Conventional CT Research Articles

Evaluation of Splenic Involvement in Lymphomas Using Extracellular Volume Fraction Computed Tomography.

To evaluate whether the extracellular volume (ECV) fraction can be used to identify splenic involvement in lymphoma patients and whether it can be used to improve the diagnostic performance of conventional computed tomography (CT) in the diagnosis of splenic diffuse involvement. Consecutive patients with newly diagnosed lymphoma who underwent abdomen contrast-enhanced CT and 18F-fluorodeoxyglucose positron emission tomography/CT for diagnosis or staging were retrospectively enrolled. Patients were divided into the splenic involvement (diffuse or focal) and noninvolvement groups. The ECV fraction was obtained in all patients. In the splenic diffuse involvement and noninvolvement groups, spleen vertical length (SVL) >13 cm and obliteration of normal heterogeneous enhancement of the spleen in arterial phase were recorded. Receiver operating characteristic curve was used to analyze the diagnostic performance, and area under the curve (AUC) comparison was performed using the Delong test. A total of 135 patients were included, 56 patients with splenic involvement (36 diffuse and 20 focal) and 79 patients with noninvolvement. Splenic involvement can be identified via the ECV fraction (AUC = 0.839). In distinguishing splenic diffuse involvement, the AUC of the ECV fraction was superior to the SVL >13 cm (0.788 vs 0.627, P = 0.007) and obliteration of normal heterogeneous enhancement of the spleen (0.788 vs 0.596, P = 0.001). The combination of ECV fraction and SVL >13 cm demonstrated superior diagnostic performance, with an AUC of 0.830, surpassing all other parameters. The ECV fraction can be used to identify splenic involvement. The ECV fraction combined with SVL >13 cm is recommended for the prediction of splenic diffuse involvement.

Diagnostic Value of Contrast-Enhanced Dual-Energy Computed Tomography in the Pancreatic Parenchymal and Delayed Phases for Pancreatic Cancer.

Background/Objectives: The usefulness of dual-energy computed tomography (DECT) for low absorption in the parenchymal phase and contrast effects in the delayed phase for pancreatic cancer is not clear. Therefore, the diagnostic capability of low-KeV images obtained using DECT for pancreatic cancer in the pancreatic parenchymal and delayed phases was evaluated quantitatively and qualitatively. Methods: Twenty-five patients with pancreatic cancer who underwent contrast-enhanced DECT were included. A total of 50 and 70 KeV CT images, classified as low-keV and conventional CT-equivalent images, were produced, respectively. The tumor-to-pancreas contrast (Hounsfield units [HU]) in the pancreatic parenchymal and delayed phases was calculated by subtracting the CT value of the pancreatic tumor from that of normal parenchyma. Results: The median tumor-to-pancreas contrast on 50 KeV CT in the pancreatic parenchymal phase (133 HU) was higher than that on conventional CT (68 HU) (p < 0.001). The median tumor-to-pancreas contrast in the delayed phase was -28 HU for 50 KeV CT and -9 HU for conventional CT (p = 0.545). For tumors < 20 mm, the tumor-to-pancreas contrast of 50 KeV CT (-39 HU) had a significantly clearer contrast effect than that of conventional CT (-16.5 HU), even in the delayed phase (p = 0.034). Conclusions: These 50 KeV CT images may clarify the low-absorption areas of pancreatic cancer in the pancreatic parenchymal phase. A good contrast effect was observed in small pancreatic cancers on 50 KeV delayed-phase images, suggesting that DECT is useful for the visualization of early pancreatic cancer with a small tumor diameter.

Comparison of diagnostic accuracy of radiomics parameter maps and standard reconstruction for the detection of liver lesions in computed tomography.

The liver is a frequent location of metastatic disease in various malignant tumor entities. Computed tomography (CT) is the most frequently employed modality for initial diagnosis. However, liver metastases may only be delineated vaguely on CT. Calculating radiomics features in feature maps can unravel textures not visible to the human eye on a standard CT reconstruction (SCTR). This study aimed to investigate the comparative diagnostic accuracy of radiomics feature maps and SCTR for liver metastases. Forty-seven patients with hepatic metastatic colorectal cancer were retrospectively enrolled. Whole-liver maps of original radiomics features were generated. A representative feature was selected for each feature class based on the visualization of example lesions from five patients. These maps and the conventional CT image data were viewed and evaluated by four readers in terms of liver parenchyma, number of lesions, visual contrast of lesions and diagnostic confidence. T-tests and chi²-tests were performed with a significance cut off of p<0.05 to compare the feature maps with SCRT, and the data were visualized as boxplots. Regarding the number of lesions detected, SCTR showed superior performance compared to radiomics maps. However, the feature map for firstorder RootMeanSquared was ranked superior in terms of very high visual contrast in 57.4% of cases, compared to 41.0% in standard reconstructions (p < 0.001). All other radiomics maps ranked significantly lower in visual contrast when compared to SCTR. For diagnostic confidence, firstorder RootMeanSquared reached very high ratings in 47.9% of cases, compared to 62.8% for SCTR (p < 0.001). The conventional CT images showed superior results in all categories for the other features investigated. The application of firstorder RootMeanSquared feature maps may help visualize faintly demarcated liver lesions by increasing visual contrast. However, reading of SCTR remains necessary for diagnostic confidence.

Prospective observational non-randomized trial protocol for surgical planner 3D image processing & reconstruction for locally advanced colon cancer

IntroductionColon cancer presents significant surgical challenges that necessitate the development of precise strategies. Standardization with complete mesocolic excision (CME) is common, but some cases require extended resections. This study investigates the use of 3D Image Processing and Reconstruction (3D-IPR) to improve diagnostic accuracy in locally advanced colon cancer (LACC) with suspected infiltration and achieve R0 surgery.MethodsSingle-center, prospective, observational, comparative, non-randomized study.•Participants: Patients aged > 18 years undergoing LACC surgery, as indicated by CT scans, confirmed via colonoscopy. Exclusion criteria include neoadjuvant therapy, suspected carcinomatosis on CT, and unresectable tumors.•Interventions: 3D-IPR models are used for surgical planning, providing detailed tumor and surrounding structure metrics. Surgical procedures are guided by CT scans and intraoperative findings, categorized by surgical margins as R0, R1, or R2.•Objective: The primary goal is to evaluate 3D-IPR’s utility in achieving R0 resection in LACC with suspected infiltration. Secondary objectives include assessing preoperative surgical strategy, comparing CT reports, detecting adenopathy, and identifying vascularization and anatomical variants.• Outcome: The main outcome is the diagnostic accuracy of 3D-IPR in determining tumor infiltration of neighboring structures compared to conventional CT scans, using definitive pathological reports as the gold standard.Results•Recruitment and Number Analyzed: The study aims to recruit about 20 patients annually over two years, focusing on preoperative 3D-IPR analysis and subsequent surgical procedures.•Outcome Parameters: These include loco-regional and distant recurrence rates, peritoneal carcinomatosis, disease-free and overall survival, and mortality due to oncologic progression.•Harms: No additional risks from CT scans, as they are mandatory for staging colon tumors. 3D-IPR is derived from these CT scans.DiscussionIf successful, this study could provide an objective tool for precise tumor extension delimitation, aiding decision-making for radiologists, surgeons, and multidisciplinary teams. Enhanced staging through 3D-IPR may influence therapeutic strategies, reduce postsurgical complications, and improve the quality of life of patients with LACC.Trial registrationTrial is registered at ISRCTN registry as ISRCTN81005215. Protocol version I (Date 29/06/2023).

Imaging performance of a LaBr3:Ce scintillation detector for photon counting x-ray computed tomography: Simulation study.

Photon counting detectors (PCDs) for x-ray computed tomography (CT) are the future of CT imaging. At present, semiconductor-based PCDs such as cadmium telluride (CdTe), cadmium zinc telluride, and silicon have been either used or investigated for clinical PCD CT. Unfortunately, all of them have the same major challenges, namely high cost and limited spectral signal-to-noise ratio (SNR). Recent studies showed that some high-quality scintillators, such as lanthanum bromide doped with cerium (LaBr3:Ce), are less expensive and almost as fast as CdTe. The objective of this study is to assess the performance of a LaBr3:Ce PCD for clinical x-ray CT. We performed Monte Carlo simulations and compared the performance of 3 mm thick LaBr3:Ce and 2 mm thick CdTe for PCD CT with x-rays at 120 kVp and 20-1000mA. The two PCDs were operated with either a threshold-subtract (TS) counting scheme or a direct energy binning (DB) counting scheme. The performance was assessed in terms of the accuracy of registered spectra, counting capability, and count-rate-dependent spectral imaging-task performance, for conventional CT imaging, water-bone material decomposition, and K-edge imaging with tungsten as the K-edge material. The performance for these imaging-tasks was quantified by nCRLB, that is, the Cramér-Rao lower bound on the variance of basis line-integral estimation, normalized by the corresponding value of CdTe at 20mA. The spectrum recorded by CdTe was distorted significantly due to charge sharing, whereas the spectra recorded by LaBr3:Ce better matched the incident spectrum. The dead time, estimated by fitting a paralyzable detector model to the count-rate curves, was 20.7, 15.0, 37.2, and 13.0ns for CdTe with TS, CdTe with DB, LaBr3:Ce with TS, and LaBr3:Ce with DB, respectively. Conventional CT imaging showed an adverse effect of reduced geometrical efficiency due to optical reflectors in LaBr3:Ce PCD. The nCRLBs (a lower value indicates a better SNR) for CdTe with TS, CdTe with DB, LaBr3:Ce with TS, LaBr3:Ce with DB, and the ideal PCD, were 1.00±0.01, 1.00±0.01, 1.18±0.02, 1.18±0.02, and 0.79±0.01, respectively, at 20mA. The nCRLBs for water-bone material decomposition, in the same order, were 1.00±0.02, 1.00±0.02, 0.85±0.02, 0.85±0.02, and 0.24±0.02, respectively, at 20mA; and 0.98±0.02, 0.98±0.02, 1.09±0.02, 0.83±0.02, and 0.24±0.02, respectively, at 1000mA. Finally, the nCRLBs for K-edge imaging, the most demanding task among the five, were 1.00±0.02, 1.00±0.02, 0.55±0.02, 0.55±0.02, and 0.13±0.02, respectively, at 20mA; and 2.45±0.02, 2.29±0.02, 3.12±0.02, 2.11±0.02, and 0.13±0.02, respectively, at 1,000mA. The Monte Carlo simulations showed that, compared to CdTe with either TS or DB, LaBr3:Ce with DB provided more accurate spectra, comparable or better counting capability, and superior spectral imaging-task performances, that is, water-bone material decomposition and K-edge imaging. CdTe had a better performance than LaBr3:Ce for the conventional CT imaging task due to its higher geometrical efficiency. LaBr3:Ce PCD with DB scheme may be an excellent alternative option for CdTe PCD.

Myelographic Techniques for the Localization of CSF-Venous Fistulas: Updates in 2024.

CSF-venous fistulas (CVFs) are a common cause of spontaneous intracranial hypotension. Despite their relatively frequent occurrence, they can be exceedingly difficult to detect on imaging. Since the initial description of CVFs in 2014, the recognition and diagnosis of this type of CSF leak has continually increased. As a result of multi-institutional efforts, a wide spectrum of imaging modalities and specialized techniques for CVF detection is now available. It is important for radiologists to be familiar with the multitude of available techniques, because each has unique advantages and drawbacks. In this article, we review the spectrum of imaging modalities available for the detection of CVFs, explain the advantages and disadvantages of each, provide typical imaging examples, and discuss provocative maneuvers that may improve the conspicuity of CVFs. Discussed modalities include conventional CT myelography, dynamic myelography, digital subtraction myelography, conebeam CT myelography, decubitus CT myelography by using conventional energy-integrating detector scanners, decubitus photon counting CT myelography, and intrathecal gadolinium MR myelography. Additional topics to be discussed include optimal patient positioning, respiratory techniques, and intrathecal pressure augmentation.

Photon-counting detector computed tomography in cardiac imaging.

Photon-counting detector computed tomography (PCD-CT) has emerged as arevolutionary technology in CT imaging. PCD-CT offers significant advancements over conventional energy-integrating detector CT, including increased spatial resolution, artefact reduction and inherent spectral imaging capabilities. In cardiac imaging, PCD-CT can offer amore accurate assessment of coronary artery disease, plaque characterisation and the in-stent lumen. Additionally, it might improve the visualisation of myocardial fibrosis through qualitative late enhancement imaging and quantitative extracellular volume measurements. The use of PCD-CT in cardiac imaging holds significant potential, positioning itself as avaluable modality that could serve as aone-stop-shop by integrating both angiography and tissue characterisation into asingle examination. Despite its potential, large-scale clinical trials, standardisation of protocols and cost-effectiveness considerations are required for its broader integration into clinical practice. This narrative review provides an overview of the current literature on PCD-CT regarding the possibilities and limitations of cardiac imaging.

Opportunistic Screening for Low Bone Mineral Density in Routine Computed Tomography Scans: A Brazilian Validation Study

Introduction/background: Osteoporotic fractures are a major health concern worldwide due to high mortality rates, deterioration in quality of life, and elevated healthcare costs related to hospital treatment. However, most patients who sustain an osteoporotic fracture have never been formally screened for osteoporosis. Opportunistic screening of osteoporosis through conventional computed tomography (CT) scans performed for unrelated reasons could help identify patients with low bone mass. There are currently no studies validating the opportunistic screening of low bone mass through CT in South America. The aim of our study is to assess whether conventional CT scans could be used for the opportunistic screening of osteopenia and osteoporosis in Brazilian patients.Methodology: Patients who underwent unenhanced CT and dual-energy X-ray absorptiometry (DXA) scans within a six-month interval were assessed retrospectively. Mean CT attenuation was measured in the first lumbar vertebra (L1) in axial, coronal, and sagittal planes and compared to their respective DXA T-scores; vertebral fractures were assessed in the sagittal plane. Potential thresholds suggestive of low bone mass density (BMD) were established using receiver operating characteristics analysis.Results: 491 patients were included (93.2 % female; mean age of 64.1 ± 9.8 years; mean interval of 63.5 days between scans). Mean L1 CT attenuation was significantly lower in osteopenic and osteoporotic patients in all CT planes (p < 0.001). Positive linear correlations were found between DXA T-scores and the average L1 attenuations in all CT planes (p < 0.001). An average L1 attenuation equal or below 100 Hounsfield Units (HU) in the sagittal plane identified low BMD (osteopenia or osteoporosis) with a specificity of 96.3 % and a positive predictive value of 96 %. In contrast, an average L1 attenuation above 180 HU demonstrated a sensitivity of 97.6 % and a negative predictive value of 94.9 % for detecting osteoporosis. Patients with L1 sagittal attenuation at or below 100 HU exhibited a significantly higher prevalence of vertebral fractures (prevalence ratio: 8.67; p < 0.001). An online calculator based on the results of this study is freely available at www.osteotc.com.br.Conclusions: Routine CT scans can identify probable low bone density (osteopenia or osteoporosis) in Brazilian patients without additional costs or radiation exposure. Opportunistic CT screening does not substitute formal bone mineral density assessment; instead, it assists in identifying patients who may benefit from it.

Value of spectral parameters in the differential diagnosis of benign and malignant breast nodules in non-enhanced chest CT.

Dual-layer spectral computed tomography (DSCT) is capable of acquiring both conventional and spectral images during one routine scan, and is widely used for the quantitative and qualitative analyses of substances, differential diagnosis, and disease staging. However, limited research has been conducted on its performance in the differential diagnosis of benign and malignant breast nodules using non-enhanced scans. This study aimed to assess the diagnostic performance of multiple quantitative parameters derived from non-enhanced DSCT in differentiating benign from malignant breast nodules. This retrospective cross-sectional study examined a total of 121 breast nodules from 114 patients (malignant group: n=68; benign group: n=53) identified during chest physical examination or routine admission for the treatment of breast diseases at The First Affiliated Hospital of Soochow University from March 2023 to December 2023. All the patients underwent DSCT scanning and pathological diagnosis. The DSCT quantitative parameters, including the effective atomic number (Zeff), computed tomography (CT) attenuation values at 40-70 keV, and the slope of the spectral Hounsfield unit curve (λHU), in non-enhanced images were measured. The λHU was calculated as follows: λHU = CT70 keV - CT40 keV/30 HU. Additionally, typical radiological features were analyzed. A DSCT parameter diagnostic model and a conventional CT diagnostic model were assessed using receiver operating characteristic (ROC) curves. The Delong test was used to assess and compare the diagnostic performance of each model. The DSCT parameters, including the Zeff (P<0.001), λHU (P<0.001), and CT attenuation values at 40 keV (P<0.001) and 50 keV (P=0.001), as well as the presence of the lobular sign (P<0.001) and spicule sign (P<0.001), exhibited statistically significant differences between the benign and malignant groups. The logistic regression analysis revealed that the Zeff [odds ratio (OR): 9.22; 95% confidence interval (CI): 2.11-40.35; P=0.003], λHU (OR: 0.64; 95% CI: 0.52-0.79; P<0.001), 40 keV CT attenuation value (OR: 8.69; 95% CI: 3.28-23.06; P<0.001), 50 keV CT attenuation value (OR: 0.01; 95% CI: 0.001-0.07; P<0.001), and lobular sign (OR: 3.95; 95% CI: 1.52-10.31; P=0.005) were independent predictors of malignancy. Compared to the benign group, the malignant group had a higher likelihood of presenting with the lobular sign and higher Zeff values but lower λHU values. The ROC curve indicated that the Zeff had the highest diagnostic efficacy [area under the curve (AUC) of the ROC =0.792, 95% CI: 0.71-0.87]. Further, the DSCT parameter diagnostic model had improved diagnostic efficacy with an AUC of 0.899 (95% CI: 0.84-0.96), which was higher than the AUC of the conventional CT diagnostic model (AUC =0.796, 95% CI: 0.72-0.87). The Delong test revealed a statistically significant difference between these two models (P=0.04). DSCT parameters derived from non-enhanced DSCT images, such as the Zeff value and λHU, can be used to differentiate benign and malignant breast nodules, and the differential diagnosis efficacy of the DSCT parameters is higher than that of conventional CT parameters.

Dual energy computed tomography in assessment of bone marrow edema in pathologies of the appendicular skeleton

BackgroundBone marrow edema cannot be detected on the conventional computed tomography scan. MRI has excellent diagnostic performance in detecting bone marrow edema but multiple difficulties in the emergency setting makes performing MRI logistically challenging. The aim of the study was to assess dual energy computed tomography accuracy for bone marrow edema in pathologies of the appendicular skeleton. This was based on color-coded maps and quantitative analysis of Hounsfield unit (HU) in subtraction images, compared with MRI. Materials and methodsProspective observational study was performed by including 60 patients who underwent Dual energy CT (DECT) and MRI. Statistical analysis was performed by calculating p-value and ROC curve analysis. The derived cut off value was used to identify bone marrow edema and diagnostic accuracy, sensitivity, specificity, negative predictive value and positive predictive value of DECT was calculated using MRI as gold standard. A further sub-analysis between the traumatic and non-traumatic groups was done. ResultsBone marrow edema on Color coded virtual non-calcium (VNCa) images and Mean HU of bone marrow edematous site was calculated. Attenuation difference between edematous bone marrow and rest of the bone were correlated with MRI, (p-value 0.0001). The sensitivity, specificity, negative predictive, positive predictive value, and diagnostic accuracy were 91.1, 93.3, 97.6, 77.8 and 91.67 % respectively. ConclusionOur results confirmed that Dual energy CT has high overall sensitivity, specificity and diagnostic accuracy in depicting bone marrow edema when compared to MRI, in various etiologies of the appendicular skeleton. This will lead to reduced missed cases by early detection of bone marrow edema secondary to fractures that are not identifiable in conventional CT. Marrow edema in DECT can be used as an indicator for disease activity and progression in conditions such as transient osteoporosis, tumour, arthritis, avascular necrosis and various other etiologies, generally missed in conventional radiography.

AAPM Task Group Report 299: Quality control in multi-energy computed tomography.

Multi-energy computed tomography (MECT) offers the opportunity for advanced visualization, detection, and quantification of select elements (e.g., iodine) or materials (e.g., fat) beyond the capability of standard single-energy computed tomography (CT). However, the use of MECT requires careful consideration as substantially different hardware and software approaches have been used by manufacturers, including different sets of user-selected or hidden parameters that affect the performance and radiation dose of MECT. Another important consideration when designing MECT protocols is appreciation of the specific tasks being performed; for instance, differentiating between two different materials or quantifying a specific element. For a given task, it is imperative to consider both the radiation dose and task-specific image quality requirements. Development of a quality control (QC) program is essential to ensure the accuracy and reproducibility of these MECT applications. Although standard QC procedures have been well established for conventional single-energy CT, the substantial differences between single-energy CT and MECT in terms of system implementations, imaging protocols, and clinical tasks warrant QC tests specific to MECT. This task group was therefore charged with developing a systematic QC program designed to meet the needs of MECT applications. In this report, we review the various MECT approaches that are commercially available, including information about hardware implementation, MECT image types, image reconstruction, and postprocessing techniques that are unique to MECT. We address the requirements for MECT phantoms, review representative commercial MECT phantoms, and offer guidance regarding homemade MECT phantoms. We discuss the development of MECT protocols, which must be designed carefully with proper consideration of MECT technology, imaging task, and radiation dose. We then outline specific recommended QC tests in terms of general image quality, radiation dose, differentiation and quantification tasks, and diagnostic and therapeutic applications.

Thoracic MRI in pleural infection – a feasibility study from patients’ and radiographers’ perspectives

BackgroundPleural infections present significant clinical challenges, particularly in elderly or immunosuppressed patients, leading to prolonged hospital stay, high morbidity and high mortality. While CT and X-ray are standard imaging modalities, MRI's potential remain unexplored due to historical limitations in scan duration and patient discomfort. Advances in MRI technology, however, may enable its broader use in thoracic imaging. The study aimed to explore the feasibility of thoracic MRI from the radiographers’ and patients’ perspectives. MethodsA prospective feasibility study was conducted involving thirteen patients with pleural infections who underwent thoracic MRI as an add-on within 48 hours of the conventional contrast-enhanced chest CT. Feasibility was assessed on technical success, and scan duration. Patients and radiographers experiences were evaluated through questionnaires and qualitative comments. ResultsTechnical success was high as all thirteen patients completed the scans. The mean in-room time was 30.7±5.5 minutes and the mean scan time was 23±5.4 minutes. Radiographers reported the MRI scans as feasible with few patients requiring breaks or assistance. Most patients found the MRI experience manageable though two reported difficulties with breath-hold instructions. No patients were challenged by lying in supine position and no patients felt very anxious. No significant movement- or breathing artefacts were identified on MRI. ConclusionThoracic MRI is feasible with high technical success, acceptable scan time, and good patient experience in patients with pleural infections offering potential as a radiation-free imaging modality. Furthermore, compared to CT, the use of MRI showed potential advantages in identifying pleural effusion septations.

Proton dose calculation on cone-beam computed tomography using unsupervised 3D deep learning networks

Background and PurposePoor image quality of cone-beam computed tomography (CBCT) images can hinder proton dose calculation to assess the influence of anatomy changes. The aim of this study was to evaluate image quality and proton dose calculation accuracy of synthetic CTs generated from CBCT using unsupervised 3D deep-learning networks. Materials and methodsA total of 102 head-and-neck cancer patients were used to train (N=82) and test (N=20) i) a cycle-consistent generative adversarial network, ii) a contrastive unpaired translation, and iii) a fusion of the two (CycleCUT). For patients in the test set, a repeat CT was deformably registered to a same-day CBCT to create a ground-truth CT for comparison. The proton plan was re-calculated on the ground-truth CT and synthetic CTs. The image quality of the synthetic CTs was evaluated using peak signal-to-noise ratio, structural similarity index measure, mean error, and mean absolute error (MAE). Proton dose calculation accuracy was assessed through 3D gamma analysis and dose-volume-histogram parameters. ResultsAll synthetic CTs accurately preserved the CBCT anatomy (verified by visual inspection) while improving the image quality. The CycleCUT network had slightly improved image quality compared to the other networks (MAE in body: 53 Hounsfield units (HU) vs. 54/55 HU). All networks had similar proton dose calculation accuracy with gamma passing rate above 97%. ConclusionsAll three evaluated networks generated synthetic CT images with dose distributions comparable to those of conventional fan-beam CT. The synthetic CT generation was fast, making all networks feasible for adaptive proton therapy.

Dual-energy CT quantitative parameters to evaluate occult peritoneal metastasis in advanced gastric cancer preoperatively.

To explore whether dual-energy CT (DECT) quantitative parameters could provide analytic value for the diagnosis of patients with occult peritoneal metastasis (OPM) in advanced gastric cancer preoperatively. This retrospective study included 219 patients with advanced gastric cancer and DECT scans. The patient's clinical data and DECT related iodine concentration (IC) parameters and effective atomic number (Zeff) were collated and analyzed among noun-peritoneal metastasis (NPM), OPM and radiologically peritoneal metastasis (RPM) groups. The predictive performance of the DECT parameters was compared with that of the conventional CT features and clinical characteristics through evaluating area under curve of the precision-recall (AUC-PR), F1 score, balanced accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Borrmann IV type diagnosed on CT and serum tumor indicator CA125 index were statistically different between the NPM and OPM groups. DECT parameters included IC, normalized IC (NIC), and Zeff of PM group were lower than the NPM group. The DECT predictive nomogram combined three independent DECT parameters produced a better diagnostic performance than the conventional CT feature Borrmann IV type and serum CA125 index in AUC-PR with 0.884 vs 0.368 vs 0.189, but similar to the combined indicator which was based on the DECT parameters, the conventional CT feature, and serum CA125 index in AUC-PR with 0.884 vs 0.918. The lower quantitative NIC, IC ratio, and Zeff on DECT was associated with peritoneal metastasis in advanced gastric cancer and was promising to identify patients with OPM noninvasively.

Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks.

The standard method for identifying active Brown Adipose Tissue (BAT) is [18F]-Fluorodeoxyglucose ([18F]-FDG) PET/CT imaging, which is costly and exposes patients to radiation, making it impractical for population studies. These issues can be addressed with computational methods that predict [18F]-FDG uptake by BAT from CT; earlier population studies pave the way for developing such methods by showing some correlation between the Hounsfield Unit (HU) of BAT in CT and the corresponding [18F]-FDG uptake in PET. In this study, we propose training convolutional neural networks (CNNs) to predict [18F]-FDG uptake by BAT from unenhanced CT scans in the restricted regions that are likely to contain BAT. Using the Attention U-Net architecture, we perform experiments on datasets from four different cohorts, the largest study to date. We segment BAT regions using predicted [18F]-FDG uptake values, achieving 23% to 40% better accuracy than conventional CT thresholding. Additionally, BAT volumes computed from the segmentations distinguish the subjects with and without active BAT with an AUC of 0.8, compared to 0.6 for CT thresholding. These findings suggest CNNs can facilitate large-scale imaging studies more efficiently and cost-effectively using only CT.

Identification of Bipolar Disorder and Schizophrenia Based on Brain CT and Deep Learning Methods.

With the increasing prevalence of mental illness, accurate clinical diagnosis of mental illness is crucial. Compared with MRI, CT has the advantages of wide application, low price, short scanning time, and high patient cooperation. This study aims to construct a deep learning (DL) model based on CT images to make identification of bipolar disorder (BD) and schizophrenia (SZ). A total of 506 patients (BD = 227, SZ = 279) and 179 healthy controls (HC) was collected from January 2022 to May 2023 at two hospitals, and divided into an internal training set and an internal validation set according to a ratio of 4:1. An additional 65 patients (BD = 35, SZ = 30) and 40 HC were recruited from different hospitals, and served as an external test set. All subjects accepted the conventional brain CT examination. The DenseMD model for identify BD and SZ using multiple instance learning was developed and compared with other classical DL models. The results showed that DenseMD performed excellently with an accuracy of 0.745 in the internal validation set, whereas the accuracy of the ResNet-18, ResNeXt-50, and DenseNet-121model was 0.672, 0.664, and 0.679, respectively. For the external test set, DenseMD again outperformed other models with an accuracy of 0.724; however, the accuracy of the ResNet-18, ResNeXt-50, and DenseNet-121model was 0.657, 0.638, and 0.676, respectively. Therefore, the potential of DL models for identification of BD and SZ based on brain CT images was established, and identification ability of the DenseMD model was better than other classical DL models.

Diagnosis of newly developed multiple myeloma without bone disease detectable on conventional computed tomography (CT) scan by using dual-energy CT

ObjectiveTo evaluate the diagnostic utility of fat (hydroxyapatite) density [DFat (HAP)] on dual-energy computed tomography (DECT) for identifying clinical diagnosed multiple myeloma without bone disease (MNBD) that is not visible on conventional CT scans. Material and MethodsIn this age-gender-examination sites matched case control prospective study, Chest and/or abdominal images on Revolution CT of MNBDs and control subjects were consecutive enrolled in a 1:2 ratio from October 2022 to November 2023. Multiple myeloma was clinical diagnosed according to criteria of the International Myeloma Working Group. Regions of interest (ROIs) were drawn separately for all thoracolumbar vertebrae in the scanning range by two radiologists. Additionally, a radiologist specializing in musculoskeletal imaging supervised the process. DFat (HAP) was extracted from each ROI. The spine was divided into upper thoracic (UPT), middle and lower thoracic (MLT), thoracolumbar (TL), and middle and lower lumbar (MLL) vertebrae. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of DFat (HAP) in diagnosing multiple myeloma, and the sensitivity, specificity, and accuracy under the optimal cut-off were determined by Youden index (sensitivity + specificity −1). ResultsA total of 32 and MNBD patients and 64 control patients were included. The total number of ROIs outlined included MNBD group (n = 493) and control group (n = 986). For all vertebrae, DFat(HAP) got average performance in the diagnosis of MNBD (AUC = 0.733, p < 0.001) with a cut-off value of 958 (mg/cm3); the sensitivity, specificity, and accuracy were 58.8 %, 77.8 %, and 71.7 %, respectively. Regarding segment analysis, the diagnostic performance was good for all (AUC, 0.803–0.837; p < 0.001) but the UPT segment (AUC = 0.692, p = 0.002). The optimal diagnostic cut-off values for the MLT, TL, and MLL vertebrae were 955 mg/cm3, 947 mg/cm3, and 947 mg/cm3, respectively; the sensitivity, specificity, and accuracy were 80.0 %-87.5 %, 71.9 %-82.6 %, and 77.1 %-81.6 %, respectively. ConclusionDECT was effective for detecting MNBD, and better diagnostic results can be obtained by grouping different spine segments.

Simultaneous iodine and barium imaging with photon-counting CT

Photon-counting computed tomography (PCCT) could potentially offer significant improvements in image quality over conventional CT. This study leverages PCCT technology to achieve simultaneous multi-contrast imaging of barium (Z=56) and iodine (Z=53), addressing the limitations of conventional CT in differentiating materials with similar atomic numbers. Using a bench-top PCCT system with a cadmium zinc telluride (CZT) detector, experiments were conducted with various phantom setups and 1-5\% contrast agent concentrations and in a biological sample. Energy thresholds were adjusted to the K-edge absorption energies of barium (37.4 keV) and iodine (33.2 keV) to capture multi-energy CT images. K-edge decomposition was performed with K-edge subtraction and principal component analysis (PCA) techniques, demonstrating clear differentiation and accurate quantification of contrast agents in phantom combinations and the biological sample. The PCCT system successfully differentiated and quantified barium and iodine, with high correlations ($R^2 \approx 1$) between true and reconstructed concentrations. PCA outperformed K-edge subtraction by providing a superior capability to differentiate barium and iodine, particularly when calcium was present in the scanned object. These findings highlight the potential of PCCT for reliable, detailed imaging in clinical and research applications, particularly for contrast agents with close atomic numbers.

Sorafenib maintenance after allogeneic stem cell transplantation in patients with FLT3+ AML receiving midostaurin during induction and consolidation: a retrospective analysis.

Acute myeloid leukemia (AML) relapse is the main cause of death after allogeneic stem cell transplant (allo-SCT). In AML FLT3+, it was shown that Sorafenib used as maintenance therapy after allo-SCT, significantly reduces the risk of relapse and death. We analyzed 29 adult patients with FLT3m AML and underwent allogeneic stem cell transplant from 2019 to 2023. All patients received midostaurin plus conventional CT during induction and consolidation. After transplantation, Sorafenib maintenance was administered in all patients independently from MRD status at transplantation. Sorafenib maintenance was applied in 18 patients out 29 patients (62%). Median time to start sorafenib was 100 days (range 37-225) and median duration of treatment was 775 days (range 140-1064). For the whole population (n=29), 2-year OS, LFS, and CIR was 76%, 68% and 28%, respectively. The median time to relapse was 137 days (range 49-246). For patients treated with sorafenib (n=18), the 2-year OS, LFS, and CIR were 94%, 84% and 11%, respectively. For the whole population, the 100-day NRM was 0% and 1-year NRM was 3%. Death was caused by transplant-associated thrombotic microangiopathy in 1 patient. For patients who were administered with Sorafenib, the 1-y NRM was 5%. Death was caused by transplant associated transplant-associated thrombotic microangiopathy. This retrospective study suggests that sorafenib maintenance seem to be effective even in patients pre-treated with midostaurin.

Photon-counting CT for forensic death investigations-a glance into the future of virtual autopsy.

This article explores the potential of photon-counting computed tomography (CT) in forensic medicine for a range of forensic applications. Photon-counting CT surpasses conventional CT in several key areas. It boasts superior spatial and contrast resolution, enhanced image quality at low x-ray energies, and spectral imaging capabilities that enable more precise material differentiation. These advantages translate to superior visualization of bone structures, foreign bodies, and soft tissues in postmortem examinations. The article discusses the technical principles of photon-counting CT detectors and highlights its potential applications in forensic imaging, including high-resolution virtual autopsies, pediatric forensic CT, trauma analysis, and bone density measurements. Furthermore, advancements in vascular imaging and soft tissue contrast promise to propel CT-based death investigations to an even more prominent role. The article concludes by emphasizing the immense potential of this new technology in forensic medicine and anthropology.