COVID-19 Computed tomography patterns in renal replacement therapy patients / Padrões de tomografia computadorizada da COVID-19 em pacientes em terapia renal substitutiva

ABSTRACT Introduction: Lung diseases are common in patients with end stage kidney disease (ESKD), making differential diagnosis with COVID-19 a challenge. This study describes pulmonary chest tomography (CT) findings in hospitalized ESKD patients on renal replacement therapy (RRT) with clinical suspicion of COVID-19. Methods: ESKD individuals referred to emergency department older than 18 years with clinical suspicion of COVID-19 were recruited. Epidemiological baseline clinical information was extracted from electronic health records. Pulmonary CT was classified as typical, indeterminate, atypical or negative. We then compared the CT findings of positive and negative COVID-19 patients. Results: We recruited 109 patients (62.3% COVID-19-positive) between March and December 2020, mean age 60 ± 12.5 years, 43% female. The most common etiology of ESKD was diabetes. Median time on dialysis was 36 months, interquartile range = 12-84. The most common pulmonary lesion on CT was ground glass opacities. Typical CT pattern was more common in COVID-19 patients (40 (61%) vs 0 (0%) in non-COVID-19 patients, p < 0.001). Sensitivity was 60.61% (40/66) and specificity was 100% (40/40). Positive predictive value and negative predictive value were 100% and 62.3%, respectively. Atypical CT pattern was more frequent in COVID-19-negative patients (9 (14%) vs 24 (56%) in COVID-19-positive, p < 0.001), while the indeterminate pattern was similar in both groups (13 (20%) vs 6 (14%), p = 0.606), and negative pattern was more common in COVID-19-negative patients (4 (6%) vs 12 (28%), p = 0.002). Conclusions: In hospitalized ESKD patients on RRT, atypical chest CT pattern cannot adequately rule out the diagnosis of COVID-19.

RESUMO Introdução: Doenças pulmonares são comuns em pacientes com doença renal em estágio terminal (DRET), dificultando o diagnóstico diferencial com COVID-19. Este estudo descreve achados de tomografia computadorizada de tórax (TC) em pacientes com DRET em terapia renal substitutiva (TRS) hospitalizados com suspeita de COVID-19. Métodos: Indivíduos maiores de 18 anos com DRET, encaminhados ao pronto-socorro com suspeita de COVID-19 foram incluídos. Dados clínicos e epidemiológicos foram extraídos de registros eletrônicos de saúde. A TC foi classificada como típica, indeterminada, atípica, negativa. Comparamos achados tomográficos de pacientes com COVID-19 positivos e negativos. Resultados: Recrutamos 109 pacientes (62,3% COVID-19-positivos) entre março e dezembro de 2020, idade média de 60 ± 12,5 anos, 43% mulheres. A etiologia mais comum da DRET foi diabetes. Tempo médio em diálise foi 36 meses, intervalo interquartil = 12-84. A lesão pulmonar mais comum foi opacidades em vidro fosco. O padrão típico de TC foi mais comum em pacientes com COVID-19 (40 (61%) vs. 0 (0%) em pacientes sem COVID-19, p < 0,001). Sensibilidade 60,61% (40/66), especificidade 100% (40/40). Valores preditivos positivos e negativos foram 100% e 62,3%, respectivamente. Padrão atípico de TC foi mais frequente em pacientes COVID-19-negativos (9 (14%) vs. 24 (56%) em COVID-19-positivos, p < 0,001), enquanto padrão indeterminado foi semelhante em ambos os grupos (13 (20%) vs. 6 (14%), p = 0,606), e padrão negativo foi mais comum em pacientes COVID-19-negativos (4 (6%) vs. 12 (28%), p = 0,002). Conclusões: Em pacientes com DRET em TRS hospitalizados, um padrão atípico de TC de tórax não pode excluir adequadamente o diagnóstico de COVID-19.

Diagnostic Performance of FAPI PET/CT vs. 18F-FDG PET/CT in Evaluation of Liver Tumors: A Systematic Review and Meta-analysis.

Objectives: Primary liver tumors constitute one of the most common tumors. These are aggressive tumors with poor survival. Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT), most commonly used functional imaging, shows limited tracer retention and poor tumor to background ratios (TBR). Novel 68Ga-fibroblast-activation-protein inhibitor (FAPI) PET/CT has shown better tracer uptake and detection efficacy in liver tumors. However, most of the available literature is limited to single center studies with limited number of patients. So, we tried to review and analyze the head-to-head comparison of 18F-FDG PET/CT and 68Ga-FAPI PET/CT in evaluation of liver tumors. Methods: Literature available on head to head comparison of diagnostic accuracy of 18F-FDG PET/CT and 68Ga-FAPI PET/CT was searched in databases like PubMed, SCOPUS, EMBASE and Google Scholar for published original studies till April 2023. The relevant studies were selected and assessed using the Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies-2 checklist. A random-effect model was used for calculating pooled sensitivity and specificity. They were represented with 95% confidence intervals (95% CI) and demonstrated in Forest plots. I-square statistic was used to assess heterogeneity in the studies. Results: Pooled sensitivity and specificity of FAPI PET/CT and 18F-FDG PET/CT for detection of primary liver tumors was 94.3% (95% CI: 90.6-96.8%); 89.3% (95% CI: 71.8-97.7%) and 56.1% (95% CI: 49.7-62.5%); 96.4% (95% CI: 81.7-99.9%) respectively. Pooled sensitivity for detection of extrahepatic metastatic disease was 92.2% (range: 88.1-100%; 95% CI: 87.8-95.4%) and 72.4% (range: 69.8-76.5; 95% CI: 65.9-78.2%) respectively. Also, the maximum standardized uptake value (SUVmax) and TBR were higher for FAPI PET/CT than 18F-FDG PET/CT in the included studies. Conclusion: Overall, FAPI PET/CT showed higher sensitivity for detection of liver tumors with better SUVmax and TBR than 18F-FDG PET/CT.

Does an untreated peri-implant dehiscence defect affect the progression of peri-implantitis?: A preclinical in vivo experimental study.

OBJECTIVE: To investigate the early impact of plaque accumulation in a buccal dehiscence defect on peri-implant marginal bone resorption. MATERIALS AND METHODS: In six male Mongrel dogs, four dental implants were placed in the posterior maxilla on both sides (two implants per side). Based on the group allocation, each implant was randomly assigned to one of the following four groups to decide whether buccal dehiscence defect was prepared and whether silk ligation was applied at 8 weeks post-implant placement for peri-implantitis induction: UC (no defect without ligation); UD (defect without ligation); LC (no defect with ligation); and LD (defect with ligation) groups. Eight weeks after disease induction, the outcomes from radiographic and histologic analyses were statistically analyzed (p < .05). RESULTS: Based on radiographs, the exposed area of implant threads was smallest in group UC (p < .0083). Based on histology, both the distances from the implant platform to the first bone-to-implant contact point and to the bone crest were significantly longer in the LD group (p < .0083). In the UD group, some spontaneous bone fill occurred from the base of the defect at 8 weeks after implant placement. The apical extension of inflammatory cell infiltrate was significantly more prominent in the LD and LC groups compared to the UC group (p < .0083). CONCLUSION: Plaque accumulated on the exposed implant surface had a negative impact on maintaining the peri-implant marginal bone level, especially when there was a dehiscence defect around the implant.

[Interstitial lung abnormalities : What the radiologist needs to know]. / Interstitielle Lungenanomalien : Was muss der Radiologe wissen?

Interstitial lung abnormalities (ILA) are incidental findings on computed tomography (CT), particularly in elderly patients and smokers. They describe mild interstitial abnormalities that can be progressive and turn into overt interstitial lung disease (ILD). In recent years, ILA have increasingly come into focus because several large cohort studies have shown poorer clinical outcomes and increased mortality for patients with ILA compared to those without ILA. The radiological classification into nonsubpleural, subpleural nonfibrotic and subpleural fibrotic as well as the assessment over time can-together with clinical risk factors-help estimate clinical outcome. Clinical management of patients with ILA includes exclusion of ILD and risk-adapted control intervals, especially in the presence of risk factors.

Nomogram to predict radicular grooves in maxillary lateral incisors in preoperative orthodontic population.

OBJECTIVES: This study aimed to develop and validate a predictive nomogram for diagnosing radicular grooves (RG) in maxillary lateral incisors (MLIs), integrating demographic information, anatomical measurements, and Cone Beam Computed Tomography (CBCT) data to diagnose the RG in MLIs based on the clinical observation before resorting to the CBCT scan. MATERIALS AND METHODS: A retrospective cohort of orthodontic patients from the School and Hospital of Stomatology, Wuhan University, was analyzed, including demographic characteristics, photographic anatomical assessments, and CBCT diagnoses. The cohort was divided into development and validation groups. Univariate and multivariate logistic regression analyses identified significant predictors of RG, which informed the development of a nomogram. This nomogram's performance was validated using receiver operating characteristic analysis. RESULTS: The study included 381 patients (64.3% female) and evaluated 760 MLIs, with RG present in 26.25% of MLIs. The nomogram incorporated four significant anatomical predictors of RG presence, demonstrating substantial predictive efficacy with an area under the curve of 0.75 in the development cohort and 0.71 in the validation cohort. CONCLUSIONS: A nomogram for the diagnosis of RG in MLIs was successfully developed. This tool offers a practical checklist of anatomical predictors to improve the diagnostic process in clinical practice. CLINICAL RELEVANCE: The developed nomogram provides a novel, evidence-based tool to enhance the detection and treatment planning of MLIs with RG in diagnostic and therapeutic strategies.

Standardized reporting for Head CT Scans in patients suspected of traumatic brain injury (TBI): An international expert endeavor.

BACKGROUND AND PURPOSE: Traumatic brain injury (TBI) is a major source of health loss and disability worldwide. Accurate and timely diagnosis of TBI is critical for appropriate treatment and management of the condition. Neuroimaging plays a crucial role in the diagnosis and characterization of TBI. Computed tomography (CT) is the first-line diagnostic imaging modality typically utilized in patients with suspected acute mild, moderate and severe TBI. Radiology reports play a crucial role in the diagnostic process, providing critical information about the location and extent of brain injury, as well as factors that could prevent secondary injury. However, the complexity and variability of radiology reports can make it challenging for healthcare providers to extract the necessary information for diagnosis and treatment planning. METHODS/RESULTS/CONCLUSION: In this article, we report the efforts of an international group of TBI imaging experts to develop a clinical radiology report template for CT scans obtained in patients suspected of TBI and consisting of fourteen different subdivisions (CT technique, mechanism of injury or clinical history, presence of scalp injuries, fractures, potential vascular injuries, potential injuries involving the extra-axial spaces, brain parenchymal injuries, potential injuries involving the cerebrospinal fluid spaces and the ventricular system, mass effect, secondary injuries, prior or coexisting pathology).

Skeletal muscle quantity and quality evaluation in heart failure: comparing thoracic versus abdominopelvic CT approaches.

Given the critical role of skeletal muscle in healthy aging, low muscle mass (myopenia) and quality (myosteatosis) can be used as predictors of poor functional and cardiometabolic outcomes. Myopenia is also a part of sarcopenia and malnutrition diagnostic criteria. However, there is limited evidence for using chest computed tomography (CT) to evaluate muscle health. We aimed to compare chest CT landmarks to the widely used L3 vertebra for single-slice skeletal muscle evaluation in patients with heart failure (HF). Patients admitted for acute decompensated HF between January 2017 and December 2018 were retrospectively analyzed. Body composition measurements were made on CT of the chest and abdomen/pelvis with or without contrast one month before discharge. Skeletal muscle index (SMI) and intermuscular adipose tissue percentage (IMAT%) were calculated at several thoracic levels (above the aortic arch, T8, and T12) and correlated to the widely used L3 level. A total of 200 patients were included, 89 (44.5%) female. The strongest correlation of thoracic SMI (for muscle quantity) and IMAT% (for muscle quality) with L3 was at the T12 level (r = 0.834, p < 0.001 and r = 0.757, p < 0.001, respectively). Cutoffs to identify low muscle mass for T12 SMI (derived from the lowest sex-stratified L3 SMI tertile) were 31.1 cm²/m² in men and 26.3 cm²/m² in women. SMI and IMAT% at T12 had excellent correlations with the widely used L3 level for muscle quantity and quality evaluation in patients with HF.

Invasive fractional-flow-reserve prediction by coronary CT angiography using artificial intelligence vs. computational fluid dynamics software in intermediate-grade stenosis.

Coronary computed angiography (CCTA) with non-invasive fractional flow reserve (FFR) calculates lesion-specific ischemia when compared with invasive FFR and can be considered for patients with stable chest pain and intermediate-grade stenoses according to recent guidelines. The objective of this study was to compare a new CCTA-based artificial-intelligence deep-learning model for FFR prediction (FFRAI) to computational fluid dynamics CT-derived FFR (FFRCT) in patients with intermediate-grade coronary stenoses with FFR as reference standard. The FFRAI model was trained with curved multiplanar-reconstruction CCTA images of 500 stenotic vessels in 413 patients, using FFR measurements as the ground truth. We included 37 patients with 39 intermediate-grade stenoses on CCTA and invasive coronary angiography, and with FFRCT and FFR measurements in this retrospective proof of concept study. FFRAI was compared with FFRCT regarding the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for predicting FFR ≤ 0.80. Sensitivity, specificity, PPV, NPV, and diagnostic accuracy of FFRAI in predicting FFR ≤ 0.80 were 91% (10/11), 82% (23/28), 67% (10/15), 96% (23/24), and 85% (33/39), respectively. Corresponding values for FFRCT were 82% (9/11), 75% (21/28), 56% (9/16), 91% (21/23), and 77% (30/39), respectively. Diagnostic accuracy did not differ significantly between FFRAI and FFRCT (p = 0.12). FFRAI performed similarly to FFRCT for predicting intermediate-grade coronary stenoses with FFR ≤ 0.80. These findings suggest FFRAI as a potential non-invasive imaging tool for guiding therapeutic management in these stenoses.

Optimal strategies for modeling anatomy in a hybrid intelligence framework for auto-segmentation of organs.

Organ segmentation is a fundamental requirement in medical image analysis. Many methods have been proposed over the past 6 decades for segmentation. A unique feature of medical images is the anatomical information hidden within the image itself. To bring natural intelligence (NI) in the form of anatomical information accumulated over centuries into deep learning (DL) AI methods effectively, we have recently introduced the idea of hybrid intelligence (HI) that combines NI and AI and a system based on HI to perform medical image segmentation. This HI system has shown remarkable robustness to image artifacts, pathology, deformations, etc. in segmenting organs in the Thorax body region in a multicenter clinical study. The HI system utilizes an anatomy modeling strategy to encode NI and to identify a rough container region in the shape of each object via a non-DL-based approach so that DL training and execution are applied only to the fuzzy container region. In this paper, we introduce several advances related to modeling of the NI component so that it becomes substantially more efficient computationally, and at the same time, is well integrated with the DL portion (AI component) of the system. We demonstrate a 9-40 fold computational improvement in the auto-segmentation task for radiation therapy (RT) planning via clinical studies obtained from 4 different RT centers, while retaining state-of-the-art accuracy of the previous system in segmenting 11 objects in the Thorax body region.

Effects of daily teriparatide, weekly high-dose teriparatide, or bisphosphonate on cortical and trabecular bone of vertebra and proximal femur in postmenopausal women with fragility fracture: Sub-analysis by quantitative computed tomography from the TERABIT study.

PURPOSE: The effects of daily teriparatide (D-PTH, 20 µg/day), weekly high-dose teriparatide (W-PTH, 56.5 µg/week), or bisphosphonate (BP) on the vertebra and proximal femur were investigated using quantitative computed tomography (QCT). METHODS: A total of 131 postmenopausal women with a history of fragility fractures were randomized to receive D-PTH, W-PTH, or bisphosphonate (oral alendronate or risedronate). QCT were evaluated at baseline and after 18 months of treatment. RESULTS: A total of 86 participants were evaluated by QCT (Spine: D-PTH: 25, W-PTH: 21, BP: 29. Hip: PTH: 22, W-PTH: 21, BP: 32. Dropout rate: 30.5 %). QCT of the vertebra showed that D-PTH, W-PTH, and BP increased total vBMD (+34.8 %, +18.2 %, +11.1 %), trabecular vBMD (+50.8 %, +20.8 %, +12.2 %), and marginal vBMD (+20.0 %, +14.0 %, +11.5 %). The increase in trabecular vBMD was greater in the D-PTH group than in the W-PTH and BP groups. QCT of the proximal femur showed that D-PTH, W-PTH, and BP increased total vBMD (+2.8 %, +3.6 %, +3.2 %) and trabecular vBMD (+7.7 %, +5.1 %, +3.4 %), while only W-PTH and BP significantly increased cortical vBMD (-0.1 %, +1.5 %, +1.6 %). Although there was no significant increase in cortical vBMD in the D-PTH group, cortical bone volume (BV) increased in all three treatment groups (+2.1 %, +3.6 %, +3.1 %). CONCLUSIONS: D-PTH had a strong effect on trabecular bone of vertebra. Although D-PTH did not increase cortical BMD of proximal femur, it increased cortical BV. W-PTH had a moderate effect on trabecular bone of vertebra, while it increased both cortical BMD and BV of proximal femur. Although BP had a limited effect on trabecular bone of vertebra compared to teriparatide, it increased both cortical BMD and BV of proximal femur.

A Cone-Beam Computed Tomography-Based Evaluation of Root Dilaceration in Permanent Premolars: A Retrospective Study.

Statement of the Problem: As a developmental disorder characterized by an abnormal bend and angle in the longitudinal axis of the tooth root, dilaceration can cause complications in routine dental procedures such as endodontics, orthodontics, and surgical treatments. Purpose: The purpose of this study was to investigate the prevalence of dilaceration in maxillary and mandibular premolar teeth in a population of Shiraz city based on cone-beam computed tomography (CBCT). Materials and Method: This is a retrospective cross-sectional study on 927 premolar teeth and 132 CBCT radiographs of patients obtained from four private radiology clinics in Shiraz (Iran). In this study, the presence, location, direction, and severity of dilaceration in premolar roots as well as its relationship with gender were investigated. Chi-square and Fisher tests were used to analyze the data. Results: The results showed that 17% of the studied 927 teeth had dilaceration. The prevalence of dilaceration was significantly higher in women than in men (20.3% vs. 13.6%, p= 0.005). The dilaceration rates were significantly higher in the mandibular first and second premolar teeth (31.6% and 26%, p= 0.002) than in the other teeth. In addition, the highest prevalence was in the distal direction with mild severity in the apical third of the root (p< 0.001). Conclusion: According to the results of this study, the prevalence of dilaceration was relatively high in mandibular premolar teeth especially in women.

Staged hybrid ablation in left atrial appendage aneurysm a rare cause of refractory atrial tachyarrhythmia-a case report.

Background: Left atrial appendage aneurysm (LAAA) is a rare cardiac anomaly, which can be congenital or acquired in origin. Because most cases are asymptomatic, it is typically diagnosed incidentally in the second to third decades of life. We present a case of a 28-year-old male with refractory atrial tachyarrhythmias and significantly reduced exercise tolerance. The informed consent was given by patient for this manuscript. Case summary: We present a case of a 28-year-old male with refractory atrial tachyarrhythmias and significantly reduced exercise tolerance after an episode of COVID respiratory infection. He was referred by primary care physician for management of atrial fibrillation (AF) with CHA2DS2Vasc score zero. He had documented AF and atrial flutter (AFL) resistant to both chemical and electrical cardioversions. Initial portable focused transthoracic echocardiography documented borderline reduced left ventricular ejection fraction in context of AFL. Electrophysiological study confirmed the diagnosis of typical AFL. Successful radiofrequency ablation of cavo-tricuspid isthmus resulted in bidirectional isthmus conduction block. However, patient developed AF, which was electrically cardioverted at the end of procedure. Patient was discharged on bisoprolol, ramipril, and apixaban, and outpatient cardiac MRI was organized to look for post-COVID myocardial scarring. Patient had recurrence of symptoms, and this time it was due to AF. Multimodal imaging led to discovery of LAAA, in which after discussion in multidisciplinary meeting, he was accepted for and managed with surgical resection of LAAA with concomitant Cox-Maze IV procedure. On 9 months post-operative follow up, patient is maintaining sinus rhythm and has completely returned to baseline activities. Discussion: A young patient with refractory atrial arrhythmia should be referred for multimodal cardiovascular imaging to rule out any structural heart disease. Left atrial appendage aneurysm is rare and can be managed conservatively, but surgical excision is most reported and appears to favour arrhythmia-free survival.

CT, MRI, and PET/CT imaging features of thoracic spine epithelioid hemangioma: a retrospective observational study.

Introduction: Epithelioid hemangioma (EH) is an intermediate locally aggressive tumor that consists of epithelioid cells and endothelial cell differentiation, which can occur at any age, but is most common between the ages of 30 and 40 years. EH in the thoracic spine is rare, and accurate diagnosis is critical to treatment planning. Our aim was to explore the imaging and clinical data of thoracic spine EH to improve the understanding of this rare disease. Methods: From January 1, 2018 to June 30, 2023, a database of thoracic spine masses was retrospectively reviewed. Five patients with histologically proven thoracic spine EH and complete imaging available were identified and analyzed. Computed tomography (CT) and magnetic resonance imaging (MRI) findings were evaluated separately by two radiologists with more than 10 years of experience. Positron emission tomography (PET)/CT was conducted by two nuclear medicine diagnostic technologists with at least 5 years of experience. Results: The patients included three male and two female patients aged 23 to 56 years (mean age was 38.4 ± 14.3 years). All patients underwent CT, MRI, and 18F-FDG PET/CT examination before treatment. Four patients were limited to one vertebral involvement, only one patient had multiple vertebral involvement, and all tumors involved the accessories, including one involving the posterior ribs. The maximum diameter of the tumor ranged from 2.7 to 4.3. Conclusions: CT, MRI, and 18F-FDG PET/CT findings of thoracic spine EH have certain characteristics, and understanding these imaging findings will help to obtain accurate diagnosis before surgery.

[A dual-domain cone beam computed tomography reconstruction framework with improved differentiable domain transform for cone-angle artifact correction].

OBJECTIVE: We propose a dual-domain cone beam computed tomography (CBCT) reconstruction framework DualCBR-Net based on improved differentiable domain transform for cone-angle artifact correction. METHODS: The proposed CBCT dual-domain reconstruction framework DualCBR-Net consists of 3 individual modules: projection preprocessing, differentiable domain transform, and image post-processing. The projection preprocessing module first extends the original projection data in the row direction to ensure full coverage of the scanned object by X-ray. The differentiable domain transform introduces the FDK reconstruction and forward projection operators to complete the forward and gradient backpropagation processes, where the geometric parameters correspond to the extended data dimension to provide crucial prior information in the forward pass of the network and ensure the accuracy in the gradient backpropagation, thus enabling precise learning of cone-beam region data. The image post-processing module further fine-tunes the domain-transformed image to remove residual artifacts and noises. RESULTS: The results of validation experiments conducted on Mayo's public chest dataset showed that the proposed DualCBR-Net framework was superior to other comparison methods in terms of artifact removal and structural detail preservation. Compared with the latest methods, the DualCBR-Net framework improved the PSNR and SSIM by 0.6479 and 0.0074, respectively. CONCLUSION: The proposed DualCBR-Net framework for cone-angle artifact correction allows effective joint training of the CBCT dual-domain network and is especially effective for large cone-angle region.

[A deep blur learning-based motion artifact reduction algorithm for dental cone-beam computed tomography images].

OBJECTIVE: We propose a motion artifact correction algorithm (DMBL) for reducing motion artifacts in reconstructed dental cone-beam computed tomography (CBCT) images based on deep blur learning. METHODS: A blur encoder was used to extract motion-related degradation features to model the degradation process caused by motion, and the obtained motion degradation features were imported in the artifact correction module for artifact removal. The artifact correction module adopts a joint learning framework for image blur removal and image blur simulation for treatment of spatially varying and random motion patterns. Comparative experiments were conducted to verify the effectiveness of the proposed method using both simulated motion data sets and clinical data sets. RESULTS: The experimental results with the simulated dataset showed that compared with the existing methods, the PSNR of the proposed method increased by 2.88%, the SSIM increased by 0.89%, and the RMSE decreased by 10.58%. The results with the clinical dataset showed that the proposed method achieved the highest expert level with a subjective image quality score of 4.417 (in a 5-point scale), significantly higher than those of the comparison methods. CONCLUSION: The proposed DMBL algorithm with a deep blur joint learning network structure can effectively reduce motion artifacts in dental CBCT images and achieve high-quality image restoration.

DATA-DRIVEN IMAGING GEOMETRIC RECOVERY OF ULTRAHIGH RESOLUTION ROBOTIC MICRO-CT FOR IN-VIVO AND OTHER APPLICATIONS.

We introduce an ultrahigh-resolution (50µm) robotic micro-CT design for localized imaging of carotid plaques using robotic arms, cutting-edge detector, and machine learning technologies. To combat geometric error-induced artifacts in interior CT scans, we propose a data-driven geometry estimation method that maximizes the consistency between projection data and the reprojection counterparts of a reconstructed volume. Particularly, we use a normalized cross correlation metric to overcome the projection truncation effect. Our approach is validated on a robotic CT scan of a sacrificed mouse and a micro-CT phantom scan, both producing sharper images with finer details than that prior correction.

Differentiating between benign and malignant breast lesions using dual-energy CT-based model: development and validation.

OBJECTIVES: To develop and validate a dual-energy CT (DECT)-based model for noninvasively differentiating between benign and malignant breast lesions detected on DECT. MATERIALS AND METHODS: This study prospectively enrolled patients with suspected breast cancer who underwent dual-phase contrast-enhanced DECT from July 2022 to July 2023. Breast lesions were randomly divided into the training and test cohorts at a ratio of 7:3. Clinical characteristics, DECT-based morphological features, and DECT quantitative parameters were collected. Univariate analyses and multivariate logistic regression were performed to determine independent predictors of benign and malignant breast lesions. An individualized model was constructed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic ability of the model, whose calibration and clinical usefulness were assessed by calibration curve and decision curve analysis. RESULTS: This study included 200 patients (mean age, 49.9 ± 11.9 years; age range, 22-83 years) with 222 breast lesions. Age, lesion shape, and the effective atomic number (Zeff) in the venous phase were significant independent predictors of breast lesions (all p < 0.05). The discriminative power of the model incorporating these three factors was high, with AUCs of 0.844 (95%CI 0.764-0.925) and 0.791 (95% CI 0.647-0.935) in the training and test cohorts, respectively. The constructed model showed a preferable fitting (all p > 0.05 by the Hosmer-Lemeshow test) and provided enhanced net benefits than simple default strategies within a wide range of threshold probabilities in both cohorts. CONCLUSION: The DECT-based model showed a favorable diagnostic performance for noninvasive differentiation between benign and malignant breast lesions detected on DECT. CRITICAL RELEVANCE STATEMENT: The combination of clinical and morphological characteristics and DECT-derived parameter have the potential to identify benign and malignant breast lesions and it may be useful for incidental breast lesions on DECT to decide if further work-up is needed. KEY POINTS: It is important to characterize incidental breast lesions on DECT for patient management. DECT-based model can differentiate benign and malignant breast lesions with good performance. DECT-based model is a potential tool for distinguishing breast lesions detected on DECT.

An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study.

OBJECTIVES: To develop and validate a novel interpretable artificial intelligence (AI) model that integrates radiomic features, deep learning features, and imaging features at multiple semantic levels to predict the prognosis of intracerebral hemorrhage (ICH) patients at 6 months post-onset. MATERIALS AND METHODS: Retrospectively enrolled 222 patients with ICH for Non-contrast Computed Tomography (NCCT) images and clinical data, who were divided into a training cohort (n = 186, medical center 1) and an external testing cohort (n = 36, medical center 2). Following image preprocessing, the entire hematoma region was segmented by two radiologists as the volume of interest (VOI). Pyradiomics algorithm library was utilized to extract 1762 radiomics features, while a deep convolutional neural network (EfficientnetV2-L) was employed to extract 1000 deep learning features. Additionally, radiologists evaluated imaging features. Based on the three different modalities of features mentioned above, the Random Forest (RF) model was trained, resulting in three models (Radiomics Model, Radiomics-Clinical Model, and DL-Radiomics-Clinical Model). The performance and clinical utility of the models were assessed using the Area Under the Receiver Operating Characteristic Curve (AUC), calibration curve, and Decision Curve Analysis (DCA), with AUC compared using the DeLong test. Furthermore, this study employs three methods, Shapley Additive Explanations (SHAP), Grad-CAM, and Guided Grad-CAM, to conduct a multidimensional interpretability analysis of model decisions. RESULTS: The Radiomics-Clinical Model and DL-Radiomics-Clinical Model exhibited relatively good predictive performance, with an AUC of 0.86 [95% Confidence Intervals (CI): 0.71, 0.95; P < 0.01] and 0.89 (95% CI: 0.74, 0.97; P < 0.01), respectively, in the external testing cohort. CONCLUSION: The multimodal explainable AI model proposed in this study can accurately predict the prognosis of ICH. Interpretability methods such as SHAP, Grad-CAM, and Guided Grad-Cam partially address the interpretability limitations of AI models. Integrating multimodal imaging features can effectively improve the performance of the model. CLINICAL RELEVANCE STATEMENT: Predicting the prognosis of patients with ICH is a key objective in emergency care. Accurate and efficient prognostic tools can effectively prevent, manage, and monitor adverse events in ICH patients, maximizing treatment outcomes.

Increased adiposity-to-muscle ratio and severity of sinusitis affect quality of life in asthma: Computed tomographic analysis.

Background: Deteriorated sinusitis and increased adiposity relative to muscle mass may affect quality of life in patients with asthma. However, whether these effects are observed regardless of intrapulmonary pathology is unknown. Objectives: We evaluated the correlation of the cross-sectional ratio of abdominal visceral fat (VF) to erector spinae muscle (ESM) and sinus findings based on Lund-Mackey scoring system (LMS) on computed tomography (CT) with the impaired score of the Asthma Quality of Life Questionnaire (AQLQ), regardless of airway and parenchymal disease, in patients with asthma. Methods: We recruited participants from the Hokkaido-based severe asthma cohort who had completed AQLQ and CT examination at the entry. The participants were divided into high (highest) and low (other quartiles) groups on the bases of the extrapulmonary indices. Multivariate analysis examined the association of VF/ESM for the adiposity-to-muscle ratio and LMS with AQLQ after adjusting for the airway fractal dimension for airway index and percentage of low attenuation volume to lung volume for parenchymal index. Results: No significant differences were observed in VF/ESM and LMS in terms of sex. The AQLQ score in the high VF/ESM group and high LMS group was lower than those in low VF/ESM group and low LMS group (63 male and 100 female subjects). High VF/ESM (estimate [95% confidence interval] (-0.43 [-0.61, -0.25]) and high LMS scores (-0.22 [-0.41, -0.03]) were associated with low AQLQ scores when adjusted for age, body mass index, smoking status, blood eosinophil count, and intrapulmonary CT indices. Conclusions: Increased VF relative to ESM mass and high LMS may deteriorate asthma-related quality of life, regardless of presence of intrapulmonary disease.

Size-matching in lung transplantation by computed tomography for end-stage interstitial disease: a retrospective analysis.

Background: Size matching between donors and recipients is a major issue in lung transplantation (LTx), especially in patients with restrictive lung disease (RLD). This study aims to evaluate computed tomography (CT) as an additional method for defining the total lung capacity (TLC) in patients with end-stage interstitial disease awaiting LTx. Methods: Clinical data and CT scans from patients who underwent a first LTx from January 2014 to July 2018 in Bichat Hospital, Paris, were prospectively included in a database. CT TLC (ctTLC) was retrospectively calculated after semi-automatic contouring of the parenchyma and compared with measured TLC (mTLC) and predicted TLC (pTLC) values. Results: The study group included 89 patients (male:female =68:21; mean age, 59.5±10.0 years). The time between pulmonary function tests (PFTs) and CT scan was 162±270 days [median, 67 days; interquartile range (IQR), 0-233 days]. ctTLC was inferior to mTLC and pTLC (respectively 2,979±1,001 mL, 3,530±1,077 and 6,381±955 mL, P<0.001). The relative difference between CT lung volume (ctLV) and measured lung volume (mLV) was higher on the left than on the right side (25.4% vs. 16.3%, respectively, P=0.11). After exclusion of two outliers, we found a significant correlation between ctTLC and mTLC (r=0.762, P<0.001). Conclusions: CT volume is a feasible method to assess TLC in patients with end-stage interstitial disease awaiting LTx. This study highlights potential size-mismatch for graft selection before LTx and opens the perspective of a prospective trial evaluating impact of size-matching by donor-recipient (D-R) ctTLC ratio on postoperative outcomes.