumor response to DEB-TACE was defined as no residual (TPost-RE ≤ 1) versus residual tumor enhancement (TPost-RE > 1).

Fig. 3
figure 3

Flowchart and two examples illustrating the proposed CTHA-EM ROI-based quantitative analysis. a Flowchart of quantitative assessment of residual tumor enhancement using CTHA-EM. b Two cases exemplifying ROI-based quantitative analysis. Top row: ROITumor (solid red circle) and ROInormal (dotted red circle) were placed on pre-treatment CTHA-EM images and transferred to the corresponding anatomical location on posttreatment CTHA-EM images. Bottom row: For cases with suspected residual enhancement, voxels with higher attenuation (orange dotted circle) were used for TPost-RE to avoid normalization bias from zero voxels due to subtraction of contrast stasis. Tpost-RE, Relative enhancement of tumor on posttreatment images; CTHA-EM, Computed tomography hepatic arteriography enhancement mapping; ROI, Region of interest

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CTHA-EM-imaging-based response prediction was interpreted and recorded blinded to the first follow-up imaging (FUI). Finally, for tumors with residual enhancement on posttreatment CTHA-EM images, maximum intensity projection (5−10 mm thin) images were used to identify the potential feeding arteries supplying the residual tumor enhancement areas, which was defined by the presence of an artery leading to the area of residual tumor enhancement. In addition, pre-treatment CTHA imaging was evaluated to identify if such feeding arteries were present or if they were new collaterals that developed following DEB-TACE delivery.

Follow-up imaging and the treatment response

The first follow-up imaging after DEB-TACE was performed either with magnetic resonance imaging (MRI) or CT quadriphasic protocol according to the American Association for the Study of Liver Diseases guidelines [2]. Two interventional radiologists (E.Y.L. and S.Y.H.), with 8 and 9 years of experience, the later one being a board-certified in diagnostic and interventional radiology, blinded to CTHA-EM, assessed the per-tumor treatment response according to mRECIST criteria.

Statistical analysis

The study primary outcome measure was to evaluate the ability of CTHA-EM in predicting the per-tumor treatment response at the first follow-up imaging. Secondary outcome was to correlate the exact anatomical areas of residual tumor on CTHA-EM with the first follow-up imaging and to explore the capability of CTHA-EM in identifying the feeding arteries to residual tumors. Quantitative evaluation of tumor relative enhancement pre- and post-DEB-TACE (HU and percentage change) between treatment response cohorts was performed using the Wilcoxon rank-sum test. To calculate specificities, sensitivities, positive predictive values (PPV), and negative predictive values (NPV) with 95% confidence intervals (CI), we used cross-tabulation. Values of p lower than 0.05 were considered statistically significant. Statistical analysis was performed by using commercially available statistical software (SPSS, v.24; IBM, Armonk, USA).

Results

A total of 29 patients (24 men, mean age 68 years, range 50−87) with 46 HCCs (mean diameter 2.7 cm, range 0.6–6.3) submitted to twenty-nine DEB-TACE sessions met the inclusion criteria. Demographic and clinical characteristics of all the patients are shown in Table 1.

Table 1 Baseline demographics and clinical characteristics of 29 patients who underwent DEB-TACE
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Quantitative evaluation of tumor relative enhancement (TPre-RE and TPost-RE) showed significant differences between residual and no-residual enhancement groups after DEB-TACE (mean ± standard deviation 3.05 ± 2.4 versus 0.48 ± 0.23, respectively, p < 0.001). No significant differences in HU were observed in HCCs between no-residual and residual enhancement before treatment (mean ± standard deviation 3.66 ± 2.7 versus 3.68 ± 2.0, p = 0.671), indicating that the posttreatment CT attenuation values of the residual enhancement were similar to the pre-treatment values. Per-tumor response analysis based on CTHA-EM (TPost-RE) showed 18/46 (39.1%) HCCs that had residual enhancement, while 28/46 (60.9%) had no residual arterial enhancement.

The median interval from DEB-TACE to the follow-up imaging was 6.7 weeks (interquartile range 3.7−9.7). The first follow-up imaging showed complete response in 27 (58.7%), partial response in 17 (37.0%), and stable disease in 2 (4.3%) of the 46 HCCs. Table 2 shows the correlation between CTHA-EM imaging and the first follow-up imaging tumor response assessment. Treatment response prediction by CTHA-EM images yielded a sensitivity of 94.7% (95% CI, 74.0–99.9), specificity of 100.0% (95% CI, 87.2−100), PPV of 100% (95% CI, 79.3–100), NPV of 96.4% (95% CI, 80.0–99.5), and an accuracy of 97.8% (95% CI, 88.5–99.9). Based on CTHA-EM analysis, there was only one false-negative case for residual tumor enhancement, identified as PR on the follow-up imaging, of all the 46 tumors (Fig. 4).

Table 2 Diagnostic accuracy of intra-procedural CTHA-EM
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Fig. 4
figure 4

A false-negative case for no-residual enhancement on CTHA-EM analysis showing residual tumor on first follow-up imaging 13.3 weeks later. a Pretreatment CTHA arterial phase showed hypervascular HCC (white arrow). b Posttreatment CTHA showed retention of contrast media in the tumor (white arrow). c Pre-treatment CTHA-EM image shown in inverted gray scale with HCC (white arrow). d Posttreatment CTHA-EM demonstrated lack of residual tumor enhancement at the target HCC or its feeding artery, therefore identified as “no-residual.” e First follow-up CT imaging (arterial phase) showed residual tumor (white arrow). f Second session of pretreatment CTHA confirmed residual tumor along the border of treated tumor (white arrow). Tumor progression instead of residual untreated tumor cannot be excluded due to long follow-up period from DEB-TACE procedure to first follow-up imaging. CTHA, Computed tomography hepatic arteriography; CTHA-EM, CTHA enhancement mapping; DEB-TACE, Drug-eluting beads transarterial chemoembolization; HCC, Hepatocellular carcinoma

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Among the 18 HCCs with residual arterial enhancement at CTHA-EM, a total of 22 feeding arteries were identified on the posttreatment CTHA-EM images. These feeding arteries were not depicted on posttreatment two-dimensional DSA and were obscured by the presence of contrast agent stasis and the enhancement of the liver parenchyma on posttreatment CTHA (Fig. 5). Of these 22 arteries, 20 (90.9%) were the same arteries initially identified on pre-treatment CTHA and treated with DEB-TACE (suboptimal embolization endpoint per CTHA-EM), whereas 2 (9.1%) arteries were not supplying the tumor on pre-treatment CTHA and were therefore designated as newly developed collateral arteries posttreatment.

Fig. 5
figure 5

An example illustrating how to identify feeding arteries on CTHA-EM with residual tumor enhancement. a Before DEB-TACE, a small feeding artery (orange arrow) could be barely depicted on pre-treatment imaging. b After DEB-TACE, this feeding artery became prominent (orange arrow) with residual tumor enhancement (red arrow) on posttreatment CTHA-EM image. A region of contrast stasis could be seen as a subtracted void area (white arrow). c Posttreatment native CT depicts contrast deposition from the delivery of DEB-TACE (white arrow) at the region suspicious for residual tumor enhancement. d Posttreatment CTHA identified a feeding artery (orange arrow) to the area of contrast deposition in c. However, it is not possible to distinguish residual enhancement from stasis without subtraction image. CT, Computed tomography; CTHA, CT hepatic arteriography; CTHA-EM, CTHA enhancement mapping; DEB-TACE, Drug-eluting beads transarterial chemoembolization

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Discussion

In this proof-of-concept study, the proposed CTHA-EM method demonstrated a high accuracy in predicting HCC treatment response to DEB-TACE on the initial follow-up imaging. Moreover, among HCCs where complete response was not achieved, CTHA-EM was able to depict the feeding arteries supplying the residual tumor enhancement area. The deformable registration and subtraction of unenhanced and contrast-enhanced CTHA images allowed to differentiate true residual tumor enhancement from contrast agent stasis or pooling within the treated HCCs. Additionally, tumor relative enhancement metric provided an objective and reproducible method to determine residual tumor enhancement following DEB-TACE.

Objective response (complete or partial response) according to mRECIST is a relevant prognostic factor of survival in HCC patients undergoing TACE [30,31,32]. Furthermore, patients with complete response have longer overall survival than those with partial response [7]. Unfortunately, approximately only 50% of the treated HCC tumors exhibit complete response after DEB-TACE [30,31,32]. Although such low complete response rates can be attributed to tumor biology or more advanced disease [22, 33], technical limitations during TACE procedures cannot be neglected as potential contributing factors. An important technical limitation of DEB-TACE is the lack of an objective intraprocedural method to determine the treatment endpoint. Angiographic indicators of complete embolization are difficult to reproduce, resulting in variable survival outcomes [18]. Moreover, nondominant communicating arterial arcades, which frequently supply HCCs at the liver watershed areas, might become dominant feeding arteries when the primary feeding arteries are embolized [34, 35] or occluded [36, 37]. Such tumor perfusion redistribution from interlobar collateral arteries could be one of the reasons for the low complete response rates [38, 39]. Therefore, recognizing residual tumor enhancement and its feeding arteries intra-procedurally is crucial during DEB-TACE.

CTHA-EM can be a valuable intraprocedural tool to improve the treatment response prediction during HCC treatment with DEB-TACE. The challenges in predicting intra-procedural response to DEB-TACE are well illustrated in our present study, as 39.1% (18/46) of the treated HCCs had residual tumor on the first follow-up imaging, despite being deemed to have complete response at the DEB-TACE procedure’s completion per the interventional radiologist’s judgment based on the DSA and CTHA (non-contrast and arterial phase) images. This suggests that standard DSA and CTHA have a low negative predictive value in predicting incomplete DEB-TACE. Also, there is indication that CTHA-EM can provide valuable information on the identification of the residual tumor feeding artery, which could improve the treatment strategy (i.e., need for further embolization), potentially improving the overall complete response rates following DEB-TACE.

We believe that the high accuracy of CTHA-EM in identifying residual tumor demonstrated in the present study is related to several factors. First, the use of CT has many advantages as it provides reliable and reproducible imaging, allows standardized quantitative arterial enhancement assessment via HU quantification, offers easy correlation with the follow-up imaging, and facilitates better image quality with comparable or often lower radiation exposure compared to CBCT [24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40]. Second, since CTHA-EM uses subtraction imaging, it removes background noise resulting from contrast-media stasis/pooling within the tumor and adjacent vessels and allows reliable HU value normalization. Based on the CT value comparison between non-residual and residual tumors, quantitative evaluation showed significant differences, suggesting that an incomplete embolization might have been the culprit for not achieving complete response on the vast majority of HCCs reported in this present patient population.

This study has several limitations. First, the small number of cases reported might limit the generalizability of the present findings. The use of CT during hepatic arteriography for DEB-TACE has been part of our institution’s practice since 2016. The requirement of pre- and posttreatment CTHA images limited the case number for this proof-of-concept study. Such repeated CTHA imaging is not performed routinely in all cases, and it would translate into an increase on overall patient exposure to radiation. Therefore, we included patients from three different institutions from 2017 to 2020 to expand the number of cases to achieve sufficient power. Likewise, there is an inherent sampling bias as only patients undergoing first session DEB-TACE and who did not have extrahepatic arterial supply were included in this study. Third, correlating the results of CTHA-EM to treatment response on first follow-up imaging has its limitations, as tumor progression or response may occur beyond the first follow-up imaging. Fourth, the applicability of this method is limited to procedure rooms equipped with hybrid angio/CT system. Although the install base of angio/CT equipment in interventional radiology practice has seen a recent uptick, its current availability is widely limited to major academic centers, thus presently resulting in limited availability of the proposed method when implemented for intra-procedural use.

In conclusion, the proposed CTHA-EM method can accurately and quantitively predict intraprocedural embolization endpoint and immediate treatment response after DEB-TACE on first imaging follow-up. In addition, it allows detection of the feeding arteries to residual tumor enhancement areas. The role of this method to personalize post-DEB-TACE imaging follow-up and its impact on tumor progression or response should be prospectively evaluated.

Availability of data and materials

Anonymized clinical data specific to this study will be shared upon request.

Abbreviations

CBCT:

Cone-beam computed tomography

CT:

Computed tomography

CTHA:

Computed tomography hepatic arteriography

CTHA-EM:

Computed tomography hepatic arteriography-enhancement mapping

DEB-TACE:

Drug-eluting beads transarterial chemoembolization

DSA:

Digital subtraction angiography

mRECIST:

Modified response evaluation criteria in solid tumors

HU:

Hounsfield units

MRI:

Magnetic resonance imaging

ROI:

Region of interest

TACE:

Transarterial chemoembolization

References

  1. European Association for the Study of the Liver; European Organisation for Research and Treatment of Cancer (2012) EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 56:908–943. https://doi.org/10.1016/j.jhep.2011.12.001

    Article  Google Scholar 

  2. Heimbach JK, Kulik LM, Finn RS et al (2018) AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology 67:358–380. https://doi.org/10.1002/hep.29086

    Article  Google Scholar 

  3. European Association for the Study of the Liver (2018) EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 69:182–236. https://doi.org/10.1016/j.jhep.2018.03.019

    Article  Google Scholar 

  4. Lencioni R, Llovet JM (2010) Modified RECIST (mRECIST) assessment for hepatocellular carcinoma. Semin Liver Dis 30:52–60. https://doi.org/10.1055/s-0030-1247132

    Article  CAS  Google Scholar 

  5. Patella F, Pesapane F, Fumarola E et al (2019) Assessment of the response of hepatocellular carcinoma to interventional radiology treatments. Future Oncol 15:1791–1804. https://doi.org/10.2217/fon-2018-0747

    Article  CAS  Google Scholar 

  6. Chapiro J, Wood LD, Lin M et al (2014) Radiologic-pathologic analysis of contrast-enhanced and diffusion-weighted MR imaging in patients with HCC after TACE: diagnostic accuracy of 3D quantitative image analysis. Radiology 273:746–758. https://doi.org/10.1148/radiol.14140033

    Article  Google Scholar 

  7. Shim JH, Lee HC, Kim SO et al (2012) Which response criteria best help predict survival of patients with hepatocellular carcinoma following chemoembolization? A validation study of old and new models. Radiology 262:708–718. https://doi.org/10.1148/radiol.11110282

    Article  Google Scholar 

  8. Odisio BC, Galastri F, Avritscher R et al (2014) Hepatocellular carcinomas within the Milan criteria: predictors of histologic necrosis after drug-eluting beads transarterial chemoembolization. Cardiovasc Intervent Radiol 37:1018–1026. https://doi.org/10.1007/s00270-013-0759-z

    Article  Google Scholar 

  9. Takayasu K, Muramatsu Y, Maeda T et al (2001) Targeted transarterial oily chemoembolization for small foci of hepatocellular carcinoma using a unified helical CT and angiography system: analysis of factors affecting local recurrence and survival rates. AJR Am J Roentgenol 176:681–688. https://doi.org/10.2214/ajr.176.3.1760681

    Article  CAS  Google Scholar 

  10. Tognolini A, Louie JD, Hwang GL, Hofmann LV, Sze DY, Kothary N (2010) Utility of C-arm CT in patients with hepatocellular carcinoma undergoing transhepatic arterial chemoembolization. J Vasc Interv Radiol 21:339–347. https://doi.org/10.1016/j.jvir.2009.11.007

    Article  Google Scholar 

  11. Choi BI, Kim HC, Han JK et al (1992) Therapeutic effect of transcatheter oily chemoembolization therapy for encapsulated nodular hepatocellular carcinoma: CT and pathologic findings. Radiology 182:709–713. https://doi.org/10.1148/radiology.182.3.1311116

    Article  CAS  Google Scholar 

  12. Monsky WL, Kim I, Loh S et al (2010) Semiautomated segmentation for volumetric analysis of intratumoral ethiodol uptake and subsequent tumor necrosis after chemoembolization. AJR Am J Roentgenol 195:1220–1230. https://doi.org/10.2214/AJR.09.3964

    Article  Google Scholar 

  13. Golowa YS, Cynamon J, Reinus JF et al (2012) Value of noncontrast CT immediately after transarterial chemoembolization of hepatocellular carcinoma with drug-eluting beads. J Vasc Interv Radiol 23:1031–1035. https://doi.org/10.1016/j.jvir.2012.04.020

    Article  Google Scholar 

  14. Suk OJ, Jong Chun H, Gil Choi B, Giu Lee H (2013) Transarterial chemoembolization with drug-eluting beads in hepatocellular carcinoma: usefulness of contrast saturation features on cone-beam computed tomography imaging for predicting short-term tumor response. J Vasc Interv Radiol 24:483–489. https://doi.org/10.1016/j.jvir.2013.01.001

    Article  Google Scholar 

  15. Loffroy R, Lin M, Yenokyan G et al (2013) Intraprocedural C-arm dual-phase cone-beam CT: can it be used to predict short-term response to TACE with drug-eluting beads in patients with hepatocellular carcinoma? Radiology 266:636–648. https://doi.org/10.1148/radiol.12112316

    Article  Google Scholar 

  16. Syha R, Grozinger G, Grosse U et al (2016) Parenchymal blood volume assessed by C-arm-based computed tomography in immediate posttreatment evaluation of drug-eluting bead transarterial chemoembolization in hepatocellular carcinoma. Invest Radiol 51:121–126. https://doi.org/10.1097/RLI.0000000000000215

    Article  CAS  Google Scholar 

  17. Zhang L, Jiang Y, Jin Z et al (2022) Real-time automatic prediction of treatment response to transcatheter arterial chemoembolization in patients with hepatocellular carcinoma using deep learning based on digital subtraction angiography videos. Cancer Imaging 22:23. https://doi.org/10.1186/s40644-022-00457-3

    Article  Google Scholar 

  18. Jin B, Wang D, Lewandowski RJ et al (2011) Chemoembolization endpoints: effect on survival among patients with hepatocellular carcinoma. AJR Am J Roentgenol 196:919–928. https://doi.org/10.2214/AJR.10.4770

    Article  Google Scholar 

  19. Miyayama S, Yamashiro M, Okuda M et al (2010) The march of extrahepatic collaterals: analysis of blood supply to hepatocellular carcinoma located in the bare area of the liver after chemoembolization. Cardiovasc Intervent Radiol 33:513–522. https://doi.org/10.1007/s00270-009-9697-1

    Article  Google Scholar 

  20. Eurvilaichit C, Chuapetcharasopon C (2001) Hepatic arterial collaterals after transcatheter oily chemoembolization of hepatocellular carcinoma. J Med Assoc Thai 84:75–84

    CAS  Google Scholar 

  21. Peng CW, Teng W, Lui KW et al (2021) Complete response at first transarterial chemoembolization predicts favorable outcome in hepatocellular carcinoma. Am J Cancer Res 11:4956–4965

    Google Scholar 

  22. Kim BK, Kim SU, Kim KA et al (2015) Complete response at first chemoembolization is still the most robust predictor for favorable outcome in hepatocellular carcinoma. J Hepatol 62:1304–1310. https://doi.org/10.1016/j.jhep.2015.01.022

    Article  Google Scholar 

  23. Mao X, Guo Y, Wen F, Liang H, Sun W, Lu Z (2021) Applying arterial enhancement fraction (AEF) texture features to predict the tumor response in hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE). Cancer Imaging 21:49. https://doi.org/10.1186/s40644-021-00418-2

    Article  Google Scholar 

  24. Lin EY, Jones AK, Chintalapani G, Jeng ZS, Ensor J, Odisio BC (2019) Comparative analysis of intra-arterial cone-beam versus conventional computed tomography during hepatic arteriography for transarterial chemoembolization planning. Cardiovasc Intervent Radiol 42:591–600. https://doi.org/10.1007/s00270-018-2116-8

    Article  Google Scholar 

  25. Tanaka T, Arai Y, Inaba Y et al (2014) Current role of hybrid CT/angiography system compared with C-arm cone beam CT for interventional oncology. Br J Radiol 87:20140126. https://doi.org/10.1259/bjr.20140126

    Article  CAS  Google Scholar 

  26. Yoon JH, Lee JM, Klotz E et al (2015) Estimation of hepatic extracellular volume fraction using multiphasic liver computed tomography for hepatic fibrosis grading. Invest Radiol 50:290–296. https://doi.org/10.1097/RLI.0000000000000123

    Article  Google Scholar 

  27. Lee DH, Lee JM, Klotz E et al (2013) Detection of recurrent hepatocellular carcinoma in cirrhotic liver after transcatheter arterial chemoembolization: value of quantitative color mapping of the arterial enhancement fraction of the liver. Korean J Radiol 14:51–60. https://doi.org/10.3348/kjr.2013.14.1.51

    Article  Google Scholar 

  28. Mahnken AH, Klotz E, Schreiber S et al (2011) Volumetric arterial enhancement fraction predicts tumor recurrence after hepatic radiofrequency ablation of liver metastases: initial results. AJR Am J Roentgenol 196:W573–W579. https://doi.org/10.2214/AJR.10.4410

    Article  Google Scholar 

  29. Kim KW, Lee JM, Klotz E et al (2009) Quantitative CT color mapping of the arterial enhancement fraction of the liver to detect hepatocellular carcinoma. Radiology 250:425–434. https://doi.org/10.1148/radiol.2501072196

    Article  Google Scholar 

  30. Prajapati HJ, Spivey JR, Hanish SI et al (2013) mRECIST and EASL responses at early time point by contrast-enhanced dynamic MRI predict survival in patients with unresectable hepatocellular carcinoma (HCC) treated by doxorubicin drug-eluting beads transarterial chemoembolization (DEB TACE). Ann Oncol 24:965–973. https://doi.org/10.1093/annonc/mds605

    Article  CAS  Google Scholar 

  31. Gillmore R, Stuart S, Kirkwood A et al (2011) EASL and mRECIST responses are independent prognostic factors for survival in hepatocellular cancer patients treated with transarterial embolization. J Hepatol 55:1309–1316. https://doi.org/10.1016/j.jhep.2011.03.007

    Article  Google Scholar 

  32. Jung ES, Kim JH, Yoon EL et al (2013) Comparison of the methods for tumor response assessment in patients with hepatocellular carcinoma undergoing transarterial chemoembolization. J Hepatol 58:1181–1187. https://doi.org/10.1016/j.jhep.2013.01.039

    Article  Google Scholar 

  33. Sandow TA, Arndt SE, Albar AA et al (2018) Assessment of response to transcatheter arterial chemoembolization with doxorubicin-eluting microspheres: tumor biology and hepatocellular carcinoma recurrence in a 5-year transplant cohort. Radiology 286:1072–1083. https://doi.org/10.1148/radiol.2017170731

    Article  Google Scholar 

  34. Kothary N, Takehana C, Mueller K et al (2015) Watershed hepatocellular carcinomas: the risk of incomplete response following transhepatic arterial chemoembolization. J Vasc Interv Radiol 26:1122–1129. https://doi.org/10.1016/j.jvir.2015.04.030

    Article  Google Scholar 

  35. Chou CT, Huang YC, Lee CW, Lee KW, Chen YL, Chen RC (2012) Efficacy of transarterial chemoembolization for hepatocellular carcinoma in interlobar watershed zone of liver: comparison of unilateral and bilateral chemoembolization. J Vasc Interv Radiol 23:1036–1042. https://doi.org/10.1016/j.jvir.2012.04.002

    Article  Google Scholar 

  36. Asayama Y, Nishie A, Ishigami K et al (2016) Hemodynamic changes under balloon occlusion of hepatic artery: predictor of the short-term therapeutic effect of balloon-occluded transcatheter arterial chemolipiodolization using miriplatin for hepatocellular carcinoma. Springerplus 5:157. https://doi.org/10.1186/s40064-016-1880-7

    Article  Google Scholar 

  37. Yoshimatsu R, Yamagami T, Ishikawa M et al (2016) Change in imaging findings on angiography-assisted CT during balloon-occluded transcatheter arterial chemoembolization for hepatocellular carcinoma. Cardiovasc Intervent Radiol 39:865–874. https://doi.org/10.1007/s00270-015-1279-9

    Article  Google Scholar 

  38. Tohma T, Cho A, Okazumi S et al (2005) Communicating arcade between the right and left hepatic arteries: evaluation with CT and angiography during temporary balloon occlusion of the right or left hepatic artery. Radiology 237:361–365. https://doi.org/10.1148/radiol.2371040919

    Article  Google Scholar 

  39. Chuang VP, Wallace S (1980) Hepatic arterial redistribution for intraarterial infusion of hepatic neoplasms. Radiology 135:295–299. https://doi.org/10.1148/radiology.135.2.7367615

    Article  CAS  Google Scholar 

  40. Jones AK, Odisio BC (2020) Comparison of radiation dose and image quality between flat panel computed tomography and multidetector computed tomography in a hybrid CT-angiography suite. J Appl Clin Med Phys 21:121–127. https://doi.org/10.1002/acm2.12808

    Article  Google Scholar 

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Acknowledgements

We thank Stephanie Deming, Research Medical Library, MD Anderson Cancer Center, for editing the article. We thank Shota Tatsumoto and Takeshi Matsumoto, Department of Radiology and Nuclear Medicine, Nara Medical University, who performed DEB-TACE in this study.

Funding

Funding was received by Siemens Healthineers.

Author information

Authors and Affiliations

  1. Division of Diagnostic Imaging, Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA

    Ryosuke Taiji, Yuan-Mao Lin, Ethan Y. Lin, Steven Y. Huang, Armeen Mahvash, Rony Avritscher, Sanjay Gupta & Bruno C. Odisio

  2. Department of Radiology and Nuclear Medicine, Nara Medical University, Kashihara, Nara, 634-8521, Japan

    Ryosuke Taiji, Hideyuki Nishiofuku, Toshihiro Tanaka & Kimihiko Kichikawa

  3. Siemens Medical Solutions USA Inc, 501 North Barrington Road, Hoffman Estates, IL, 60192, USA

    Gouthami Chintalapani

  4. Department of Radiology, Taipei Veterans General Hospital, Taipei, 112, Taiwan

    Chien-An Liu & Rheun-Chuan Lee

  5. College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

    Chien-An Liu & Rheun-Chuan Lee

  6. Department of Surgery, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil

    Vivian Resende

  7. Siemens Healthineers, Siemensstraße 3, 91301, Forchheim, Germany

    Ernst Klotz

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  1. Ryosuke Taiji
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  2. Yuan-Mao Lin
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Contributions

Study conception and design, BCO, GC, and EK. Data collection, RT. Data analysis, RT, GC, EYL, RA, EK, and BCO. Draft of the work, RT. Review and editing of manuscript, all authors. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Bruno C. Odisio.

Ethics declarations

Ethics approval and consent to participate

This study received IRB approval with a waiver of informed consent (IRB no. PA17-0597). The leading site (The University of Texas MD Anderson Cancer Center) received de-identified data from other 2 institutions (Nara Medical University and Taipei Veterans General Hospital) via a material transfer agreement.

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Not applicable

Competing interests

Gouthami Chintalapani and Ernst Klotz are employees of Siemens Healthineers. The other authors declare that they have no competing interests.

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Supplementary Information

Additional file 1: Supplementary Table 1.

CTHA acquisition and reconstruction parameters.

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Taiji, R., Lin, YM., Chintalapani, G. et al. A novel method for predicting hepatocellular carcinoma response to chemoembolization using an intraprocedural CT hepatic arteriography-based enhancement mapping: a proof-of-concept analysis. Eur Radiol Exp 7, 4 (2023). https://doi.org/10.1186/s41747-022-00315-8

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