Perfusion CT best predicts outcome after radioembolization of liver metastases: a comparison of radionuclide and CT imaging techniques

Learning with privileged knowledge of multiple kernels via joint prediction for CT Kernel conversion

BACKGROUND

Most existing models for CT kernel conversion take images reconstructed with a single predetermined source kernel as input and convert them to images that are reconstructed with a target kernel. However, these models can achieve even better performance if they leverage complementary information obtained from images reconstructed with multiple different kernels. In many clinical practice scenarios, only images with one kernel can be acquired.

PURPOSE

We propose a privileged knowledge learning framework that learns privileged knowledge of other source kernels available only in the training data (called privileged information) to guide the conversion from a specific single source kernel to the target kernel, via a joint prediction (JP) task.

METHODS

We construct an ensemble of kernel-specific (KS) tasks where a KS network (KSNet) takes images reconstructed with a specific source kernel as input and converts them to images reconstructed with the target kernel. Then, a JP task is designed to provide extra regularization, which helps each KSNet learn more informative feature representations for kernel conversion, such as detail and structure representations. Meanwhile, we use a cross-shaped window-based attention mechanism in the JP task to highlight the most relevant features to strengthen privileged knowledge learning, thereby alleviating the problems of redundant noise unrelated to images reconstructed with target kernel and inconsistent features that arise from images reconstructed with different kernels. All KSNets can be trained collaboratively by using a JP task to improve the performance of each individual KSNet.

RESULTS

We extensively evaluate our method on a clinical dataset with scanners from three manufacturers, that is, Siemens, GE and Philips. The experimental results demonstrate that our privileged knowledge learning framework is effective in improving CT kernel conversion.

CONCLUSIONS

Through both quantitative and qualitative research, our privileged knowledge learning framework improves the kernel conversion results, thereby contributing to the improvement of diagnostic accuracy and the advancement of comparative research in quantitative measurements.

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

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

Neovascularization, vascular mimicry and molecular exchange: The imaging of tumorous tissue aggressiveness based on tissue perfusion

Angiogenesis in healthy tissue and within malignant tumors differs on many levels, which may partly be explained by vascular mimicry formation resulting in altered contrast material or different radiopharmaceuticals distributions. Failed remodulation results in changes in the molecular exchange through the capillary wall and those consequences affect the behavior of contrast agents and radiopharmaceuticals. One of the most indicative signs of malignant tissue is the increased permeability and the faster molecular exchange that occurs between the extracellular and intravascular spaces. Dynamic imaging can help to assess the changed microenvironment. The fast-distribution of molecules reflects newly developed conditions in blood-flow redistribution inside a tumor and within the affected organ during the early stages of tumor formation. Tumor development, as well as aggressiveness, can be assessed based on the change to the vascular bed development, the level of molecular exchange within the tissue, and/or indicative distribution within the organ. The study of the vascular network organization and its impact on the distribution of molecules is important to our understanding of the image pattern in several imaging methods, which in turn influences our interpretation of the findings. A hybrid imaging approach (including PET/MRI) allows the quantification of vascularization and/or its pathophysiological impressions in structural and metabolic images. It might optimize the evaluation of the pretreatment imaging, as well as help assess the effect of therapy targeting neovascularization; antiVEGF drugs and embolization-based therapies, for example.

Prediction of treatment response to transarterial radioembolization of liver metastases: Radiomics analysis of pre-treatment cone-beam CT: A proof of concept study

Purpose

To investigate the potential of texture analysis and machine learning to predict treatment response to transarterial radioembolization (TARE) on pre-interventional cone-beam computed tomography (CBCT) images in patients with liver metastases.

Materials and Methods

In this IRB-approved retrospective single-center study 36 patients with a total of 104 liver metastases (56 % male, mean age 61.1 ± 13 years) underwent CBCT prior to TARE and follow-up imaging 6 months after therapy. Treatment response was evaluated according to RECIST version 1.1 and dichotomized into disease control (partial response/stable disease) versus disease progression (progressive disease). After target lesion segmentation, 104 radiomics features corresponding to seven different feature classes were extracted with the pyRadiomics package. After dimension reduction machine learning classifications were performed on a custom artificial neural network (ANN). Ten-fold cross validation on a previously unseen test data set was performed.

Results

The average administered cumulative activity from TARE was 1.6 Gbq (± 0.5 Gbq). At a mean follow-up of 5.9 ± 0.8 months disease control was achieved in 82 % of metastases. After dimension reduction, 15 of 104 (15 %) texture analysis features remained for further analysis. On a previously unseen set of liver metastases the Multilayer Perceptron ANN yielded a sensitivity of 94.2 %, specificity of 67.7 % and an area-under-the receiver operating characteristics curve of 0.85.

Conclusion

Our study indicates that texture analysis-based machine learning may has potential to predict treatment response to TARE using pre-treatment CBCT images of patients with liver metastases with high accuracy.

Effects of Interventional Therapy on Liver Metastases-Measurement of Liver Volume by Abdominal Computed Tomography

Purpose: To evaluate the effects of transhepatic arterial infusion (TAI) with transcatheter arterial embolization (TAE) on liver volume of patients with liver metastases, by liver volumetry using 256-slice CT (iCT 256, Philips Healthcare). Methods: A retrospective analysis of 19 patients with liver metastases, who received combination treatment of TAI with TAE, were conducted. Residual liver volumes (LV) were measured before (LV0), after the first (LV1) and the second treatment (LV2) with iCT 256. Bland-Altman method was used to evaluate the agreements of residual liver volume between two reviewers. Residual liver volume changes were compared by One-Way ANOVA. Results: For the first reviewer, LV0, LV1, LV2 were: 872.67±139.31, 960.63±143.91, 842.13±141.45 cc. LV1 > LV0, but the difference was not significant (P = 0.061). LV2 < LV0, the difference was statistically significant (P = 0.013). LV2 < LV0, and the difference was not statistically significant (P = 0.509). For the second reviewer, LV0, LV1, LV2 were: 909.99±135.46, 996.36±180.10, 845.70±131.632 cc. LV1 > LV0, the difference was not statistically significant (P = 0.083). LV2 < LV1, the difference was statistically significant (P = 0.003). LV2 < LV0, the difference was not statistically significant (P = 0.194). Conclusion: Combination treatment of TAI with TAE did not induce significant liver damage in patients with metastatic liver cancer, and iCT256 volumetry provided a precise measurement of liver volume and may play a critical role in the development of interventional surgery.

Comparison of patient dose from routine multi-phase and dynamic liver perfusion CT studies taking into account the effect of iodinated contrast administration

OBJECTIVES

To accurately determine and compare patient radiation burden from routine multi-phase CT (MPCT) and dynamic CT liver perfusion (CTLP) studies taking into account the effect of iodine uptake of exposed tissues/organs.

MATERIALS AND METHODS

40 consecutive MPCT of upper abdomen and 40 consecutive CTLP studies performed on a modern CT scanner were retrospectively studied. Iodine uptake of radiosensitive tissues at the time of acquisition was calculated through the difference of tissues' CT numbers between NECT and CECT images. Monte Carlo simulation and mathematical anthropomorphic phantoms were employed to derive patient-size-specific organ dose data from each scan involved taking into account the effect of iodinated contrast uptake on absorbed dose. Effective dose estimates were derived for routine multiphase CT and CTLP by summing up the contribution of NECT and CECT scans involved.

RESULTS

The mean underestimation error in organ doses from CECT exposures if iodine uptake is not encountered was found to be 2.2%-38.9%. The effective dose to an average-size patient from routine 3-phase CT, 4-phase CT and CTLP studies was found to be 20.6, 27.7 and 25.8 mSv, respectively. Effective dose from CTLP was found lower than 4-phase CT of upper abdomen irrespective of patient body size. Compared to 3-phase CT, the radiation burden from CTLP was found to be higher for average size-patients but again lower for overweight patients.

CONCLUSIONS

Modern CT technology allows CTLP studies at comparable or even lower patient radiation burden compared to routine multi-phase liver CT imaging.

Assessment of Therapy Response to Transarterial Radioembolization for Liver Metastases by Means of Post-treatment MRI-Based Texture Analysis

INTRODUCTION

To determine whether post-treatment magnetic resonance imaging (MRI)-based texture analysis of liver metastases (LM) may be suited predicting therapy response to transarterial radioembolization (TARE) during follow-up.

MATERIALS AND METHODS

Thirty-seven patients with LM treated by TARE (mean age 63.4 years) between January 2006 and December 2014 were identified in this retrospective feasibility study. They underwent dynamic contrast-enhanced and hepatocellular phase MRI after TARE (mean 2.2 days). Response was evaluated on follow-up imaging scheduled in intervals of 3 months (median follow-up, 7.3 months) based on response evaluation criteria in solid tumors 1.1 (RECIST 1.1). Results of texture analysis [mean, standard deviation, skewness (s), kurtosis (k), entropy and uniformity] were compared between patients with progressive disease (PD) and patients with stable disease (SD), partial or complete response (PR/CR). Receiver operating characteristics including the area under the curve (AUC) and cutoff values including the sensitivity and specificity were calculated.

RESULTS

According to RECIST 1.1, 24 patients (64.9%) had PD, 8 SD (21.6%) and 5 PR (13.5%). MRI-based texture analysis showed an earlier differentiation between patients with and without PD when compared with RECIST 1.1. Median k (2.88 vs. 2.35) in arterial phase MRI and median s (0.48 vs. 0.25) and k (2.85 vs. 2.25) in venous phase MRI were significantly different (p < 0.05). The AUC for k derived from arterial phase MRI was 0.73 (cutoff = 2.55, sensitivity = 0.83, specificity = 0.62) (p < 0.05). The AUC for s and k in venous phase MRI was 0.76 (cutoff = 0.35, sensitivity = 0.71, specificity = 0.85) (p > 0.05) and 0.83 (cutoff = 2.50, sensitivity = 0.75, specificity = 0.85) (p < 0.05).

CONCLUSION

This study indicates the potential of MRI-based texture analysis at arterial and venous phase MRI for the early prediction of PD after TARE.

LEVEL OF EVIDENCE

IV.

Dual-energy CT iodine maps as an alternative quantitative imaging biomarker to abdominal CT perfusion: determination of appropriate trigger delays for acquisition using bolus tracking

OBJECTIVE

Quantitative evaluation of different bolus tracking trigger delays for acquisition of dual energy (DE) CT iodine maps as an alternative to CT perfusion.

METHODS

Prior to this retrospective analysis of prospectively acquired data, DECT perfusion sequences were dynamically acquired in 22 patients with pancreatic carcinoma using dual source CT at 80/140 kV_p with tin filtration. After deformable motion-correction, perfusion maps of blood flow (BF) were calculated from 80 kV_p image series of DECT, and iodine maps were calculated for each of the 34 DECT acquisitions per patient. BF and iodine concentrations were measured in healthy pancreatic tissue and carcinoma. To evaluate potential DECT acquisition triggered by bolus tracking, measured iodine concentrations from the 34 DECT acquisitions per patient corresponding to different trigger delays were assessed for correlation to BF and intergroup differences between tissue types depending on acquisition time.

RESULTS

Average BF measured in healthy pancreatic tissue and carcinoma was 87.6 ± 28.4 and 38.6 ± 22.2 ml/100 ml min^-1, respectively. Correlation between iodine concentrations and BF was statistically significant for bolus tracking with trigger delay greater than 0 s (r_max = 0.89; p < 0.05). Differences in iodine concentrations between healthy pancreatic tissue and carcinoma were statistically significant for DECT acquisitions corresponding to trigger delays of 15-21 s (p < 0.05).

CONCLUSION

An acquisition window between 15 and 21 s after exceeding bolus tracking threshold shows promising results for acquisition of DECT iodine maps as an alternative to CT perfusion measurements of BF. Advances in knowledge: After clinical validation, DECT iodine maps of pancreas acquired using bolus tracking with appropriate trigger delay as determined in this study could offer an alternative quantitative imaging biomarker providing functional information for tumor assessment at reduced patient radiation exposure compared to CT perfusion measurements of BF.

CT Perfusion for Early Response Evaluation of Radiofrequency Ablation of Focal Liver Lesions: First Experience

PURPOSE

To investigate the value of perfusion CT (P-CT) for early assessment of treatment response in patients undergoing radiofrequency ablation (RFA) of focal liver lesions.

METHODS AND MATERIALS

20 consecutive patients (14 men; mean age 64 ± 14) undergoing P-CT within 24 h after RFA of liver metastases (n = 10) or HCC (n = 10) were retrospectively included. Two readers determined arterial liver perfusion (ALP, mL/min/100 mL), portal liver perfusion (PLP, mL/min/100 mL), and hepatic perfusion index (HPI, %) in all post-RFA lesions by placing a volume of interest in the necrotic central (CZ), the transition (TZ), and the surrounding parenchymal (PZ) zone. Patients were classified into complete responders (no residual tumor) and incomplete responders (residual/progressive tumor) using imaging follow-up with contrast-enhanced CT or MRI after a mean of 57 ± 30 days. Prediction of treatment response was evaluated using the area under the curve (AUC) from receiver operating characteristic analysis.

RESULTS

Mean ALP/PLP/HPI of both readers were 4.8/15.4/61.2 for the CZ, 9.9/16.8/66.3 for the TZ and 20.7/29.0/61.8 for the PZ. Interreader agreement of HPI was fair for the CZ (intraclass coefficient 0.713), good for the TZ (0.813), and excellent for the PZ (0.920). For both readers, there were significant differences in HPI of the CZ and TZ between responders and nonresponders (both, P < 0.05). HPI of the TZ showed the highest AUC (0.911) for prediction of residual tumor, suggesting a cut-off value of 76 %.

CONCLUSION

Increased HPI of the transition zone assessed with P-CT after RFA might serve as an early quantitative biomarker for residual tumor in patients with focal liver lesions.

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging for Prediction of Early Arterial Blood Flow Stasis in Radioembolization of Breast Cancer Liver Metastases

PURPOSE

To retrospectively evaluate predictive value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for early arterial blood flow stasis during transarterial radioembolization (TARE) of liver dominant breast metastases (LdBM).

MATERIALS AND METHODS

Preinterventional 1.5T DWI (b0, b1, b2 = 0, 50, 800 s/mm(2)) data for 28 liver lobes of 18 female patients treated by resin-based radioembolization (10 bilobar and 8 unilobar treatments) were analyzed. Apparent diffusion coefficient (ADC) (0, 800) and an estimation of the true diffusion coefficient D' and of the perfusion fraction f' were calculated for the 2 largest metastases. Response rate at 3 months and survival were analyzed. Procedures without full dose application because of early stasis were assigned to group A (n = 15), and procedures with full dose application were assigned to group B (n = 13).

RESULTS

Metastases in group A showed significantly lower f' (0.035 ± 0.018 vs 0.076 ± 0.015, P < .0001) and a trend toward lower ADC(0, 800) with values given in 10(-6) mm(2)/s (1,066 ± 141 vs 1,189 ± 176, P = .051); no group difference was shown for D'. Groups were best discriminated by weighted mean f' values of the 2 largest metastases with accuracy of 100%. Mean tumor diameter before and after TARE was 51 mm ± 18 and 50 mm ± 24 in group A and 47 mm ± 27 and 48 mm ± 32 for group B. Imaging response did not differ between groups (P = .545). Overall survival did not differ significantly between group A (230 d) and B (155 d) (P = .124).

CONCLUSIONS

Perfusion-sensitive IVIM parameter f' may predict early blood flow stasis in patients undergoing TARE for LdBM. Determination of this parameter before intervention may increase awareness of the interventionalist and increase safety of microsphere administration.

The value of intravoxel incoherent motion model-based diffusion-weighted imaging for outcome prediction in resin-based radioembolization of breast cancer liver metastases

Purpose

To evaluate prognostic values of clinical and diffusion-weighted magnetic resonance imaging-derived intravoxel incoherent motion (IVIM) parameters in patients undergoing primary radioembolization for metastatic breast cancer liver metastases.

Subjects and methods

A total of 21 females (mean age 54 years, range 43–72 years) with liver-dominant metastatic breast cancer underwent standard liver magnetic resonance imaging (1.5 T, diffusion-weighted imaging with b-values of 0, 50, and 800 s/mm²) before and 4–6 weeks after radioembolization. The IVIM model-derived estimated diffusion coefficient D’ and the perfusion fraction f’ were evaluated by averaging the values of the two largest treated metastases in each patient. Kaplan–Meier and Cox regression analyses for overall survival (OS) were performed. Investigated parameters were changes in f’- and D’-values after therapy, age, sex, Eastern Cooperative Oncology Group (ECOG) status, grading of primary tumor, hepatic tumor burden, presence of extrahepatic disease, baseline bilirubin, previous bevacizumab therapy, early stasis during radioembolization, chemotherapy after radioembolization, repeated radioembolization and Response Evaluation Criteria in Solid Tumors (RECIST) response at 6-week follow-up.

Results

Median OS after radioembolization was 6 (range 1.5–54.9) months. In patients with therapy-induced decreasing or stable f’-values, median OS was significantly longer than in those with increased f’-values (7.6 [range 2.6–54.9] vs 2.6 [range 1.5–17.4] months, P<0.0001). Longer median OS was also seen in patients with increased D’-values (6 [range 1.6–54.9] vs 2.8 [range 1.5–17.4] months, P=0.008). Patients with remission or stable disease (responders) according to RECIST survived longer than nonresponders (7.2 [range 2.6–54.9] vs 2.6 [range 1.5–17.4] months, P<0.0001). An ECOG status ≤1 resulted in longer median OS than >1 (7.6 [range 2.6–54.9] vs 1.7 [range 1.5–4.5] months, P<0.0001). Pretreatment IVIM parameters and the other clinical characteristics were not associated with OS. Classification by f’-value changes and ECOG status remained as independent predictors of OS on multivariate analysis, while RECIST response and D’-value changes did not predict survival.

Conclusion

Following radioembolization of breast cancer liver metastases, early changes in the IVIM model-derived perfusion fraction f’ and baseline ECOG score were predictive of patient outcome, and may thus help to guide treatment strategy.

Quantitative Measurements of Enhancement on Preprocedure Triphasic CT Can Predict Response of Colorectal Liver Metastases to Radioembolization

OBJECTIVE

Colorectal liver metastases (CLM) have a variable response to radioembolization. This may be due at least partly to differences in tumor arterial perfusion. The present study examines whether quantitative measurements of enhancement on preprocedure triphasic CT can be used to predict the response of CLM to radioembolization.

MATERIALS AND METHODS

We retrospectively reviewed patients with CLM treated with radioembolization who underwent pretreatment PET/CT and triphasic CT examinations and posttreatment PET/CT examinations. A total of 31 consecutive patients with 60 target tumors were included in the present study. For each tumor, we calculated the hepatic artery coefficient (HAC), portal vein coefficient (PVC), and arterial enhancement fraction (AEF) based on enhancement measurements on pretreatment triphasic CT. HAC and PVC are estimates of the hepatic artery and portal vein blood supply. AEF, which is the arterial phase enhancement divided by the portal phase enhancement, provides an estimate of the hepatic artery blood supply as a fraction of the total blood supply. For each tumor, the metabolic response to radioembolization was based on findings from the initial follow-up PET/CT scan obtained at 4-8 weeks after treatment.

RESULTS

A total of 55% of CLM had a complete or partial metabolic response. Arterial phase enhancement, the HAC, and the PVC did not predict which tumors responded to radioembolization. However, the AEF was statistically significantly greater in tumors with a complete or partial metabolic response than in tumors with no metabolic response (i.e., those with stable disease or disease progression) (p = 0.038). An AEF of less than 0.4 was associated with a 40% response rate, whereas an AEF greater than 0.75 was associated with a 78% response rate.

CONCLUSION

Response to radioembolization can be predicted using the AEF calculated from the preprocedure triphasic CT.

Evaluation of a Simplified Intravoxel Incoherent Motion (IVIM) Analysis of Diffusion-Weighted Imaging for Prediction of Tumor Size Changes and Imaging Response in Breast Cancer Liver Metastases Undergoing Radioembolization: A Retrospective Single Center Analysis

To investigate the value of a simplified intravoxel incoherent motion (IVIM) analysis for evaluation of therapy-induced tumor changes and response of breast cancer liver metastases (mBRC) undergoing radioembolization.In 21 females (mean age 54 years, range 43-72) with mBRC tumor size changes and response evaluation criteria in solid tumors (RECIST) response to 26 primary radioembolization procedures were analyzed. Standard 1.5-T liver magnetic resonance imaging including respiratory-gated diffusion-weighted imaging (DWI) with b0 = 0 s/mm, b1 = 50 s/mm, b2 = 800 s/mm before and 6 weeks after each treatment was performed. In addition to the apparent diffusion coefficient (ADC)(0,800), the estimated diffusion coefficient D' and the perfusion fraction f' were determined using a simplified IVIM approach. For each radioembolization, the 2 largest treated metastases (if available) were analyzed. Lesions were categorized according to size changes into group A (reduction of longest diameter [LD]) and group B (LD increase) after 3 months. Radioembolization procedures were further categorized into "response" (partial response and stable disease) and "nonresponse" (progressive disease) according to RECIST after 3 months. ADC and D' are given in 10 mm/s.Forty-five metastases were analyzed. Thirty-two lesions were categorized as A; 13 as B. Before therapy, group A lesions showed significantly larger f'-values than B (P = 0.001), but ADC(0,800) and D' did not differ. After therapy, in group A lesions the ADC(0,800)- and D'-values increased and f' decreased (P < 0.0001); in contrast in group B lesions f' increased (P = 0.001). Groups could be differentiated by preinterventional f' and by changes of D' and f' between pre and postinterventional imaging (area under the curve [AUC] of 0.903, 0.747 and 1.0, respectively).Preinterventional parameters did not differ between responders and nonresponders according to RECIST. ADC(0,800)- and D'-values showed a larger increase in responders compared with nonresponders (P = 0.013 and P = 0.001, respectively). After therapy f'-values decreased significantly in responders (P = 0.001). Good to excellent prediction of long-term RECIST response was possible by therapy-induced changes in LD, D', and f' (AUC 0.903, 0.879, and 0.867, respectively).A simplified IVIM model-based analysis of early post-treatment DWI can deliver additional information on tumor size changes and long-term RECIST response after radioembolization of mBRC. The estimated perfusion fraction f' is better suited for response assessment than the conventional ADC(0,800) or D'. This can be useful to guide further treatment strategy.

Perfusion CT imaging of treatment response in oncology

Perfusion CT was first described in the 1970s but has become accepted as a clinical technique in recent years. In oncological practice Perfusion CT allows the downstream effects of therapies on the tumour vasculature to be monitored. From the dynamic changes in tumour and vascular enhancement following intravenous iodinated contrast agent administration, qualitative and quantitative parameters may be derived that reflect tumour perfusion, blood volume, and microcirculatory changes with treatment. This review outlines the mechanisms of action of available therapies and state-of-the-art imaging practice.

Arterial Therapies of Non-Colorectal Liver Metastases

BACKGROUND

The unique situation of the liver with arterial and venous blood supply and the dependency of the tumor on the arterial blood flow make this organ an ideal target for intrahepatic catheter-based therapies. Main forms of treatment are classical bland embolization (TAE) cutting the blood flow to the tumors, chemoembolization (TACE) inducing high chemotherapy concentration in tumors, and radioembolization (TARE) without embolizing effect but very high local radiation. These different forms of therapies are used in different centers with different protocols. This overview summarizes the different forms of treatment, their indications and protocols, possible side effects, and available data in patients with non-colorectal liver tumors.

METHODS

A research in PubMed was performed. Mainly clinical controlled trials were reviewed. The search terms were 'embolization liver', 'TAE', 'chemoembolization liver', 'TACE', 'radioembolization liver', and 'TARE' as well as 'chemosaturation' and 'TACP' in the indications 'breast cancer', 'neuroendocrine', and 'melanoma'. All reported studies were analyzed for impact and reported according to their clinical relevance.

RESULTS

The main search criteria revealed the following results: 'embolization liver + breast cancer', 122 results, subgroup clinical trials 16; 'chemoembolization liver + breast cancer', 62 results, subgroup clinical trials 11; 'radioembolization liver + breast cancer', 37 results, subgroup clinical trials 3; 'embolization liver + neuroendocrine', 283 results, subgroup clinical trials 20; 'chemoembolization liver + neuroendocrine', 202 results, subgroup clinical trials 9; 'radioembolization liver + neuroendocrine', 64 results, subgroup clinical trials 9; 'embolization liver + melanoma', 79 results, subgroup clinical trials 15; 'chemoembolization liver + melanoma', 60 results, subgroup clinical trials 14; 'radioembolization liver + melanoma', 18 results, subgroup clinical trials 3. The term 'chemosaturation liver' was tested without indication since only few publications exist and provided us with five results and only one clinical trial.

CONCLUSION

Despite many years of clinical use and documented efficacy on intra-arterial treatments of the liver, there are still only a few prospective multicenter trials with many different protocols. To guarantee the future use of these efficacious therapies, especially in the light of many systemic or surgical therapies in the treatment of non-colorectal liver metastases, further large randomized trials and transparent guidelines need to be established.

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment

PURPOSE

To evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE).

MATERIALS AND METHODS

Sixteen patients (15 male; mean age 65 years; age range 47-80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters' ability to discriminate responders from non-responders.

RESULTS

According to mRECIST, 8 patients (50%) were responders and 8 (50%) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min(-1) 100 mL(-1)); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min(-1) 100 mL(-1); p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min(-1) 100 mL(-1), therapy response could be predicted with a sensitivity of 88% (7/8) and specificity of 75% (6/8).

CONCLUSION

Voxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.

CT Perfusion Imaging Can Predict Patients' Survival and Early Response to Transarterial Chemo-Lipiodol Infusion for Liver Metastases from Colorectal Cancers

Objective

To prospectively evaluate the performance of computed tomography perfusion imaging (CTPI) in predicting the early response to transarterial chemo-lipiodol infusion (TACLI) and survival of patients with colorectal cancer liver metastases (CRLM).

Materials and Methods

Computed tomography perfusion imaging was performed before and 1 month after TACLI in 61 consecutive patients. Therapeutic response was evaluated on CT scans 1 month and 4 months after TACLI; the patients were classified as responders and non-responders based on 4-month CT scans after TACLI. The percentage change of CTPI parameters of target lesions were compared between responders and non-responders at 1 month after TACLI. The optimal parameter and cutoff value were determined. The patients were divided into 2 subgroups according to the cutoff value. The log-rank test was used to compare the survival rates of the 2 subgroups.

Results

Four-month images were obtained from 58 patients, of which 39.7% were responders and 60.3% were non-responders. The percentage change in hepatic arterial perfusion (HAP) 1 month after TACLI was the optimal predicting parameter (p = 0.003). The best cut-off value was -21.5% and patients who exhibited a ≥ 21.5% decrease in HAP had a significantly higher overall survival rate than those who exhibited a < 21.5% decrease (p < 0.001).

Conclusion

Computed tomography perfusion imaging can predict the early response to TACLI and survival of patients with CRLM. The percentage change in HAP after TACLI with a cutoff value of -21.5% is the optimal predictor.

Technical prerequisites and imaging protocols for CT perfusion imaging in oncology

The aim of this review article is to define the technical prerequisites of modern state-of-the-art CT perfusion imaging in oncology at reasonable dose levels. The focus is mainly on abdominal and thoracic tumor imaging, as they pose the largest challenges with respect to attenuation and patient motion. We will show that low kV dynamic scanning in conjunction with detection technology optimized for low photon fluxes has the highest impact on reducing dose independently of other choices made in the protocol selection. We discuss, derived from relatively simple first principles, on what appropriate temporal sampling and total scan duration depend on and why optimized contrast medium injection protocols are also essential in limiting dose. Finally we will examine the possibility of simultaneously extracting standard morphological and functional information from one single 4D examination as a potential enabler for a more widespread use of dynamic contrast enhanced CT in oncology.