Conventional Computed Tomography Imaging Research Articles

Thermometry mapping during CT-guided thermal ablations: proof of feasibility and internal validation using spectral CT.

Conventional CT imaging does not provide quantitative information on local thermal changes during percutaneous ablative therapy of cancerous and benign tumors, aside from few qualitative, visual cues. In this study, we have investigated changes in CT signal across a wide range of temperatures and two physical phases for two different tissue mimicking materials, each. 
Approach: A series of experiments were conducted using an anthropomorphic phantom filled with water-based gel and olive oil, respectively. Multiple, clinically used ablation devices were applied to locally cool or heat the phantom material and were arranged in a configuration that produced thermal changes in regions with inconsequential amounts of metal artifact. Eight fiber optic thermal sensors were positioned in the region absent of metal artifact and were used to record local temperatures throughout the experiments. A spectral CT scanner was used to periodically acquire and generate Electron Density weighted images. Average electron density weighted values in 1 mm3 volumes of interest near the temperature sensors were computed and these data were then used to calculate thermal volumetric expansion coefficients for each material and phase. 
Main Results: The experimentally determined expansion coefficients well-matched existing published values and variations with temperature -maximally differing by 5% of the known value. As a proof of concept, a CT-generated temperature map was produced during a heating time point of the water-based gel phantom, demonstrating the capability to map changes in electron density weighted signal to temperature. This study has demonstrated that spectral CT can be used to estimate local temperature changes for different materials and phases across temperature ranges produced by thermal ablations.

Predicting epidermal growth factor receptor mutations in non-small cell lung cancer through dual-layer spectral CT: a prospective study

ObjectiveTo determine whether quantitative parameters of detector-derived dual-layer spectral computed tomography (DLCT) can reliably identify epidermal growth factor receptor (EGFR) mutation status in patients with non-small cell lung cancer (NSCLC).MethodsPatients with NSCLC who underwent arterial phase (AP) and venous phase (VP) DLCT between December 2021 and November 2022 were subdivided into the mutated and wild-type EGFR groups following EGFR mutation testing. Their baseline clinical data, conventional CT images, and spectral images were obtained. Iodine concentration (IC), iodine no water (INW), effective atomic number (Zeff), virtual monoenergetic images, the slope of the spectral attenuation curve (λHU), enhancement degree (ED), arterial enhancement fraction (AEF), and normalized AEF (NAEF) were measured for each lesion.ResultsNinety-two patients (median age, 61 years, interquartile range [51, 67]; 33 men) were evaluated. The univariate analysis indicated that IC, normalized IC (NIC), INW and ED for the AP and VP, as well as Zeff and λHU for the VP were significantly associated with EGFR mutation status (all p < 0.05). INW(VP) showed the best diagnostic performance (AUC, 0.892 [95% confidence interval {CI}: 0.823, 0.960]). However, neither AEF (p = 0.156) nor NAEF (p = 0.567) showed significant differences between the two groups. The multivariate analysis showed that INW(AP) and NIC(VP) were significant predictors of EGFR mutation status, with the latter showing better performance (p = 0.029; AUC, 0.897 [95% CI: 0.816, 0.951] vs. 0.774 [95% CI: 0.675, 0.855]).ConclusionQuantitative parameters of DLCT can help predict EGFR mutation status in patients with NSCLC.Critical relevance statementQuantitative parameters of DLCT, especially NIC(VP), can help predict EGFR mutation status in patients with NSCLC, facilitating appropriate and individualized treatment for them.Key PointsDetermining EGFR mutation status in patients with NSCLC before starting therapy is essential.Quantitative parameters of DLCT can predict EGFR mutation status in NSCLC patients.NIC in venous phase is an important parameter to guide individualized treatment selection for NSCLC patients.Graphical

Detecting Metastatic Patterns of Oligometastatic Breast Cancer: A Comparative Analysis of 18F-FDG PET/CT and Conventional CT Imaging.

Metastasis-directed therapy has the potential to improve progression-free and overall survival in oligometastatic disease (OMD). For breast cancer, however, randomized trials have failed so far to confirm this finding. Because the concept of metastasis-directed therapy in OMD is highly dependent on the accuracy of the imaging modality, we aimed to assess the impact of 18F-FDG PET/CT on the definition of OMD in breast cancer patients. Methods: Eighty patients with a total of 150 18F-FDG PET/CT images (between October 2006 and January 2022) were enrolled in this retrospective study at the Technical University of Munich. The inclusion criteria were OMD, defined as 1-5 distant metastases, at the time of 18F-FDG PET/CT. For the current study, we systemically compared the metastatic pattern on 18F-FDG PET/CT with conventional CT. Results: At the time of 18F-FDG PET/CT, 21.3% of patients (n = 32) had a first-time diagnosis of metastatic disease, 40.7% (n = 61) had a previous history of OMD, and 38% (n = 57) had a previous history of polymetastatic disease. In 45.3% of cases, the imaging modality (18F-FDG PET/CT vs. conventional CT) had an impact on the assessment of whether OMD was present. An identical metastatic pattern was observed in only 32% of cases.18F-FDG PET/CT detected additional metastases in 33.3% of cases, mostly in the nonregional lymph node system. Conclusion: The use of 18F-FDG PET/CT had a substantial impact on the definition of OMD and detection of metastatic pattern in breast cancer. Our results emphasize the importance of establishing a standardized definition for imaging modalities in future trials and clinical practices related to metastasis-directed therapy in breast cancer patients.

Thrombus discrimination with electron density: potential implications for non-contrast computed tomography imaging.

The potential clinical usefulness of electron density (ED) imaging, that can be directly estimated using dual-layer spectral computed tomography (CT), has been poorly investigated. We explored whether ED imaging might improve thrombus identification compared to conventional imaging in vitro. We evaluated mechanical thrombectomy material obtained from patients with acute ischemic stroke (AIS) treated in a tertiary level stroke center and immediately fixed in 10% neutral buffered formalin and stored in polystyrene test tubes. The test tubes were immersed in a bucket of water for evaluation by spectral CT, along with scattered control tubes. All images were obtained using a dual-layer detector CT scanner. Each tube was assessed using multiparametric side-by-side view of conventional CT (120 kVp), low monoenergetic imaging (40 keV), and ED images. Fifty-eight polystyrene tubes were analyzed, comprising 52 tubes with thrombectomy material of at least 1 mm2 size obtained from 52 AIS patients, and six control tubes filled with formalin. ED imaging identified accurately the presence of material in all tubes, whereas 2 (3%) of the tubes containing thrombus were not identified by conventional CT, leading to a very good agreement between observers for the presence of material using conventional CT and ED imaging (kappa =0.84, P<0.001). Using ED imaging, thrombus material showed a mean density of 108.8±2.9 percent ED relative to water (%EDW), water had a mean density of 100.0±0.3 %EDW, and formalin a mean density of 103.5±1.2 %EDW. Compared to conventional imaging and 40 keV monoenergetic, ED imaging had a significantly higher signal-to-noise ratio (conventional 10.4±7.0, vs. 40 keV 11.5±8.4, vs. ED 490.0±304.5, P<0.001) and contrast-to-noise ratio (CNR) (conventional 4.3±4.3, vs. 40 keV 5.7±11.2, vs. ED 37.8±29.1, P<0.001). In this in-vitro study, we demonstrated improved visualization of thrombus with ED imaging compared to conventional imaging and low monoenergetic imaging, with a significant increase in CNR.

Examination of archaeological bronze parts using micro-computed tomography and metallography

Abstract Archeological finds, such as old coins among which some show signs of corrosion, are, in general, unique pieces even though several copies exist of individual types. Subferrati, Roman coins with an iron core and a bronze coating, for instance, could be examined by conventional computed tomography (CT). The CT image allows an easy distinction of corrosion products, metallic iron, and the bronze so that appropriate sections could be selected from the images for metallography. The micro-CT technology even allows examining smaller archaeological objects to get an overview. The resolution of the micro-CT is a function of the object size and lies between 5 and 10 μm. The following metallographic examinations are intended to characterize the microstructure. Apart from these examinations, SEM analyses may also be performed on the sections. Different bronze pieces from cremation and inhumation burials were examined. Micro-CT provides a well recognizable contrast between corrosion products and the metallic bronze. If several similar objects exist, micro-CT examinations allow a decision to be made on which parts are suitable for metallographic analyses and which are not.

Photon-Counting Detector CT Virtual Monoenergetic Images in Cervical Trauma Imaging-Optimization of Dental Metal Artifacts and Image Quality.

The aim of this study was to analyze the extent of dental metal artifacts in virtual monoenergetic (VME) images, as they often compromise image quality by obscuring soft tissue affecting vascular attenuation reducing sensitivity in the detection of dissections. Neck photon-counting CT datasets of 50 patients undergoing contrast-enhanced trauma CT were analyzed. Hyperattenuation and hypoattenuation artifacts, muscle with and without artifacts and vessels with and without artifacts were measured at energy levels from 40 keV to 190 keV. The corrected artifact burden, corrected image noise and artifact index were calculated. We also assessed subjective image quality on a Likert-scale. Our study showed a lower artifact burden and less noise in artifact-affected areas above the energy levels of 70 keV for hyperattenuation artifacts (conventional polychromatic CT images 1123 ± 625 HU vs. 70 keV VME 1089 ± 733 HU, p = 0.125) and above of 80 keV for hypoattenuation artifacts (conventional CT images -1166 ± 779 HU vs. 80 keV VME -1170 ± 851 HU, p = 0.927). Vascular structures were less hampered by metal artifacts than muscles (e.g., corrected artifact burden at 40 keV muscle 158 ± 125 HU vs. vessels -63 ± 158 HU p < 0.001), which was also reflected in the subjective image assessment, which showed better ratings at higher keV values and overall better ratings for vascular structures than for the overall artifact burden. Our research suggests 70 keV might be the best compromise for reducing metal artifacts affecting vascular structures and preventing vascular contrast if solely using VME reconstructions. VME imaging shows only significant effects on the general artifact burden. Vascular structures generally experience fewer metal artifacts than soft tissue due to their greater distance from the teeth, which are a common source of such artifacts.

Image quality and metal artifact reduction in total hip arthroplasty CT: deep learning-based algorithm versus virtual monoenergetic imaging and orthopedic metal artifact reduction

BackgroundTo compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to conventional CT and 130-keV monoenergetic images with and without orthopedic metal artifact reduction (O-MAR).MethodsConventional CT and 130-keV monoenergetic images with and without O-MAR and DL-MAR images of 28 unilateral THA patients were reconstructed. Image quality, metal artifacts, and diagnostic confidence in bone, pelvic organs, and soft tissue adjacent to the prosthesis were jointly scored by two experienced musculoskeletal radiologists. Contrast-to-noise ratios (CNR) between bladder and fat and muscle and fat were measured. Wilcoxon signed-rank tests with Holm-Bonferroni correction were used.ResultsSignificantly higher image quality, higher diagnostic confidence, and less severe metal artifacts were observed on DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001 for all comparisons). Higher image quality, higher diagnostic confidence for bone and soft tissue adjacent to the prosthesis, and less severe metal artifacts were observed on DL-MAR when compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.014). CNRs were higher for DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001). Higher CNRs were observed on DL-MAR images compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.010).ConclusionsDL-MAR showed higher image quality, diagnostic confidence, and superior metal artifact reduction compared to conventional CT images and 130-keV monoenergetic images with and without O-MAR in unilateral THA patients.Relevance statementDL-MAR resulted into improved image quality, stronger reduction of metal artifacts, and improved diagnostic confidence compared to conventional and virtual monoenergetic images with and without metal artifact reduction, bringing DL-based metal artifact reduction closer to clinical application.Key points• Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT.• A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR.• DL-MAR showed best image quality and diagnostic confidence.• Highest contrast-to-noise ratios were observed on the DL-MAR images.Graphical

Detecting bone marrow infiltration in nonosteolytic multiple myeloma through separation of hydroxyapatite via the two-material decomposition technique in spectral computed tomography.

Conventional computed tomography (CT) has low sensitivity for the diagnosis of bone marrow infiltration in nonosteolytic multiple myeloma (NOL-MM). This study aimed to compare the performance of the two-material decomposition technique of spectral CT with the removal of X-ray absorption components of calcium (Ca) versus that of hydroxyapatite (HAP) for diagnosis of NOL-MM. From October 2022 to March 2023, a total of 41 consecutive patients with MM without focal bone lesions undergoing chest spectral CT and thoracic spine magnetic resonance imaging (MRI) in Fujian Medical University Union Hospital were prospectively enrolled; meanwhile, another set of 41 age- and sex-matched healthy consecutive participants were selected as a comparison group. Based on MRI findings, patients with MM were classified with a diffuse infiltration pattern MM (DP-MM) or a normal pattern MM (NP-MM). Regions of interest (ROIs) were manually drawn on vertebrae. CT values of 70-keV images and basic material density within the ROIs were stored. The basic two-material pairs included a Ca-related pair (Ca-X) and an HAP-related pair (HAP-X), with X referring to fat, water, or muscle. Material density values DCa(X), DX(Ca), DHAP(X), and DX(HAP) were each used to diagnose MM, and the area under the receiver operating characteristic curve (AUC) was used to assess diagnostic performance. The 41 patients with NOL-MM included 30 with DP-MM and 11 with NP-MM. CT value, DCa(X), and DHAP(X) were comparable between the NOL-MM, DP-MM, NP-MM, and comparison groups. DX(HAP) was better than DX(Ca) for distinguishing the NOL-MM group from the comparison group {AUC [95% confidence interval (CI)], 0.874 (0.800, 0.949) vs. 0.737 (0.630, 0.844); P=0.02}, the DP-MM group from the comparison group [AUC (95% CI), 0.933 (0.878, 0.989) vs. 0.785 (0.677, 0.894); P=0.01], the NP-MM group from the comparison group [AUC (95% CI), 0.714 (0.540, 0.888) vs. 0.605 (0.429, 0.782); P=0.03], and the DP-MM group from the NP-MM group [AUC (95% CI), 0.809 (0.654, 0.964) vs. 0.736 (0.566, 0.907); P=0.049]. The diagnostic performance of DX(HAP) and DX(Ca) was influenced only by the removed material, while the X material had no influence. The spectral CT two-material decomposition technique with removal of X-ray absorption components of HAP is useful for diagnosis of NOL-MM, irrespective of the paired material.

Synthesis of virtual monoenergetic images from kilovoltage peak images using wavelet loss enhanced CycleGAN for improving radiomics features reproducibility.

Dual-energy computed tomography (CT) can provide a range of image information beyond conventional CT through virtual monoenergetic images (VMIs). The purpose of this study was to investigate the impact of material decomposition in detector-based spectral CT on radiomics features and effectiveness of using deep learning-based image synthesis to improve the reproducibility of radiomics features. In this paper, spectral CT image data from 45 esophageal cancer patients were collected for investigation retrospectively. First, we computed the correlation coefficient of radiomics features between conventional kilovoltage peak (kVp) CT images and VMI. Then, a wavelet loss-enhanced CycleGAN (WLL-CycleGAN) with paired loss terms was developed to synthesize virtual monoenergetic CT images from the corresponding conventional single-energy CT (SECT) images for improving radiomics reproducibility. Finally, the radiomic features in 6 different categories, including gray-level co-occurrence matrix (GLCM), gray-level difference matrix (GLDM), gray-level run-length matrix (GLRLM), gray-level size-zone matrix (GLSZM), neighborhood gray-tone difference matrix (NGTDM), and wavelet, were extracted from the gross tumor volumes from conventional single energy CT, synthetic virtual monoenergetic CT images, and virtual monoenergetic CT images. Comparison between errors in the VMI and synthetic VMI (sVMI) suggested that the performance of our proposed deep learning method improved the radiomic feature accuracy. Material decomposition of dual-layer dual-energy CT (DECT) can substantially influence the reproducibility of the radiomic features, and the degree of impact is feature dependent. The average reduction of radiomics errors for 15 patients in testing sets was 96.9% for first-order, 12.1% for GLCM, 12.9% for GLDM, 15.7% for GLRLM, 50.3% for GLSZM, 53.4% for NGTDM, and 6% for wavelet features. The work revealed that material decomposition has a significant effect on the radiomic feature values. The deep learning-based method reduced the influence of material decomposition in VMIs and might improve the robustness and reproducibility of radiomic features in esophageal cancer. Quantitative results demonstrated that our proposed wavelet loss-enhanced paired CycleGAN outperforms the original CycleGAN.

Diagnostic Value of Dual-Energy CT Virtual Noncalcium for the Assessment of Bone Marrow Edema of Wrist in Patients with Rheumatoid Arthritis

To evaluate the value of dual-energy CT (DECT) virtual noncalcium (VNCa) images in the diagnosis of wrist bone marrow edema (BME) in patients with rheumatoid arthritis (RA). 43 patients with wrist involvement in active RA prospectively underwent DECT and MRI. Functional DECT images reconstruction yielded VNCa images. MRI served as the reference standard for diagnosing BME. BME diagnosis differences between VNCa images and MRI were compared. Differences in CT values between BME and normal bone marrow were assessed. The optimal CT value for detecting BME in VNCa images was determined through ROC curve analysis. The correlation between VNCa images scores and RA disease activity was evaluated. There was a high agreement between VNCa images and MRI in diagnosing BME (Kappa=0.831). VNCa images showed a significant difference in CT values between BME and normal bone marrow (P<0.001). A cut-off value of -54.8 HU yielded a sensitivity, specificity, and accuracy of 90.72%, 94.30%, and 93.33%, respectively, for detecting BME on VNCa images. The area under the ROC curve was 0.937 for distinguishing BME from normal bone marrow. Conventional CT images showed no statistically significant difference (P=0.174) in CT values between BME and normal bone marrow. The VNCa images BME scores were positively correlated with RA disease activity (r=0.399). The DECT VNCa technique demonstrates its potential for diagnosing wrist BME in patients with RA and provides a valuable tool for assessing disease activity in RA. The DECT VNCa technique has the ability to distinguish between BME and normal bone marrow. The VNCa images BME scores were positively correlated with the disease activity in RA.

Quantification of ischemic brain edema after mechanical thrombectomy using dual-energy computed tomography in patients with ischemic stroke

Net water uptake (NWU) is a quantitative imaging biomarker used to assess cerebral edema resulting from ischemia via Computed Tomography (CT)-densitometry. It serves as a strong predictor of clinical outcome. Nevertheless, NWU measurements on follow-up CT scans after mechanical thrombectomy (MT) can be affected by contrast staining. To improve the accuracy of edema estimation, virtual non-contrast images (VNC-I) from dual-energy CT scans (DECT) were compared to conventional polychromatic CT images (CP-I) in this study. We examined NWU measurements derived from VNC-I and CP-I to assess their agreement and predictive value in clinical outcome. 88 consecutive patients who received DECT as follow-up after MT were included. NWU was quantified on CP-I (cNWU) and VNC-I (vNWU). The clinical endpoint was functional independence at discharge. cNWU and vNWU were highly correlated (r = 0.71, p < 0.0001). The median difference between cNWU and vNWU was 8.7% (IQR: 4.5–14.1%), associated with successful vessel recanalization (mTICI2b-3) (ß: 11.6%, 95% CI 2.9–23.0%, p = 0.04), and age (ß: 4.2%, 95% CI 1.3–7.0%, p = 0.005). The diagnostic accuracy to classify outcome between cNWU and vNWU was similar (AUC:0.78 versus 0.77). Although there was an 8.7% median difference, indicating potential edema underestimation on CP-I, it did not have short-term clinical implications.

Multi-instance learning based lung nodule system for assessment of CT quality after small-field-of-view reconstruction

Small-field-of-view reconstruction CT images (sFOV-CT) increase the pixel density across airway structures and reduce partial volume effects. Multi-instance learning (MIL) is proposed as a weakly supervised machine learning method, which can automatically assess the image quality. The aim of this study was to evaluate the disparities between conventional CT (c-CT) and sFOV-CT images using a lung nodule system based on MIL and assessments from radiologists. 112 patients who underwent chest CT were retrospectively enrolled in this study between July 2021 to March 2022. After undergoing c-CT examinations, sFOV-CT images with small-field-of-view were reconstructed. Two radiologists analyzed all c-CT and sFOV-CT images, including features such as location, nodule type, size, CT values, and shape signs. Then, an MIL-based lung nodule system objectively analyzed the c-CT (c-MIL) and sFOV-CT (sFOV-MIL) to explore their differences. The signal-to-noise ratio of lungs (SNR-lung) and contrast-to-noise ratio of nodules (CNR-nodule) were calculated to evaluate the quality of CT images from another perspective. The subjective evaluation by radiologists showed that feature of minimal CT value (p = 0.019) had statistical significance between c-CT and sFOV-CT. However, most features (all with p < 0.05), except for nodule type, location, volume, mean CT value, and vacuole sign (p = 0.056–1.000), had statistical differences between c-MIL and sFOV-MIL by MIL system. The SNR-lung between c-CT and sFOV-CT had no statistical significance, while the CNR-nodule showed statistical difference (p = 0.007), and the CNR of sFOV-CT was higher than that of c-CT. In detecting the difference between c-CT and sFOV-CT, features extracted by the MIL system had more statistical differences than those evaluated by radiologists. The image quality of those two CT images was different, and the CNR-nodule of sFOV-CT was higher than that of c-CT.

Dual-layer spectral detector CT: A noninvasive preoperative tool for predicting histopathological differentiation in pancreatic ductal adenocarcinoma

PurposeTo predict histopathological differentiation grades in patients with pancreatic ductal adenocarcinoma (PDAC) before surgery with quantitative and qualitative variables obtained from dual-layer spectral detector CT (DLCT). MethodsTotally 128 patients with histopathologically confirmed PDAC and preoperative DLCT were retrospectively enrolled and categorized into the low-grade (LG) (well and moderately differentiated, n = 82) and high-grade (HG) (poorly differentiated, n = 46) subgroups. Both conventional and spectral variables for PDAC were measured. The ratio of iodine concentration (IC) values in arterial phase(AP) and venous phase (VP) was defined as iodine enhancement fraction_AP/VP (IEF_AP/VP). Necrosis was visually assessed on both conventional CT images (necrosis_con) and virtual mono-energetic images (VMIs) at 40 keV (necrosis_40keV). Forward stepwise logistic regression method was conducted to perform univariable and multivariable analysis. Receiver operating characteristic (ROC) curves and the DeLong method were used to evaluate and compare the efficiencies of variables in predicting tumor grade. ResultsNecrosis_con (odds ratio [OR] = 2.84, 95% confidence interval [CI]: 1.13–7.13; p < 0.001) was an independent predictor among conventional variables, and necrosis_40keV (OR = 5.82, 95% CI: 1.98–17.11; p = 0.001) and IEF_AP/VP (OR = 1.12, 95% CI:1.07–1.17; p < 0.001) were independent predictors among spectral variables for distinguishing LG PDAC from HG PDAC. IEF_AP/VP (AUC = 0.754, p = 0.016) and combination model (AUC = 0.812, p < 0.001) had better predictive performances than necrosis_con (AUC = 0.580). The combination model yielded the highest sensitivity (72%) and accuracy (79%), while IEF_AP/VP exhibited the highest specificity (89%). ConclusionVariables derived from DLCT have the potential to preoperatively evaluate PDAC tumor grade. Furthermore, spectral variables and their combination exhibited superior predictive performances than conventional CT variables.

Dual-energy computed tomography quality control: Initial experiences with a semi-automatic analysis tool

PurposeA quality control (QC) system for dual-energy CT (DECT) was developed. The scope of the QC system was to monitor both the constancy of the CT images and the software used in calculating the DECT derived maps. Longitudinal analysis was based on a standard imaging protocol, a commercial multi-energy phantom, and a semi-automatic analysis tool. MethodsThe phantom consisted of an elliptical body section with round slots for interchangeable inserts. It was scanned with 90kVp/Sn150kVp, automatic tube current modulation, and 9.6 mGy CTDIvol. From the two conventional CT images, scanner manufacturer’s software was used to provide virtual monoenergetic images at two different energies, effective atomic number (Zeff) maps, and iodine concentration maps. The images were analyzed using an open-source tool allowing user-selected statistics of interest. The means and standard deviations of the phantom background and the iodine, calcium, and water inserts were recorded. The QC tool is available at github.com/tomakela/dectqatool. ResultsThe obtained results were generally highly consistent over time, except for the smaller diameter iodine inserts. A small change inZeff was observed after a DECT software update. The developed QC tool aided the analysis robustness: the segmentations were modifiable when needed, and small rotations or air bubbles in the water insert were easily corrected. ConclusionThe developed QC system provided easy-to-use workflow for constancy measurements. A small deviation due to change in the post-processing was detected. The proposed imaging protocol and analysis steps, and the reported measurement variations can aid in determining action levels for DECT QC.

Bone scintigraphy with SPECT/CT in paediatric patients with neck and back pain in comparison with other imaging modalities: the experience of a tertiary paediatric referral centre.

Retrospective review of the additional clinical value provided by single photon emission computed tomography-computed tomography (SPECT/CT) in children and adolescents with back pain. A total of 207 consecutive paediatric patients (94 males, 113 females, age range 5-17 years, median age 14 years) were reviewed after referral to the spinal surgery clinic of a paediatric teaching hospital between November 2009 and February 2021. All patients had either only whole spine X-rays or whole spine x-rays and MRI, along with bone scan with planar whole-body images and SPECT/CT (with spot views of painful area). X-ray identified the pain generator in 23 of 177 (13.0%) cases. MRI identified the pain generator in 49 of 165 (29.7%) cases. SPECT/CT reported relevant positive findings which identified the pain generator in 107 of 185 (57.8%) cases. SPECT/CT changed patients' management in 72 of 185 (38.9%) cases. SPECT/CT was most effective at identifying the pain generator in cases of facet arthropathy, previous vertebral fracture and patients with previous deformity correction, where the pain generator was identified in 76.5% (13 of 17), 71.4% (5 of 7) and 63.4% (26 of 41) of cases, respectively. CT settings were adjusted to minimise the radiation burden (50 mAs/80kVp under 8 years, 24 mAs/110 kVp over 8 years). The role of SPECT/CT in diagnosing back pain is justified in selected paediatric patients, particularly with diagnostic uncertainty using conventional imaging. The CT component of the SPECT/CT study produced a lower radiation dose than conventional CT imaging, whilst producing bone images of diagnostic quality.

Landmark-based registration of a cochlear model to a human cochlea using conventional CT scans

Cochlear implants can provide an advanced treatment option to restore hearing. In standard pre-implant procedures, many factors are already considered, but it seems that not all underlying factors have been identified yet. One reason is the low quality of the conventional computed tomography images taken before implantation, making it difficult to assess these parameters. A novel method is presented that uses the Pietsch Model, a well-established model of the human cochlea, as well as landmark-based registration to address these challenges. Different landmark numbers and placements are investigated by visually comparing the mean error per landmark and the registrations’ results. The landmarks on the first cochlear turn and the apex are difficult to discern on a low-resolution CT scan. It was possible to achieve a mean error markedly smaller than the image resolution while achieving a good visual fit on a cochlear segment and directly in the conventional computed tomography image. The employed cochlear model adjusts image resolution problems, while the effort of setting landmarks is markedly less than the segmentation of the whole cochlea. As a next step, the specific parameters of the patient could be extracted from the adapted model, which enables a more personalized implantation with a presumably better outcome.

The utility of three-dimensional modeling and printing in pediatric surgical patient and family education: a systematic review

BackgroundThree-dimensional (3D) modeling and printing are increasingly being used in surgical settings. This technology has several applications including pre-operative surgical planning, inter-team communication, and patient education and counseling. The majority of research on 3D technology has focused on adult populations, where it has been found to be a useful tool for educating patients across various surgical specialties. There is a dearth, however, of research on the utility of 3D modeling and printing for patient and family education in pediatric populations. Our objective was to systematically review the current literature on how this modality is being utilized in pediatric surgical settings for patient and family education and counselling.MethodsWe conducted a systematic review in accordance with PRISMA and CASP guidelines. The MEDLINE, CINAHL, Embase, and Web of Science databases were searched from inception to October 21, 2023, with no restrictions on language or geographical location. Citation chaining was used to ensure relevant papers were included. Articles were doubly screened and data was extracted independently by two authors. In the case of disagreement, a third author was consulted. Any articles pertaining to 3D modeling and printing in pediatric surgical settings for patient and family education and counseling were included.ResultsSix articles met inclusion criteria and were used for qualitative analysis. Two involved questionnaires given to parents of children to assess their understanding of relevant anatomy, surgical procedure, and risks after viewing conventional CT images and again after viewing a 3D-printed model. One involved a quasi-experimental study to assess young patients’ pre-operative surgical understanding and anxiety after undergoing conventional teaching as compared to after viewing a 3D storybook. One involved questionnaires given to parents of children in control and study groups to assess the usefulness of 3D printed models compared to conventional CT images in their understanding of relevant anatomy and the surgical procedure. Another study looked at the usefulness of 3D printed models compared to 2D and 3D CT images in providing caregiver understanding during the pre-operative consent process. The last article involved studying the impact of using 3D printing to help patients understand their disease and participate in decision-making processes during surgical consultations. In all six studies, utilizing 3D technology improved transfer of information between surgical team members and their patients and families.ConclusionOur systematic review suggests that 3D modeling and printing is a useful tool for patient and family education and counselling in pediatric surgical populations. Given the very small number of published studies, further research is needed to better define the utility of this technology in pediatric settings.

Improving Visualization of In-stent Lumen Using Prototype Photon-counting Detector Computed Tomography with High-resolution Plaque Kernel

The study aimed to compare the performance of photon-counting detector computed tomography (PCD CT) with high-resolution (HR)-plaque kernel with that of the energy-integrating detector CT (EID CT) in terms of the visualization of the lumen size and the in-stent stenotic portion at different coronary vessel angles. The lumen sizes in PCD CT and EID CT images were 2.13 and 1.80 mm at 0°, 2.20 and 1.77 mm at 45°, and 2.27 mm and 1.67 mm at 90°, respectively. The lumen sizes in PCD CT with HR-plaque kernel were wider than those in EID CT. The mean degree of the in-stent stenotic portion at 50% was 69.7% for PCD CT and 90.4% for EID CT. PCD CT images with HR-plaque kernel enable improved visualization of lumen size and accurate measurements of the in-stent stenotic portion compared to conventional EID CT images regardless of the stent direction.

Technical note: Implementing MRI/CT-based elemental concentration data to Monte Carlo simulation for yielding positron emitters in proton therapy.

The elemental concentration (especially oxygen and carbon) and mass density must be accurately assigned to perform Monte Carlo (MC) simulations for predicting proton-induced nuclear reactions in the human body. We recently proposed an approach to quantify elemental concentrations and mass densities of human soft tissues from water content (WC) data obtained by quantitative magnetic resonance (MR) imaging (which we called "MRWC"). This study presents the first implementation of MRWC-derived elemental concentrations and mass densities as complementary inputs into MC simulations on a virtual head phantom, and demonstrates the simulation of positron emitter production yields in proton therapy. An MC code, PHITS, was used to simulate proton therapy with a monoenergetic 140 MeV beam for a digital head phantom provided by BrainWeb. Three different head images were synthesized as inputs: a conventional CT image, an ideal CT image as a reference, and a WC image coupled with the bone-only CT image for a hybrid approach (MRWC/CT). Thereafter, the performance of the MRWC/CT method was evaluated by comparing its accuracy in predicting the production yields of positron emitters (11C and 15O) with the gold-standard CT-only method. The MRWC/CT method could predict 11C and 15O production yield maps that closely resembled the corresponding reference maps, while the CT-only method failed. The structural similarity index measures between the reference and CT- or MRWC/CT-derived maps were improved from 0.67 (CT-only) to 0.87 (MRWC/CT) for 11C and 0.76 (CT-only) to 0.93 (MRWC/CT) for 15O. Furthermore, applying post-processing normalizations to account for elemental density variations in the production yields of positron emitters facilitated the determination of distal fall-off positions in depth activity profiles. At least in the head area, the MRWC/CT method demonstrated potential for more precise predictions of proton-induced positron emitter distributions via MC simulations than that of the CT-only method.

Low-dose versus conventional CT urography using dual-source CT with different time-current product values and the same tube voltage: image quality and diagnostic performance in various diagnoses.

To compare the image quality and diagnostic performance of low-dose CT urography to that of concurrently acquired conventional CT using dual-source CT. This retrospective study included 357 consecutive CT urograms performed by third-generation dual-source CT in a single institution between April 2020 and August 2021. Two-phase CT images (unenhanced phase, excretory phase with split bolus) were obtained with two different tube current-time products (280 mAs for the conventional-dose protocol and 70 mAs for the low-dose protocol) and the same tube voltage (90 kVp) for the two X-ray tubes. Iterative reconstruction was applied for both protocols. Two radiologists independently performed quantitative and qualitative image quality analysis and made diagnoses. The correlation between the noise level or the effective radiation dose and the patients' body weight was evaluated. Significantly higher noise levels resulting in a significantly lower liver signal-to-noise ratio and contrast-to-noise ratio were noted in low-dose images compared to conventional images (P < .001). Qualitative analysis by both radiologists showed significantly lower image quality in low-dose CT than in conventional CT images (P < .001). Patient's body weight was positively correlated with noise and effective radiation dose (P < .001). Diagnostic performance for various diseases, including urolithiasis, inflammation, and mass, was not different between the two protocols. Despite inferior image quality, low-dose CT urography with 70 mAs and 90 kVp and iterative reconstruction demonstrated diagnostic performance equivalent to that of conventional CT for identifying various diseases of the urinary tract. Low-dose CT (25% radiation dose) with low tube current demonstrated diagnostic performance comparable to that of conventional CT for a variety of urinary tract diseases.