Gastrointestinal Applications of Iodine Quantification Using Dual-Energy CT: A Systematic Review

Xu, Jack Junchi; Taudorf, Mikkel; Ulriksen, Peter; Achiam, Michael Patrick; Resch, Timothy; Nielsen, Michael Bachmann; Lönn, Lars; Hansen, Kristoffer Lindskov

doi:10.3390/diagnostics10100814

Cited by 14 publications

(14 citation statements)

References 78 publications

(125 reference statements)

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“…More importantly, our study demonstrated iodine-uptake derived radiomics provided more powerful value to predict PM than the conventional one. DECT is a candidate modality to apply in the gastric tumor due to its insight into materials decomposition (29). Our previous researches have introduced the role of DECT combined with PET/CT in dynamically monitoring the process of peritoneal metastasis for GC in vitro (35).…”

Section: Discussionmentioning

confidence: 99%

“…For iodine concentration images, iodine quantitation was standardized in an in-house software (iodine standardization, Syngo via). The purpose of iodine standardization was to reduce the influence of technical or physiological differences resulting from variational cardiac output and phase time when loading iodine within tissues (29). A circular ROI inside the abdominal aorta was independently outlined for individuals on the portalvenous phase and delayed phase from the IU images, omitting calcified plaque secondary to atherosclerosis.…”

Section: Standardization For Iodine Concentrationmentioning

confidence: 99%

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

Chen

Yao

et al. 2021

Front. Oncol.

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

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Section: Discussionmentioning

confidence: 99%

Section: Standardization For Iodine Concentrationmentioning

confidence: 99%

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

Chen

Yao

et al. 2021

Front. Oncol.

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“…Moreover, the IC value of the non-response group was significantly lower than that of the response group, which may indicate that the relatively low blood supply of the tumor before chemotherapy has some difficulties in the targeted organ transportation of chemotherapy drugs, leading to a lower sensitivity of chemotherapy than that of the tumor with relatively rich blood supply before chemotherapy. Although NIC has been proven to be a relatively stable indicators in tumor staging and detection of HER2 status (53,54), its application and benefits are not entirely clear (55). Previous study revealed that NIC cannot serve as an independent predictive factor for lymph node metastasis in GC (51).…”

Section: Evaluation Of Clinical-radiomics Nomogram Performancementioning

confidence: 99%

Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT Radiomics: A Pilot Study

et al. 2021

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ObjectiveTo build and assess a pre-treatment dual-energy CT-based clinical-radiomics nomogram for the individualized prediction of clinical response to systemic chemotherapy in advanced gastric cancer (AGC).MethodsA total of 69 pathologically confirmed AGC patients who underwent dual-energy CT before systemic chemotherapy were enrolled from two centers in this retrospective study. Treatment response was determined with follow-up CT according to the RECIST standard. Quantitative radiomics metrics of the primary lesion were extracted from three sets of monochromatic images (40, 70, and 100 keV) at venous phase. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used to select the most relevant radiomics features. Multivariable logistic regression was performed to establish a clinical model, three monochromatic radiomics models, and a combined multi-energy model. ROC analysis and DeLong test were used to evaluate and compare the predictive performance among models. A clinical-radiomics nomogram was developed; moreover, its discrimination, calibration, and clinical usefulness were assessed.ResultAmong the included patients, 24 responded to the systemic chemotherapy. Clinical stage and the iodine concentration (IC) of the tumor were significant clinical predictors of chemotherapy response (all p < 0.05). The multi-energy radiomics model showed a higher predictive capability (AUC = 0.914) than two monochromatic radiomics models and the clinical model (AUC: 40 keV = 0.747, 70 keV = 0.793, clinical = 0.775); however, the predictive accuracy of the 100-keV model (AUC: 0.881) was not statistically different (p = 0.221). The clinical-radiomics nomogram integrating the multi-energy radiomics signature with IC value and clinical stage showed good calibration and discrimination with an AUC of 0.934. Decision curve analysis proved the clinical usefulness of the nomogram and multi-energy radiomics model.ConclusionThe pre-treatment DECT-based clinical-radiomics nomogram showed good performance in predicting clinical response to systemic chemotherapy in AGC, which may contribute to clinical decision-making and improving patient survival.

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“…As opposed to conventional CT where only a single energy level is used for imaging, Dual Energy CT (DECT) uses the attenuation measurements acquired at different energy spectra to differentiate and quantify material composition with the use of known changes in attenuation between the two spectra. In DECT, iodine can be separated and, with reconstruction algorithms, quantified as the iodine concentration, which may be used for assessment of tissue perfusion, tumor differentiation, and treatment response [ 9 ].…”

Section: Computed Tomography (Ct)mentioning

confidence: 99%

“…In this special edition both case series, original research, and reviews are presented. The topics cover various vascular geometries using ultrasound, CT, MRI, and angiography [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

New Trends in Vascular Imaging

Hansen

Carlsen

2021

Diagnostics

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Gastrointestinal Applications of Iodine Quantification Using Dual-Energy CT: A Systematic Review

Cited by 14 publications

References 78 publications

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

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

Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT Radiomics: A Pilot Study

New Trends in Vascular Imaging

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