Accuracy of Combined Computed Tomography Colonography and Dual Energy Iiodine Map Imaging for Detecting Colorectal masses using High-pitch Dual-source CT

Evaluation of Radiation Dose Effect on Lung Function Using Iodine Maps Derived From Dual-Energy Computed Tomography

PURPOSE

There is interest in using dual-energy computed tomography (DECT) to evaluate organ function before and after radiation therapy (RT). The purpose of this study (trial identifier: NCT04863027) is to assess longitudinal changes in lung perfusion using iodine maps derived from DECT in patients with lung cancer treated with conventional or stereotactic RT.

METHODS AND MATERIALS

For 48 prospectively enrolled patients with lung cancer, a contrast-enhanced DECT using a dual-source CT simulator was acquired pretreatment and at 6 and 12 months posttreatment. Pulmonary functions tests (PFT) were obtained at baseline and at 6 and 12 months posttreatment. Iodine maps were extracted from the DECT images using a previously described 2-material decomposition framework. Longitudinal iodine maps were normalized using a reference region defined as all voxels with perfusion in the top 10% outside of the 5 Gy isodose volume. Normalized functional responses (NFR) were calculated for 3 dose ranges: <5, 5 to 20, and >20 Gy. Mixed model analysis was used to assess the correlation between dose metrics and NFR. Pearson correlation was used to assess if NFRs were correlated with PFT changes.

RESULTS

Out of the 48 patients, 21 (44%) were treated with stereotactic body RT and 27 (56%) were treated with conventionally fractionated intensity-modulated RT. Thirty-one out of these 48 patients were ultimately included in data analysis. It was found that NFR is linearly correlated with dose (P < .001) for both groups. The number of months elapsed post-RT was also found to correlate with NFR (P = .029), although this correlation was not observed for the stereotactic body RT subgroup. The NFR was not found to correlate with PFT changes.

CONCLUSIONS

DECT-derived iodine maps are a promising method for detailed anatomic evaluation of radiation effect on lung function, including potentially subclinical changes.

Canadian Association of Radiologists Practice Guidelines for Computed Tomography Colonography

Colon cancer is the third most common malignancy in Canada. Computed tomography colonography (CTC) provides a creditable and validated option for colon screening and assessment of known pathology in patients for whom conventional colonoscopy is contraindicated or where patients self-select to use imaging as their primary modality for initial colonic assessment. This updated guideline aims to provide a toolkit for both experienced imagers (and technologists) and for those considering launching this examination in their practice. There is guidance for reporting, optimal exam preparation, tips for problem solving to attain high quality examinations in challenging scenarios as well as suggestions for ongoing maintenance of competence. We also provide insight into the role of artificial intelligence and the utility of CTC in tumour staging of colorectal cancer. The appendices provide more detailed guidance into bowel preparation and reporting templates as well as useful information on polyp stratification and management strategies. Reading this guideline should equip the reader with the knowledge base to perform colonography but also provide an unbiased overview of its role in colon screening compared with other screening options.

Dual Energy CT in Oncology: Benefits for Both Patients and Radiologists From an Emerging Quantitative and Functional Diagnostic Technique

Dual-energy CT (DECT) imaging makes it possible to identify the characteristics of materials that cannot be recognized with conventional single-energy CT (SECT). In the postprocessing study phase, virtual monochromatic images and virtual-non-contrast (VNC) images, also permits reduction of dose exposure by eliminating the precontrast acquisition scan. Moreover, in virtual monochromatic images, the iodine contrast increases when the energy level decreases resulting in better visualization of hypervascular lesions and in a better tissue contrast between hypovascular lesions and the surrounding parenchyma; thus, allowing for reduction of required iodinate contrast material, especially important in patients with renal impairment. All these advantages are particularly important in oncology, providing the possibility of overcoming many SECT imaging limits and making CT examinations safer and more feasible in critical patients. This review explores the basis of DECT imaging and its utility in routine oncologic clinical practice, with particular attention to the benefits of this technique for both the patients and the radiologists.

Impact of the automatic tube current modulation (ATCM) system on virtual monoenergetic image quality for dual-source CT: A phantom study

PURPOSE

To assess the impact of the automatic tube current modulation (ATCM) on virtual monoenergetic images (VMIs) quality in dual-source CT(DSCT).

MATERIALS AND METHODS

Acquisitions were performed on DSCT using the Mercury phantom. The acquisition parameters for an abdomen-pelvic examination with single-energy CT(SECT) and dual-energy CT(DECT) imaging were used. Acquisitions were performed for each imaging mode using fixed mAs and ATCM. The mAs value was set to obtain a volume CT dose index of 11 mGy in fixed mAs acquisitions. This value was used as the reference mAs in ATCM acquisitions. The noise power spectrum and task-based transfer function at 40,50,60 and 70 keV levels were computed on VMIs and SECT images. The detectability index (d') was calculated for a lesion with an iodine concentration of 10 mg/mL.

RESULTS

The noise magnitude on VMIs was higher with the ATCM system than with fixed mAs for all energy levels and section diameters of 21,26 and 31 cm. The noise texture and spatial resolution were similar between the fixed mAs and ATCM acquisitions for both imaging modes. The d' values were lower for all energy levels with ATCM than with fixed mAs acquisitions for 21 and 26 cm diameters by -39.82 ± 9.32%, similar at 31 cm diameter -4.13 ± 0.24% and higher at 36 cm diameter 10.40 ± 6.69%. It was higher on VMIs at all energy levels compared to SECT images.

CONCLUSIONS

The ATCM system could be used with DECT imaging to optimize patient exposure without changing the noise texture and spatial resolution of VMIs compared to fixed mAs and SECT.

Comparison of image quality of two versions of deep-learning image reconstruction algorithm on a rapid kV-switching CT: a phantom study

BACKGROUND

To assess the impact of the new version of a deep learning (DL) spectral reconstruction on image quality of virtual monoenergetic images (VMIs) for contrast-enhanced abdominal computed tomography in the rapid kV-switching platform.

METHODS

Two phantoms were scanned with a rapid kV-switching CT using abdomen-pelvic CT examination parameters at dose of 12.6 mGy. Images were reconstructed using two versions of DL spectral reconstruction algorithms (DLSR V1 and V2) for three reconstruction levels. The noise power spectrum (NSP) and task-based transfer function at 50% (TTF₅₀) were computed at 40/50/60/70 keV. A detectability index (d') was calculated for enhanced lesions at low iodine concentrations: 2, 1, and 0.5 mg/mL.

RESULTS

The noise magnitude was significantly lower with DLSR V2 compared to DLSR V1 for energy levels between 40 and 60 keV by -36.5% ± 1.4% (mean ± standard deviation) for the standard level. The average NPS frequencies increased significantly with DLSR V2 by 23.7% ± 4.2% for the standard level. The highest difference in TTF₅₀ was observed at the mild level with a significant increase of 61.7% ± 11.8% over 40-60 keV energy with DLSR V2. The d' values were significantly higher for DLSR V2 versus DLSR V1.

CONCLUSIONS

The DLSR V2 improves image quality and detectability of low iodine concentrations in VMIs compared to DLSR V1. This suggests a great potential of DLSR V2 to reduce iodined contrast doses.

Detection methods of synchronous colorectal lesions in proximal colon for patients with obstructive colorectal cancer: a literature review

INTRODUCTION

Colorectal cancer holds a high morbidity and mortality rate. As a common method for colorectal cancer detection, colonoscopy has difficulty in passing through the malignant stenosis in patients with obstructive colorectal cancer, which results in incomplete detection and missed diagnosis. The missed synchronous lesions increase the risk of metachronous cancer. Therefore, detecting proximal synchronous lesions in patients with obstructive colorectal cancer should be appreciated before operation.

AREA COVERED

This review evaluates related literature, aiming at providing clinicians with more ideas and attention for detecting proximal synchronous lesions in patients with obstructive colorectal cancer.

EXPERT OPINION

In patients with obstructive colorectal cancer, missed diagnosis of lesions proximal to the obstruction may lead to metachronous colorectal cancer. Except for preoperative colonoscopy which is difficult to pass through malignant stenosis, other methods that can evaluate proximal colon segment are critical. This article introduced several preoperative, intraoperative and postoperative measures for synchronous lesions detection. The choice of methods should base on patients' conditions, aiming at a high diagnostic yield and low risk. Early detection and resection of synchronous lesions in the proximal section of malignant obstruction are expected to minimize the risk of metachronous colorectal cancer and even effect follow-up treatment strategy, which deserves the attention of clinicians.

Application of dual-layer spectral detector computed tomography to evaluate the expression of Ki-67 in colorectal cancer

BACKGROUND

Compared with traditional computed tomography (CT), dual-layer spectral detector CT (SDCT) shows significant improvement in imaging soft tissues of the digestive tract. This work aimed to explore the application of SDCT to evaluate the expression of the molecular marker Ki-67 in colorectal cancer.

METHODS

We retrospectively analyzed the imaging data of the SDCT (IQon Spectral CT; Philips Healthcare) of 45 patients with colorectal cancer in our centre. We used Spearman's test for the imaging parameters (reconstruction of 40, 70, and 100 keV virtual monoenergetic images [VMIs] and the slope of the Hounsfield unit attenuation plot [VMI Slope] based on venous phase CT images, the arterial phase iodine concentration [AP-IC] and venous phase iodine concentration [VP-IC], and the effective atomic number [Z effect]) and correlation analysis for the Ki-67 index. Multivariate logistic regression was used to eliminate confounding factors. We evaluated the expression level of Ki-67 and drew the receiver operating characteristic curve.

RESULTS

The 40-keV VMI, VMI Slope, and AP-IC were found to better reflect the Ki-67 index in patients with colorectal cancer with statistical significance. The 40-keV VMI (r = -0.612, p < 0.001) and VMI Slope (r = -0.523, p < 0.001) were negatively correlated with the Ki-67 index, and AP-IC (r = 0.378, p = 0.010) was positively correlated with the Ki-67 index. The other indexes (p > 0.05) were not statistically significant. The SDCT parameters demonstrated good performance, with area under curves of 0.785 for 40-keV VMI and 0.752 for AP-IC.

CONCLUSION

The SDCT parameters 40-keV VMI and AP-IC can be used for preliminary evaluation of the Ki-67 index in colorectal cancer.

Dual-energy CT: minimal essentials for radiologists

Dual-energy CT, the object is scanned at two different energies, makes it possible to identify the characteristics of materials that cannot be evaluated on conventional single-energy CT images. This imaging method can be used to perform material decomposition based on differences in the material-attenuation coefficients at different energies. Dual-energy analyses can be classified as image data-based- and raw data-based analysis. The beam-hardening effect is lower with raw data-based analysis, resulting in more accurate dual-energy analysis. On virtual monochromatic images, the iodine contrast increases as the energy level decreases; this improves visualization of contrast-enhanced lesions. Also, the application of material decomposition, such as iodine- and edema images, increases the detectability of lesions due to diseases encountered in daily clinical practice. In this review, the minimal essentials of dual-energy CT scanning are presented and its usefulness in daily clinical practice is discussed.

Efficiency of dual-energy computed tomography enterography in the diagnosis of Crohn's disease

Background

This retrospective study aimed to investigate the usefulness of the optimized kiloelectron volt (keV) for virtual monoenergetic imaging (VMI) combined with iodine map in dual-energy computed tomography enterography (DECTE) in the diagnosis of Crohn’s disease (CD).

Methods

Seventy-two patients (mean age: 41.89 ± 17.28 years) with negative computed tomography enterography (CTE) were enrolled for investigating the optimized VMI keV in DECTE by comparing subjective and objective parameters of VMIs that were reconstructed from 40 to 90 keV. Moreover, 68 patients (38.27 ± 15.10 years; 35 normal and 33 CD) were included for evaluating the diagnostic efficacy of DECTE iodine map at the optimized VMI energy level and routine CTE for CD and active CD. Statistical analysis for all data was conducted.

Results

Objective and subjective imaging evaluations showed the best results at 60 keV for VMIs. The CT values of the normal group, active subgroup, and CD group during the small intestinal phase at routine 120 kVp or 60 keV VMI had significant differences. The diagnostic efficacy of an iodine map was the best when NIC = 4% or fat value = 45.8% for CD, whereas NIC < 0.35 or the fat value < 0.38 for active CD. The combined routine CTE and optimized VMI improved the diagnostic efficacy (P < 0.001).

Conclusions

VMI at 60 keV provided the best imaging quality on DECTE. NIC and fat value provided important basis for active CD evaluation. Routine CTE combined with VMI at 60 keV improved the diagnostic efficiency for CD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-021-00716-y.

Multi-label Learning for the Diagnosis of Cancer and Identification of Novel Biomarkers with High-throughput Omics

Background:

The advancement of bioinformatics and machine learning has facilitated the diagnosis of cancer and the discovery of omics-based biomarkers.

Objective:

Our study employed a novel data-driven approach to classifying the normal samples and different types of gastrointestinal cancer samples, to find potential biomarkers for effective diagnosis and prognosis assessment of gastrointestinal cancer patients.

Methods:

Different feature selection methods were used, and the diagnostic performance of the proposed biosignatures was benchmarked using support vector machine (SVM) and random forest (RF) models.

Results:

All models showed satisfactory performance in which Multilabel-RF appeared to be the best. The accuracy of the Multilabel-RF based model was 83.12%, with precision, recall, F1, and Hamming- Loss of 79.70%, 68.31%, 0.7357 and 0.1688, respectively. Moreover, proposed biomarker signatures were highly associated with multifaceted hallmarks in cancer. Functional enrichment analysis and impact of the biomarker candidates in the prognosis of the patients were also examined.

Conclusion:

We successfully introduced a solid workflow based on multi-label learning with High- Throughput Omics for diagnosis of cancer and identification of novel biomarkers. Novel transcriptome biosignatures that may improve the diagnostic accuracy in gastrointestinal cancer are introduced for further validations in various clinical settings.

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

Dual-energy computed tomography (DECT) can estimate tissue vascularity and perfusion via iodine quantification. The aim of this systematic review was to outline current and emerging clinical applications of iodine quantification within the gastrointestinal tract using DECT. The search was conducted with three databases: EMBASE, Pubmed and The Cochrane Library. This identified 449 studies after duplicate removal. From a total of 570 selected studies, 30 studies were enrolled for the systematic review. The studies were categorized into four main topics: gastric tumors (12 studies), colorectal tumors (8 studies), Crohn’s disease (4 studies) and miscellaneous applications (6 studies). Findings included a significant difference in iodine concentration (IC) measurements in perigastric fat between T1–3 vs. T4 stage gastric cancer, poorly and well differentiated gastric and colorectal cancer, responders vs. non-responders following chemo- or chemoradiotherapy treatment among cancer patients, and a positive correlation between IC and Crohn’s disease activity. In conclusion, iodine quantification with DECT may be used preoperatively in cancer imaging as well as for monitoring treatment response. Future studies are warranted to evaluate the capabilities and limitations of DECT in splanchnic flow.

Stepwise analysis of potential accuracy-influencing factors of iodine quantification on a fast kVp-switching second-generation dual-energy CT: from 3D-printed phantom to a simple solution in clinical routine use

Background

Measurement of iodine concentration from dual-energy or spectral computed tomography (CT) provides useful diagnostic information especially in patients suffering from malignant tumors of various origins.

Purpose

The purpose of this study was to systematically investigate the accuracy of the measurement of iodine concentration, focusing on potential influencing factors and assessing its suitability for routine clinical use.

Material and Methods

First, a 3D-printed cylindrical phantom was used to assess reliability of dual-energy CT-based iodine concentration measurement. Second, a semi-anthropomorphic phantom was used to evaluate the potential impact of positional variation of the target volume as typically seen in clinical scans. Finally, a reference vial was placed on the body surface of 38 patients undergoing abdominal dual-energy CT to analyze correlations between applied doses and patient diameters.

Results

The position of the target volume within the cylindrical phantom and the applied dose level significantly influenced the magnitude of measured iodine concentrations ( P < 0.001). We also found a significant difference in accuracy depending on target volume position in the semi-anthropomorphic phantom ( P = 0.028). In patient scans, we observed an error of 19.6 ± 5.6% in iodine concentration measurements of a reference and significant, moderate to strong, negative correlations between measured iodine concentration, maximum patient diameter, and applied dose (maximum sagittal diameter: r = −0.455, P = 0.004; maximum coronal diameter: r=−0.517, P = 0.001; CTDIvol: r = −0.385, P = 0.017)

Conclusion

Dual-energy CT-based iodine concentration measurement should be interpreted with caution. In clinical examinations, placement of a reference vial could be a potential solution to relativize errors.

High-Throughput Omics and Statistical Learning Integration for the Discovery and Validation of Novel Diagnostic Signatures in Colorectal Cancer

The advancement of bioinformatics and machine learning has facilitated the discovery and validation of omics-based biomarkers. This study employed a novel approach combining multi-platform transcriptomics and cutting-edge algorithms to introduce novel signatures for accurate diagnosis of colorectal cancer (CRC). Different random forests (RF)-based feature selection methods including the area under the curve (AUC)-RF, Boruta, and Vita were used and the diagnostic performance of the proposed biosignatures was benchmarked using RF, logistic regression, naïve Bayes, and k-nearest neighbors models. All models showed satisfactory performance in which RF appeared to be the best. For instance, regarding the RF model, the following were observed: mean accuracy 0.998 (standard deviation (SD) < 0.003), mean specificity 0.999 (SD < 0.003), and mean sensitivity 0.998 (SD < 0.004). Moreover, proposed biomarker signatures were highly associated with multifaceted hallmarks in cancer. Some biomarkers were found to be enriched in epithelial cell signaling in Helicobacter pylori infection and inflammatory processes. The overexpression of TGFBI and S100A2 was associated with poor disease-free survival while the down-regulation of NR5A2, SLC4A4, and CD177 was linked to worse overall survival of the patients. In conclusion, novel transcriptome signatures to improve the diagnostic accuracy in CRC are introduced for further validations in various clinical settings.