Image Quality and Dose Comparison of Single-Energy CT (SECT) and Dual-Energy CT (DECT)

Differentiation of osteoblastic metastases and bone islands on dual-energy computed tomography in patients with untreated lung cancer

OBJECTIVE

To evaluate the diagnostic efficacy of quantitative dual-energy computed tomography (CT) parameters for distinguishing osteoblastic metastases (OBMs) from bone islands (BIs) in untreated lung cancer.

MATERIAL AND METHODS

Dual-energy CT images of 24 patients with OBMs and 56 patients with BIs obtained between January 2019 and December 2021 were retrospectively analyzed. The CT70keV value, calcium(water) density [Dcalcium(water)], and water(calcium) density [Dwater(calcium)] were analyzed. Diagnostic performance was assessed by measuring the area under the curve (AUC), and specificity, sensitivity, and accuracy were determined.

RESULTS

A total of 70 OBMs and 67 BIs were included. The AUC values of CT70keV, Dcalcium(water), and Dwater(calcium) showed no significant differences (0.950 vs. 0.947 vs. 0.929, respectively; P > 0.05). The optimal CT70keV cutoff value was 885.1 HU, with specificity, sensitivity, and accuracy of 81.4 %, 92.5 %, and 86.9 %, respectively. When using Dcalcium(water) < 254.9 mg/cm3 and Dwater(calcium) < 1250.6 mg/cm3, respectively, 119 of 137 lesions showed consistent diagnostic results (true or false). Sub-analysis of these 119 lesions showed specificity of 92.1 %, which was higher than that of CT70keV (P = 0.021). The AUC, sensitivity, and accuracy were 0.974, 92.9 %, and 92.4 %, respectively, which were not significantly different from those of CT70keV (P = 0.230, 0.906, and 0.220, respectively). Among the 18 lesions showing inconsistent diagnoses, Dcalcium(water) diagnosed 11 lesions correctly, and Dwater(calcium) diagnosed the remaining seven lesions correctly.

CONCLUSION

The combination of Dcalcium(water) and Dwater(calcium) demonstrated a promising role in the differentiation of OBMs from BIs in lung cancer patients.

Dual-energy CT in musculoskeletal imaging: technical considerations and clinical applications

Dual-energy CT stands out as a robust and innovative imaging modality, which has shown impressive advancements and increasing applications in musculoskeletal imaging. It allows to obtain detailed images with novel insights that were once the exclusive prerogative of magnetic resonance imaging. Attenuation data obtained by using different energy spectra enable to provide unique information about tissue characterization in addition to the well-established strengths of CT in the evaluation of bony structures. To understand clearly the potential of this imaging modality, radiologists must be aware of the technical complexity of this imaging tool, the different ways to acquire images and the several algorithms that can be applied in daily clinical practice and for research. Concerning musculoskeletal imaging, dual-energy CT has gained more and more space for evaluating crystal arthropathy, bone marrow edema, and soft tissue structures, including tendons and ligaments. This article aims to analyze and discuss the role of dual-energy CT in musculoskeletal imaging, exploring technical aspects, applications and clinical implications and possible perspectives of this technique.

Coronary artery calcium quantification technique using dual energy material decomposition: a simulation study

Coronary artery calcification is a significant predictor of cardiovascular disease, with current detection methods like Agatston scoring having limitations in sensitivity. This study aimed to evaluate the effectiveness of a novel CAC quantification method using dual-energy material decomposition, particularly its ability to detect low-density calcium and microcalcifications. A simulation study was conducted comparing the dual-energy material decomposition technique against the established Agatston scoring method and the newer volume fraction calcium mass technique. Detection accuracy and calcium mass measurement were the primary evaluation metrics. The dual-energy material decomposition technique demonstrated fewer false negatives than both Agatston scoring and volume fraction calcium mass, indicating higher sensitivity. In low-density phantom measurements, material decomposition resulted in only 7.41% false-negative (CAC = 0) measurements compared to 83.95% for Agatston scoring. For high-density phantoms, false negatives were removed (0.0%) compared to 20.99% in Agatston scoring. The dual-energy material decomposition technique presents a more sensitive and reliable method for CAC quantification.

Detection of monosodium urate depositions and atherosclerotic plaques in the cardiovascular system by dual-energy computed tomography

Aim

The study aimed to explore the relationship between urate deposition and surrounding atherosclerotic plaques, and to confirm the contribution of urate deposition to the development of coronary atherosclerosis.

Methods and results

The present study employed Dual-energy CT (DECT) material separation technology through calcium score scan to access the presence of MSU crystal deposition in coronary atherosclerotic plaques in patients with clinically suspected coronary heart diseases undergoing DECT. DECT showed that among 872 patients, 441 had plaques in coronary arteries; the incidence of plaque was 50.6 %. The patients were divided in the atherosclerotic plaque vs. non-plaque groups. There were significant differences in age, sex, blood pressure, blood glucose, serum creatinine, and history of gout and hyperuricemia between the plaque and non-plaque groups (all P < 0.05). Among the patients with coronary plaques, there were 348 patients (78.9 %) with simple atherosclerotic plaque (AP), 8 (1.8 %) with simple urate depositions (UD), and 85 (19.3 %) with urate depositions and atherosclerotic plaques (UDAP). The multivariable analysis showed that urate deposition was independently associated with plaques after adjustment for age, sex, blood pressure, blood glucose, serum creatinine, history of gout, and history of hyperuricemia (OR = 13.69, 95%CI: 7.53-22.95, P = 0.035). UPAP patients had significantly higher coronary calcium scores than AP patients [210.1 (625.2) AU vs 58.2 (182.5) AU, P < 0.001] Urate deposition (16.7 mm3) positively correlated with plaque calcification (73.8 mm³) in UPAP patients (r = 0.325, P < 0.001).

Conclusion

Patients with gout or a history of hyperuricemia were more likely to exhibit UDAP. Urate deposition was independently associated with plaques.

Presentation of Organ Dose and Effective Dose Conversion Factors in Dual-Energy Computed Tomography: A Monte Carlo Simulation Study

Background

The same conversion factors (k-factors) of Single CT (SECT) are applied to estimate the Effective Dose (ED) in Dual Energy Computed Tomography (DECT). However, k-factors for different organs need independently validating for DECT, due to the different conditions in DECT.

Objective

This study aimed to calculate organ dose and k-factors in different imaging protocols (liver, chest, cardiac, and abdomen) for male and female phantoms.

Material and Methods

This Monte Carlo Simulation study used Monte Carlo N-Particle (MCNP) code for modeling a Siemens Somatom Definition Flash dual-source CT scanner. The organ dose, dose length product, and k-factors were calculated for the Medical Internal Radiation Dose (MIRD) of male and female phantoms.

Results

For the male phantom, the k-factors for the liver, chest, cardiac, and abdomen-pelvis imaging protocols are equal to 0.020, 0.012, 0.016, and 0.014 mSv.mGy-1cm-1, respectively. For the female phantom, the corresponding values are equal to 0.026, 0.023, 0.036, and 0.018, respectively. These values for DECT are different from those corresponding values for SECT, especially for the female phantom.

Conclusion

The calculated k-factors for DECT can be used as reference values for the estimation of ED in DECT.

A Comprehensive Evaluation of Health-Related Life Quality Assessment Through Head and Neck, Prostate, Breast, Lung, and Skin Cancer in Adults

Health assessment data assists the well-being and patient care teams' process in drawing up a care and assistance plan and comprehending the requirements of the patient. Comprehensive and precise data about the Quality of Life of cancer patients play a significant part in the development and organization of cancer patient care. Quality of Life has been used to mean a variety of various things, such as health situation, physical function, symptoms, psychosocial modification, well-being, enjoyment of life, and happiness. Chronic diseases such as cancer are among the disorders that severely affect people's health and consequently their Quality of Life. Cancer patients experience a range of symptoms, including pain and various physical and mental conditions that negatively affect their Quality of Life. In this article, we examined cancer and the impact that this disease can have on the Quality of Life of cancer patients. The cancers examined in this article include head and neck, prostate, breast, lung, and skin cancers. We also discussed health assessment and the importance and purpose of studying patients' Quality of Life, especially cancer patients. The various signs and symptoms of the disease that affect the Quality of Life of patients were also reviewed.

Dual Energy CT Physics-A Primer for the Emergency Radiologist

Dual energy CT (DECT) refers to the acquisition of CT images at two energy spectra and can provide information about tissue composition beyond that obtainable by conventional CT. The attenuation of a photon beam varies depends on the atomic number and density of the attenuating material and the energy of the incoming photon beam. This differential attenuation of the beam at varying energy levels forms the basis of DECT imaging and enables separation of materials with different atomic numbers but similar CT attenuation. DECT can be used to detect and quantify materials like iodine, calcium, or uric acid. Several post-processing techniques are available to generate virtual non-contrast images, iodine maps, virtual mono-chromatic images, Mixed or weighted images and material specific images. Although initially the concept of dual energy CT was introduced in 1970, it is only over the past two decades that it has been extensively used in clinical practice owing to advances in CT hardware and post-processing capabilities. There are numerous applications of DECT in Emergency radiology including stroke imaging to differentiate intracranial hemorrhage and contrast staining, diagnosis of pulmonary embolism, characterization of incidentally detected renal and adrenal lesions, to reduce beam and metal hardening artifacts, in identification of uric acid renal stones and in the diagnosis of gout. This review article aims to provide the emergency radiologist with an overview of the physics and basic principles of dual energy CT. In addition, we discuss the types of DECT acquisition and post processing techniques including newer advances such as photon-counting CT followed by a brief discussion on the applications of DECT in Emergency radiology.

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.

Single- and Dual-Source CT Myelography: Comparison of Radiation Exposure and Establishment of Diagnostic Reference Levels

CT myelography (CTM) is a diagnostic technique for the evaluation of various spinal pathologies, and plays an important role in diagnosis of different diseases such as spontaneous intracranial hypotension and postoperative cerebrospinal fluid leaks. The aims of this study were to examine radiation exposure, establish diagnostic reference levels (DRLs) and compare radiation doses of single- and dual-source examinations and different CTM protocols. In this retrospective study, 183 CTMs comprising 155 single-source and 28 dual-source examinations, performed between May 2015 and December 2020, were analyzed. Dose data included 31 whole spine (A), 23 cervical (B), 10 thoracic (C), and 119 lumbar (D) CTMs. Radiation exposure was reported for volume-weighted CT dose index (CTDI_vol) and dose-length product (DLP). Radiation doses for CTDI_vol and DLP were distributed as follows (median, IQR): A: 7.44 mGy (6.01–11.17 mGy)/509.7 mGy·cm (382.4–682.9 mGy·cm), B: 9.31 mGy (7.20–14.64 mGy)/214.5 mGy·cm (153.7–308.2 mGy·cm), C: 6.80 mGy (6.14–8.26 mGy)/365.4 mGy·cm (222.8–432.4 mGy·cm), D: 11.02 mGy (7.97–14.89 mGy)/308.0 mGy·cm (224.7–413.7 mGy·cm). Local DRLs could be depicted as follows (CTDI_vol/DLP): A: 11 mGy/683 mGy·cm, B: 15 mGy/308 mGy·cm, C: 8 mGy/432 mGy·cm, D: 15 mGy/414 mGy·cm. High image quality was achieved for all anatomical regions. Basically, radiation exposure of CTM differs according to anatomical location.

Virtual Monoenergetic CT Imaging via Deep Learning

Conventional single-spectrum computed tomography (CT) reconstructs a spectrally integrated attenuation image and reveals tissues morphology without any information about the elemental composition of the tissues. Dual-energy CT (DECT) acquires two spectrally distinct datasets and reconstructs energy-selective (virtual monoenergetic [VM]) and material-selective (material decomposition) images. However, DECT increases system complexity and radiation dose compared with single-spectrum CT. In this paper, a deep learning approach is presented to produce VM images from single-spectrum CT images. Specifically, a modified residual neural network (ResNet) model is developed to map single-spectrum CT images to VM images at pre-specified energy levels. This network is trained on clinical DECT data and shows excellent convergence behavior and image accuracy compared with VM images produced by DECT. The trained model produces high-quality approximations of VM images with a relative error of less than 2%. This method enables multi-material decomposition into three tissue classes, with accuracy comparable with DECT.

Early prediction of final infarct volume with material decomposition images of dual-energy CT after mechanical thrombectomy

PURPOSE

Evaluation of water material density images (wMDIm) of dual-energy CT (DECT) for earlier prediction of final infarct volume (fiV) in follow-up single-energy CT (SECT) and correlation with clinical outcome.

METHODS

Fifty patients (69 years, ± 12.1, 40-90, 50% female) with middle cerebral artery (MCA) occlusions were included. Early infarct volumes were analyzed in monoenergetic images (MonoIm) and wMDIm at 60 keV and compared with the fiV in SECT 4.9 days (± 4) after thrombectomy. Association between infarct volume and functional outcome was tested by linear regression analysis.

RESULTS

wMDIm shows a prior visible infarct demarcation (60.7 ml, ± 74.9 ml) compared with the MonoIm (37.57 ml, ± 76.7 ml). Linear regression analysis, Bland-Altman plots and Pearson correlation coefficients show a close correlation of infarct volume in wMDIm to the fiV in SECT (r = 0.86; 95% CI 0.76-0.92), compared with MonoIm and SECT (r = 0.81; 95% CI 0.69-0.89). The agreement with SECT is substantially higher in patients with infarct volumes < 70 ml (n = 33; 66%). Coefficients were smaller with r = 0.59 (95% CI 0.31; 0.78) for MonoIm and SECT compared with r = 0.77 (95% CI 0.57; 0.88) for wMDIm and SECT. At admission, the mean NIHSS score and mRS were 17.02 (± 4.7) and 4.9 (± 0.2). mRS ≤ 2 was achieved in 56% at 90 days with a mean mRS of 2.5 (± 0.8) at discharge.

CONCLUSION

Material decomposition allows earlier visibility of the final infarct volume. This promises an earlier evaluation of the dimension and severity of infarction and may lead to faster initiation of secondary stroke prophylaxis.