CT spectral imaging for monitoring the therapeutic efficacy of VEGF receptor kinase inhibitor AG-013736 in rabbit VX2 liver tumours

Beyond Conventional CT: Role of Dual-Energy CT in Monitoring Response to Therapy in Abdominal Malignancies

In the era of precision medicine, imaging plays a critical role in evaluating treatment response to various oncologic therapies. For decades, conventional morphologic assessments using cross-sectional imaging have been the standard for monitoring the effectiveness of systemic and locoregional therapies in patients with cancer. However, the development of new functional imaging tools has widened the scope of imaging from mere response assessment to patient selection and outcome prediction. Dual-energy CT (DECT), known for its superior material differentiation capabilities, shows promise in enhancing treatment response evaluation. DECT-based iodine quantification methods are increasingly being investigated as surrogates for assessing tumor vascularity and physiology, which is particularly important in patients undergoing emerging targeted therapies. The purpose of this review article is to discuss the current and emerging role of DECT in assessing treatment response in patients with malignant abdominal tumors. Keywords: CT-Dual Energy, Transcatheter Tumor Therapy, Tumor Response, Iodine Uptake, Therapeutic Response © RSNA, 2025.

Sequential dual-energy CT for longitudinal assessment of pathologic response to neoadjuvant immuno-chemotherapy in locally advanced gastric cancer

OBJECTIVES

To longitudinally evaluate pathologic response outcomes after neoadjuvant immuno-chemotherapy (NICT) for patients with locally advanced gastric cancer (LAGC) using pre- and post-treatment dual-energy CT (DECT).

MATERIALS AND METHODS

Between Jan 2021 and Dec 2023, 115 patients who underwent NICT plus gastrectomy and triple-phase enhanced DECT scans before and after NICT were retrospectively enrolled. Pathologic tumor regression grade (TRG) was the reference standard, patients were labelled as responders (TRG = 0 + 1) and non-responders (TRG = 2 + 3) accordingly. A two-dimensional free-hand region of interest method was adopted to obtain the iodine concentration (IC) values. Pre- and post-NICT IC and normalized IC (nIC) were measured at arterial/venous/delay phase (AP/VP/DP), respectively; their changes [ΔIC (%)] defined as (IC_post-IC_pre)⁄IC_pre × 100% were calculated. Pre- and post-NICT imaging parameters and their changes were compared between different response groups. Non-responders' associated parameters were selected using multivariable logistic regression analysis. Their performances were analyzed by the area under the receiver operating characteristic curve (AUC). Their associations with patient survival were explored by using Kaplan-Meier survival analysis.

RESULTS

ICDP-pre, ΔICAP, thickness-post with cut-off value of > 2.306 mg/mL, ≤ 26.70%, > 18.5 mm, respectively, indicates non-responders with equivalent AUC being 0.616 (95% CI: 0.521-0.705), 0.625 (95% CI: 0.529-0.713), and 0.660 (95% CI: 0.565-0.745). Their combination demonstrated an improved AUC of 0.774 (95% CI: 0.686-0.846) and was associated with patient disease-free survival (DFS) with a hazard ratio being 2.239 (95% CI: 1.004-4.991) (p = 0.026).

CONCLUSION

Pre- and post-NICT DECT-based quantifications are useful for longitudinal assessment of pathologic response outcomes after NICT in LAGC. ICDP-pre, ΔICAP, and thickness-post are equally useful, their combination demonstrated incremental benefit.

KEY POINTS

Question Accurate evaluation of the efficacy of NICT in patients with LAGC remains challenging due to the lack of effective biomarkers. Findings Sequential DECT-based ICDP-pre, ΔICAP, and tumor thickness-post were predictive of TRG status. Their combination demonstrated enhanced performance and was associated with patient DFS. Clinical relevance DECT represents a promising imaging technique with added advantages for longitudinal assessment of pathologic response to NICT in LAGC, potentially facilitating more personalized treatment strategies among this population.

Current trends in the characterization and monitoring of vascular response to cancer therapy

Tumor vascular physiology is an important determinant of disease progression as well as the therapeutic outcome of cancer treatment. Angiogenesis or the lack of it provides crucial information about the tumor's blood supply and therefore can be used as an index for cancer growth and progression. While standalone anti-angiogenic therapy demonstrated limited therapeutic benefits, its combination with chemotherapeutic agents improved the overall survival of cancer patients. This could be attributed to the effect of vascular normalization, a dynamic process that temporarily reverts abnormal vasculature to the normal phenotype maximizing the delivery and intratumor distribution of chemotherapeutic agents. Longitudinal monitoring of vascular changes following antiangiogenic therapy can indicate an optimal window for drug administration and estimate the potential outcome of treatment. This review primarily focuses on the status of various imaging modalities used for the longitudinal characterization of vascular changes before and after anti-angiogenic therapies and their clinical prospects.

Preliminary differentiation of benign and malignant gastric wall thickening using dual-layer spectral-detector CT

BACKGROUND

Dual-layer spectral-detector computed tomography (DLCT) may have the potential to evaluate gastric wall thickening.

PURPOSE

To evaluate the efficacy of DLCT quantitative parameters in differentiating between benign and malignant thickening of the gastric wall.

MATERIAL AND METHODS

A total of 58 patients with "gastric wall thickening" who underwent multi-phase abdominal enhanced DLCT scans were included in this study. Of these patients, 33 were malignant and 25 were benign. Parameters such as iodine concentration (IC), effective atomic number (Zeff), and attenuation of the lesions were measured during the arterial phase (AP) and venous phase (VP). Binary logistic regression was employed to calculate the combined prediction probabilities. The accuracy of the DLCT parameters was assessed using receiver operating characteristic (ROC) curves.

RESULTS

The values of IC, nIC, Zeff, normalized Zeff, and attenuation in the AP and VP were significantly higher (all P < 0.05) in the malignant group compared to the benign group. The ROC curves revealed that the IC, Zeff, and attenuation in the VP exhibited high diagnostic performance, with area under the ROC curve (AUC) values of 0.864, 0.862, and 0.840, respectively. The new combination of these three factors and gastric wall thickness had an AUC of 0.884, and the sensitivity and specificity were determined to be 81.8% and 92.0%, respectively.

CONCLUSION

Spectral CT parameters, particularly the combination of gastric wall thickness, attenuation, IC, and Zeff in VP, have value in distinguishing between benign and malignant gastric wall thickening.

A nomogram model of spectral CT quantitative parameters and clinical characteristics predicting lymphovascular invasion of gastric cancer

Objective

The study established a nomogram based on quantitative parameters of spectral computed tomography (CT) and clinical characteristics, aiming to evaluate its predictive value for preoperative lymphovascular invasion (LVI) in gastric cancer (GC).

Methods

From December 2019 to December 2021, 171 patients with pathologically confirmed GC were retrospectively collected with corresponding clinical data and spectral CT quantitative data. Patients were divided into LVI-positive and LVI-negative groups based on their pathological results. The univariate and multivariate logistic regression analyses were used to identify the risk factors and construct a nomogram. The calibration curve and receiver operating characteristic (ROC) curve were adopted to evaluate the predictive accuracy of nomogram.

Results

Four clinical characteristics or spectral CT quantitative parameters, including Borrmann classification (P = 0.039), CA724 (P = 0.007), tumor thickness (P = 0.031), and iodine concentration in the venous phase (VIC) (P = 0.004) were identified as independent factors for LVI in GC patients. The nomogram was established based on the four factors, which had a potent predictive accuracy in the training, internal validation and external validation cohorts, with the area under the ROC curve (AUC) of 0.864 (95% CI, 0.798-0.930), 0.964 (95% CI, 0.903-1.000) and 0.877 (95% CI, 0.759-0.996), respectively.

Conclusion

This study constructed a comprehensive nomogram consisting spectral CT quantitative parameters and clinical characteristics of GC, which exhibited a robust efficiency in predicting LVI in GC patients.

Predicting pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer: The establishment of a spectral CT-based nomogram from prospective datasets

BACKGROUND

To establish a spectral CT-based nomogram for predicting early neoadjuvant chemotherapy (NAC) response for locally advanced gastric cancer (LAGC).

METHODS

This study prospectively recruited 222 cases (177 male and 45 female patients, 9.59 ± 9.54 years) receiving NAC and radical gastrectomy. Triple enhanced spectral CT scans were performed before NAC initiation. According to post-operative tumor regression grade (TRG), patients were classified into responders (TRG = 0 + 1) or non-responders (TRG = 2 + 3), and split into a primary (156) and validation (66) dataset at 7:3 ratio chronologically. We compared clinicopathological data, follow-up information, iodine concentration (IC), normalized ICs (nICs) in arterial/venous/delayed phases (AP/VP/DP) between responders and non-responders. Independent risk factors of response were screened by multivariable logistic regression and adopted for model construction. Model was visualized by nomograms and its capability was determined through receiver operating characteristic (ROC) curves. Log-rank survival analysis was conducted to explore associations between TRG, nomogram and patients' survival.

RESULTS

This work identified Borrmann classification, ICDP, and nICDP were independent risk factors of response outcomes. A spectral CT-based nomogram was built accordingly and achieved an area under the curve (AUC) of 0.797 (0.692-0.879) and 0.741(0.661-0.811) for the primary and validation dataset, respectively, higher than AUC of individual parameters alone. The nomogram was related to disease-free survival in the validation dataset (Hazard ratio (HR): 5.19 [1.18-12.93], P = 0.02).

CONCLUSIONS

The spectral CT-based nomogram provides an efficient tool for predicting the pathologic response outcomes of GC after NAC and disease-free survival risk stratification.

Radiomics Analysis to Predict Lymphovascular Invasion of Gastric Cancer Based on Iodine-Based Material Decomposition Images and Virtual Monoenergetic Images

OBJECTIVE

This study aimed to investigate the utility of virtual monoenergetic images (VMIs) and iodine-based material decomposition images (IMDIs) in the assessment of lymphovascular invasion (LVI) in gastric cancer (GC) patients.

METHODS

A total of 103 GC patients who underwent dual-energy spectral computed tomography preoperatively were enrolled. The LVI status was confirmed by pathological analysis. The radiomics features obtained from the 70 keV VMI and IMDI were used to build radiomics models. Independent clinical factors for LVI were identified and used to build the clinical model. Then, combined models were constructed by fusing clinical factors and radiomics signatures. The predictive performance of these models was evaluated.

RESULTS

The computed tomography-reported N stage was an independent predictor of LVI, and the areas under the curve (AUCs) of the clinical model in the training group and testing group were 0.750 and 0.765, respectively. The radiomics models using the VMI signature and IMDI signature and combining these 2 signatures outperformed the clinical model, with AUCs of 0.835, 0.855, and 0.924 in the training set and 0.838, 0.825, and 0.899 in the testing set, respectively. The model combined with the computed tomography-reported N stage and the 2 radiomics signatures achieved the best performance in the training (AUC, 0.925) and testing (AUC, 0.961) sets, with a good degree of calibration and clinical utility for LVI prediction.

CONCLUSIONS

The preoperative assessment of LVI in GC is improved by radiomics features based on VMI and IMDI. The combination of clinical, VMI-, and IMDI-based radiomics features effectively predicts LVI and provides support for clinical treatment decisions.

The diagnostic value of dual-layer CT in the assessment of lymph nodes in lymphoma patients with PET/CT as a reference standard

This study aimed to evaluate the diagnostic performances of dual-layer CT (DLCT) for the identification of positive lymph nodes (LNs) in patients with lymphoma and retrospectively included 1165 LNs obtained by biopsy from 78 patients with histologically proven lymphoma, who underwent both pretreatment DLCT and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). According to 18F-FDG PET/CT findings as a reference standard, cases were categorized into the LN-negative and LN-positive groups. LNs were then randomly divided at a ratio of 7:3 into the training (n = 809) and validation (n = 356) cohorts. The patients' clinical characteristics and quantitative parameters including spectral curve slope (λHU), iodine concentration (IC) on arterial phase (AP) and venous phase (VP) images were compared between the LN-negative and LN-positive groups using Chi-square test, t-test or Mann-Whitney U test for categorical variables or quantitative parameters. Multivariate logistic regression analysis with tenfold cross-validation was performed to establish the most efficient predictive model in the training cohort. The area under the curve (AUC) was used to evaluate the diagnostic value of the predictive model, and differences in AUC were determined by the DeLong test. Moreover, the predictive model was validated in the validation cohort. Repeatability analysis was performed for LNs using intraclass correlation coefficients (ICCs). In the training cohort, long diameter (LD) had the highest AUC as an independent factors compared to other parameter in differentiating LN positivity from LN negativity (p = 0.006 to p < 0.001), and the AUC of predictive model jointly involving LD and λHU-AP was significantly elevated (AUC of 0.816, p < 0.001). While the AUC of predictive model in the validation cohort was 0.786. Good to excellent repeatability was observed for all parameters (ICC > 0.75). The combination of DLCT with morphological and functional parameters may represent a potential imaging biomarker for detecting LN positivity in lymphoma.

Thoracic Diseases: Technique and Applications of Dual-Energy CT

Dual-energy computed tomography (DECT) is one of the most promising technological innovations made in the field of imaging in recent years. Thanks to its ability to provide quantitative and reproducible data, and to improve radiologists' confidence, especially in the less experienced, its applications are increasing in number and variety. In thoracic diseases, DECT is able to provide well-known benefits, although many recent articles have sought to investigate new perspectives. This narrative review aims to provide the reader with an overview of the applications and advantages of DECT in thoracic diseases, focusing on the most recent innovations. The research process was conducted on the databases of Pubmed and Cochrane. The article is organized according to the anatomical district: the review will focus on pleural, lung parenchymal, breast, mediastinal, lymph nodes, vascular and skeletal applications of DECT. In conclusion, considering the new potential applications and the evidence reported in the latest papers, DECT is progressively entering the daily practice of radiologists, and by reading this simple narrative review, every radiologist will know the state of the art of DECT in thoracic diseases.

New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function

The latest evolutions in Computed Tomography (CT) technology have several applications in oncological imaging. The innovations in hardware and software allow for the optimization of the oncological protocol. Low-kV acquisitions are possible thanks to the new powerful tubes. Iterative reconstruction algorithms and artificial intelligence are helpful for the management of image noise during image reconstruction. Functional information is provided by spectral CT (dual-energy and photon counting CT) and perfusion CT.

The multikinase inhibitor axitinib in the treatment of advanced hepatocellular carcinoma: the current clinical applications and the molecular mechanisms

Advanced hepatocellular carcinoma (HCC) is a formidable public health problem with limited curable treatment options. Axitinib, an oral tyrosine kinase inhibitor, is a potent and selective second-generation inhibitor of vascular endothelial growth factor receptor (VEGFR) 1, 2, and 3. This anti-angiogenic drug was found to have promising activity in various solid tumors, including advanced HCC. At present, however, there is no relevant review article that summarizes the exact roles of axitinib in advanced HCC. In this review, 24 eligible studies (seven studies in the ClinicalTrials, eight experimental studies, and nine clinical trials) were included for further evaluation. The included randomized or single-arm phase II trials indicated that axitinib could not prolong the overall survival compared to the placebo for the treatment of advanced HCC, but improvements in progression free survival and time to tumor progression were observed. Experimental studies showed that the biochemical effects of axitinib in HCC might be regulated by its associated genes and affected signaling cascades (e.g. VEGFR2/PAK1, CYP1A2, CaMKII/ERK, Akt/mTor, and miR-509-3p/PDGFRA). FDA approved sorafenib combined with nivolumab (an inhibitor of PD-1/PD-L1) as the first line regimen for the treatment of advanced HCC. Since both axitinib and sorafenib are tyrosine kinase inhibitors as well as the VEGFR inhibitors, axitinib combined with anti-PDL-1/PD-1 antibodies may also exhibit tremendous potential in anti-tumoral effects for advanced HCC. The present review highlights the current clinical applications and the molecular mechanisms of axitinib in advanced HCC. To move toward clinical applications by combining axitinib and other treatments in advanced HCC, more studies are still warranted in the near future.

Spectral CT: Current Liver Applications

Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.

Early evaluation of liver metastasis using spectral CT to predict outcome in patients with colorectal cancer treated with FOLFOXIRI and bevacizumab

PURPOSE

Early evaluation of the efficacy of first-line chemotherapy combined with bevacizumab in patients with colorectal cancer liver metastasis (CRLM) remains challenging. This study used 2-month post-chemotherapy spectral computed tomography (CT) to predict the overall survival (OS) and response of CRLM patients with bevacizumab-containing therapy.

METHOD

This retrospective analysis was performed in 104 patients with pathologically confirmed CRLM between April 2017 and October 2021. Patients were treated with 5-fluorouracil, leucovorin, oxaliplatin or irinotecan with bevacizumab. Portal venous phase spectral CT was performed on the target liver lesion within 2 months of commencing chemotherapy to demonstrate the iodine concentration (IoD) of the target liver lesion. The patients were classified as responders (R +) or non-responders (R -) according to the Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 at 6 months. Multivariate analysis was performed to determine the relationships of the spectral CT parameters, tumor markers, morphology of target lesions with OS and response. The differences in portal venous phase spectral CT parameters between the R + and R - groups were analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the predictive power of spectral CT parameters.

RESULTS

Of the 104 patients (mean age ± standard deviation: 57.73 years ± 12.56; 60 men) evaluated, 28 (26.9%) were classified as R + . Cox multivariate analysis identified the iodine concentration (hazard ratio [HR]: 1.238; 95% confidence interval [95% CI]: 1.089-1.408; P < 0.001), baseline tumor longest diameter (BLD) (HR: 1.022; 95% CI: 1.005-1.038, P = 0.010), higher baseline CEA (HR: 1.670; 95% CI: 1.016-2.745, P = 0.043), K-RAS mutation (HR: 2.027; 95% CI: 1.192-3.449; P = 0.009), and metachronous liver metastasis (HR: 1.877; 95% CI: 1.179-2.988; P = 0.008) as independent risk factors for patient OS. Logistic multivariate analysis identified the IoD (Odds Ratio [OR]: 2.243; 95% CI: 1.405-4.098; P = 0.002) and clinical N stage of the primary tumor (OR: 4.998; 95% CI: 1.210-25.345; P = 0.035) as independent predictor of R + . Using IoD cutoff values of 4.75 (100ug/cm³) the area under the ROC curve was 0.916, sensitivity and specificity were 80.3% and 96.4%, respectively.

CONCLUSIONS

Spectral CT IoD can predict the OS and response of patients with CRLM after 2 months of treatment with bevacizumab-containing therapy.

Spectral CT-based nomogram for preoperative prediction of perineural invasion in locally advanced gastric cancer: a prospective study

OBJECTIVES

This work focused on developing and validating the spectral CT-based nomogram to preoperatively predict perineural invasion (PNI) for locally advanced gastric cancer (LAGC).

METHODS

This work prospectively included 196 surgically resected LAGC patients (139 males, 57 females, 59.55 ± 11.97 years) undergoing triple enhanced spectral CT scans. Patients were labeled as perineural invasion (PNI) positive and negative according to pathologic reports, then further split into primary (n = 130) and validation cohort (n = 66). We extracted clinicopathological information, follow-up data, iodine concentration (IC), and normalized IC values against to aorta (nICs) at arterial/venous/delayed phases (AP/VP/DP). Clinicopathological features and IC values between PNI positive and negative groups were compared. Multivariable logistic regression was performed to screen independent risk factors of PNI. Then, a nomogram was established, and its capability was determined by ROC curves. Its clinical use was evaluated by decision curve analysis. The correlations of PNI and the nomogram with patients' survival were explored by log-rank survival analysis.

RESULTS

Borrmann classification, tumor thickness, and nICDP were independent predictors of PNI and used to build the nomogram. The nomogram yielded higher AUCs of 0.853 (0.744-0.928) and 0.782 (0.701-0.850) in primary and validation cohorts than any other parameters (p < 0.05). Both PNI and the nomogram were related to post-surgical treatment planning. Only PNI was associated with disease-free survival in the primary cohort (p < 0.05).

CONCLUSION

This work prospectively established a spectral CT-based nomogram, which can effectively predict PNI preoperatively and potentially guide post-surgical treatment strategy in LAGC.

KEY POINTS

• The present prospective study established a spectral CT-based nomogram for preoperative prediction of perineural invasion in LAGC. • The proposed nomogram, including morphological features and the quantitative iodine concentration values from spectral CT, had the potential to predict PNI for LAGC before surgery, along with guide post-surgical treatment planning. • Normalized iodine concentration at the delayed phase was the most valuable quantitative parameter, suggesting the importance of delayed enhancement in gastric CT.

Treatment Effect of a Vascular-Disrupting Agent Dynamically Monitored by DWI: An Animal Experimental Study

Objective

To investigate the treatment effect of a vascular-disrupting agent, M410, using diffusion-weighted imaging in a rabbit model of hepatic VX2 tumor.

Methods

28 New Zealand white rabbit models with VX2 liver tumors were established and were randomly divided into M410 (intravenous injection of M410 at a dose of 25 mg/kg every three days) and control (intravenous injection of saline every three days) groups. Conventional and diffusion-weighted imaging (DWI) were acquired on a 3.0 T MR unit at baseline, 4 h, d 1, d 4, d 7, and d 14 posttreatment. B-value with 700 (s/mm2) was chosen during DWI examinations. Tumor volume and apparent diffusion coefficient (ADC) values of the entire tumor and solid component of the tumor at every time point were measured. Two randomly chosen rabbits from each group were sacrificed for H&E staining and CD34 immunohistochemical assessments at each time point. An independent sample t-test was used to assess differences in tumor sizes and ADC values of the entire tumor and solid component of tumors between two groups, with P < 0.05 considered statistically significant.

Result

There was no significant difference in tumor volume between the two groups at baseline, 4 h, and d 1. With time, the tumors in the control group grew significantly faster than those in the M410 group, and the average ADC values of the M410 group were lower than those of the control group at d 1 and higher than those of the control group at d 4; as such, there were statistical differences between the two groups at these two time points but not at the other four time points. The following pathological results reflected the underlying morphological changes and vascular alterations.

Conclusions

M410 performed well in inhibiting the growth of the hepatic VX2 tumor which could be noninvasively monitored by DWI metrics.

Dual-Energy Computed Tomography-Based Radiomics to Predict Peritoneal Metastasis in Gastric Cancer

Objective

To develop and validate a dual-energy computed tomography (DECT) derived radiomics model to predict peritoneal metastasis (PM) in patients with gastric cancer (GC).

Methods

This retrospective study recruited 239 GC (non-PM = 174, PM = 65) patients with histopathological confirmation for peritoneal status from January 2015 to December 2019. All patients were randomly divided into a training cohort (n = 160) and a testing cohort (n = 79). Standardized iodine-uptake (IU) images and 120-kV-equivalent mixed images (simulating conventional CT images) from portal-venous and delayed phases were used for analysis. Two regions of interest (ROIs) including the peritoneal area and the primary tumor were independently delineated. Subsequently, 1691 and 1226 radiomics features were extracted from the peritoneal area and the primary tumor from IU and mixed images on each phase. Boruta and Spearman correlation analysis were used for feature selection. Three radiomics models were established, including the R_IU model for IU images, the R_MIX model for mixed images and the combined radiomics model (the R_comb model). Random forest was used to tune the optimal radiomics model. The performance of the clinical model and human experts to assess PM was also recorded.

Results

Fourteen and three radiomics features with low redundancy and high importance were extracted from the IU and mixed images, respectively. The R_IU model showed significantly better performance to predict PM than the R_MIX model in the training cohort (AUC, 0.981 vs. 0.917, p = 0.034). No improvement was observed in the R_comb model (AUC = 0.967). The R_IU model was the optimal radiomics model which showed no overfitting in the testing cohort (AUC = 0.967, p = 0.528). The R_IU model demonstrated significantly higher predictive value on peritoneal status than the clinical model and human experts in the testing cohort (AUC, 0.785, p = 0.005; AUC, 0.732, p <0.001, respectively).

Conclusion

DECT derived radiomics could serve as a non-invasive and easy-to-use biomarker to preoperatively predict PM for GC, providing opportunity for those patients to tailor appropriate treatment.

Development of a dual-energy spectral CT based nomogram for the preoperative discrimination of mutated and wild-type KRAS in patients with colorectal cancer

PURPOSE

To develop a dual-energy spectral CT (DESCT) nomogram for the preoperative identification of KRAS mutation in patients with colorectal cancer (CRC).

METHOD

One hundred and twenty-four patients who underwent energy spectrum CT pre-operatively were recruited and split into mutated KRAS group (n = 50) and wild-type KRAS group (n = 74). DESCT parameters, including monochromatic CT value, iodine concentration, water concentration, and effective atomic number were measured independently by two reviewers in the arterial, venous, and delayed phases. Normalized iodine concentration (NIC) and slope k of the spectral HU curve were calculated. Evaluate other imaging features such as ATL/LTL ratio, tumor gross pattern, pericolorectal fat invasion (PFI) was also performed by these reviewers. Independent predictors for KRAS mutation were screened out using logistic regression, and these predictors were presented as a nomogram. The receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to evaluate the clinical usefulness of the nomogram.

RESULTS

The slope k in the arterial phase, effective atomic number in the arterial phase, NIC in the venous phase, ATL/LTL ratio and PFI were significant independent predictors for KRAS mutation. Based on these independent predictors, a quantitative nomogram was developed to predict individual KRAS mutation probability. The nomogram had excellent performance with an AUC of 0.848 and excellent calibration. DCA showed that our nomogram has outstanding clinical utility.

CONCLUSIONS

This study demonstrates that a DESCT based nomogram has potential value for individual preoperative identification of KRAS mutation in CRC patients.

Spatial heterogeneity of nanomedicine investigated by multiscale imaging of the drug, the nanoparticle and the tumour environment

Genetic and phenotypic tumour heterogeneity is an important cause of therapy resistance. Moreover, non-uniform spatial drug distribution in cancer treatment may cause pseudo-resistance, meaning that a treatment is ineffective because the drug does not reach its target at sufficient concentrations. Together with tumour heterogeneity, non-uniform drug distribution causes “therapy heterogeneity”: a spatially heterogeneous treatment effect. Spatial heterogeneity in drug distribution occurs on all scales ranging from interpatient differences to intratumour differences on tissue or cellular scale. Nanomedicine aims to improve the balance between efficacy and safety of drugs by targeting drug-loaded nanoparticles specifically to tumours. Spatial heterogeneity in nanoparticle and payload distribution could be an important factor that limits their efficacy in patients. Therefore, imaging spatial nanoparticle distribution and imaging the tumour environment giving rise to this distribution could help understand (lack of) clinical success of nanomedicine. Imaging the nanoparticle, drug and tumour environment can lead to improvements of new nanotherapies, increase understanding of underlying mechanisms of heterogeneous distribution, facilitate patient selection for nanotherapies and help assess the effect of treatments that aim to reduce heterogeneity in nanoparticle distribution.

In this review, we discuss three groups of imaging modalities applied in nanomedicine research: non-invasive clinical imaging methods (nuclear imaging, MRI, CT, ultrasound), optical imaging and mass spectrometry imaging. Because each imaging modality provides information at a different scale and has its own strengths and weaknesses, choosing wisely and combining modalities will lead to a wealth of information that will help bring nanomedicine forward.

Spectral Computed Tomographic Parameters Predict the Therapeutic Efficacy and Overall Survival of the Angiogenesis Inhibitor AL3818 in Hepatic Lesions: Preliminary Animal Study

OBJECTIVE

This study aimed to investigate the predictive and prognostic values of repeated spectral computed tomographic (CT) parameter changes for the prediction of treatment responses to the angiogenesis inhibitor AL3818 in hepatic tumors.

METHODS

A total of 30 rabbits with VX2 hepatic tumors that underwent spectral contrast-enhanced abdominal CT before and during treatment were included in the study. The percent change (Δ, %) of the normalized iodine concentration (nIC) during the arterial phase (AP) and venous phase (VP) was used to predict the tumor response and to calculate the overall survival (OS). The threshold of the nIC for tumor response prediction and prognostic significance was determined by a receiver operating characteristic curve and Kaplan-Meier analysis.

RESULTS

After treatment, there were 43% (13/30) responders and 57% (17/30) nonresponders. When ΔnICAP ≥ -13.10% was used as the threshold, the sensitivity and specificity for the prediction of tumor response were 82.41% and 92.31%, respectively. ΔnICVP resulted in 88.20% sensitivity and 76.92% specificity for cutoff values ≥10.78%. Kaplan-Meier analyses showed that high ΔnICAP and ΔnICVP were associated with improved OS.

CONCLUSIONS

The current study shows the capability of the changes (Δ) in repeated spectral CT parameters to predict the tumor response during antiangiogenesis therapy in small hepatic tumors. ΔnICAP and ΔnICVP were predictors for treatment response and were associated with OS.

Dose Optimization of Perfusion-derived Response Assessment in Hepatocellular Carcinoma Treated with Transarterial Chemoembolization: Comparison of Volume Perfusion CT and Iodine Concentration

RATIONALE AND OBJECTIVES

We assessed the value of iodine concentration (IC) as a perfusion-derived response marker for hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) in comparison with volume perfusion computed tomography (VPCT) parameters.

MATERIALS AND METHODS

Forty-one HCC lesions in 32 patients examined before and after TACE were analyzed retrospectively. VPCT-parameters were calculated and lesion iodine-maps were computed using subtraction of the baseline and the scan 7 seconds after aortic peak enhancement from the corresponding 80 kVp-VPCT data set. Modified RECIST was used as standard response criteria. Comparisons were performed using Student's t test for normal distributed data and Mann-Whitney U test for non-normal distributed data. Additionally, correlation analysis, receiver operating characteristics (ROC) and interreader agreement were assessed.

RESULTS

In responding lesions, mean pre-TACE IC and blood flow (BF) were 131.2 mg/100 mL and 96.7 mL/100 mL/min, decreasing to IC 25.6 mg/100 mL (P < 0.001) and BF 28.5 mL/100 mL/min (P < 0.001) post-TACE. In nonresponding lesions, the values remained almost unchanged: pre-TACE: mean BF 79.3 mL/100 mL/min and mean IC 90.4 mg/100 mL; post-TACE: mean BF 71.3 mL/100 mL/min (n.s.) and mean IC 105.4 mg/100 mL (n.s.). Differences in IC-values revealed a high sensitivity/specificity of 96.7%/81.8%. IC and VPCT-parameters showed strong, positive correlations. Mean volume CT dose index for VPCT was 63.4 mGy and 4.9 mGy for iodine maps.

CONCLUSION

Thus, IC is a meaningful perfusion marker for local therapy response monitoring in HCC that can be acquired with low radiation dose. This information is important for further therapy response applications using dual and single energy CT.

Can dual-energy CT replace perfusion CT for the functional evaluation of advanced hepatocellular carcinoma?

OBJECTIVES

To determine the degree of relationship between iodine concentrations derived from dual-energy CT (DECT) and perfusion CT parameters in patients with advanced HCC under treatment.

METHODS

In this single-centre IRB approved study, 16 patients with advanced HCC treated with sorafenib or radioembolization who underwent concurrent dynamic perfusion CT and multiphase DECT using a single source, fast kV switching DECT scanner were included. Written informed consent was obtained for all patients. HCC late-arterial and portal iodine concentrations, blood flow (BF)-related and blood volume (BV)-related perfusion parameters maps were calculated. Mixed-effects models of the relationship between iodine concentrations and perfusion parameters were computed. An adjusted p value (Bonferroni method) < 0.05 was considered significant.

RESULTS

Mean HCC late-arterial and portal iodine concentrations were 22.7±12.7 mg/mL and 18.7±8.3 mg/mL, respectively. Late-arterial iodine concentration was significantly related to BV (mixed-effects model F statistic (F)=28.52, p<0.0001), arterial BF (aBF, F=17.62, p<0.0001), hepatic perfusion index (F=28.24, p<0.0001), positive enhancement integral (PEI, F=66.75, p<0.0001) and mean slope of increase (F=32.96, p<0.0001), while portal-venous iodine concentration was mainly related to BV (F=29.68, p<0.0001) and PEI (F=66.75, p<0.0001).

CONCLUSIONS

In advanced HCC lesions, DECT-derived late-arterial iodine concentration is strongly related to both aBF and BV, while portal iodine concentration mainly reflects BV, offering DECT the ability to evaluate both morphological and perfusion changes.

KEY POINTS

• Late-arterial iodine concentration is highly related to arterial BF and BV. • Portal iodine concentration mainly reflects tumour blood volume. • Dual-energy CT offers significantly decreased radiation dose compared with perfusion CT.

Dual energy CT allows for improved characterization of response to antiangiogenic treatment in patients with metastatic renal cell cancer

OBJECTIVES

To evaluate the potential role of dual energy CT (DECT) to visualize antiangiogenic treatment effects in patients with metastatic renal cell cancer (mRCC) while treated with tyrosine-kinase inhibitors (TKI).

METHODS

26 patients with mRCC underwent baseline and follow-up single-phase abdominal contrast enhanced DECT scans. Scans were performed immediately before and 10 weeks after start of treatment with TKI. Virtual non-enhanced (VNE) and colour coded iodine images were generated. 44 metastases were measured at the two time points. Hounsfield unit (HU) values for VNE and iodine density (ID) as well as iodine content (IC) in mg/ml of tissue were derived. These values were compared to the venous phase DECT density (CTD) of the lesions. Values before and after treatment were compared using a paired Student's t test.

RESULTS

Between baseline and follow up, mean CTD and DECT-derived ID both showed a significant reduction (p < 0.005). The relative reduction measured in percent was significantly greater for ID than for CTD (49.8 ± 36,3 % vs. 29.5 ± 20.8 %, p < 0.005). IC was also significantly reduced under antiangiogenic treatment (p < 0.0001).

CONCLUSIONS

Dual energy CT-based quantification of iodine content of mRCC metastases allows for significantly more sensitive and reproducible detection of antiangiogenic treatment effects.

KEY POINTS

• A sign of tumour response to antiangiogenic treatment is reduced tumour perfusion. • DECT allows visualizing iodine uptake, which serves as a marker for vascularization. • More sensitive detection of antiangiogenic treatment effects in mRCC is possible.