New powder reuse schema in laser-based powder bed fusion of polymers.

The laser-based powder bed fusion of polymers (PBF-LB/P) process often utilizes a blend of powders with varying degrees of degradation. Specifically, for polyamide 12, the traditional reuse schema involves mixing post-processed powder with virgin powder at a predetermined ratio before reintroducing it to the process. Given that only about 15% of the powder is utilized in part production, and powders are refreshed in equal proportions, there arises a challenge with the incremental accumulation of material across build cycles. To mitigate the consumption of fresh powder relative to the actual material usage, this study introduces the incorporation of recycled material into the PBF-LB/P process. This new powder reuse schema is presented for the first time, focusing on the laser sintering process. The characteristics of the recycled powder were evaluated through scanning electron microscopy, differential scanning calorimetry, X-ray diffraction, particle size distribution, and dynamic powder flowability assessments. The findings reveal that waste powders can be effectively reused in PBF-LB/P to produce components with satisfactory mechanical properties, porosity levels, dimensional accuracy, and surface quality.

Simulating Two-Phase Seepage in Undisturbed Soil Based on Lattice Boltzmann Method and X-ray Computed Tomography Images.

The two-phase seepage fluid (i.e., air and water) behaviors in undisturbed granite residual soil (U-GRS) have not been comprehensively studied due to a lack of accurate and representative models of its internal pore structure. By leveraging X-ray computed tomography (CT) along with the lattice Boltzmann method (LBM) enhanced by the Shan-Chen model, this study simulates the impact of internal pore characteristics of U-GRS on the water-gas two-phase seepage flow behaviors. Our findings reveal that the fluid demonstrates a preference for larger and straighter channels for seepage, and as seepage progresses, the volume fraction of the water/gas phases exhibits an initial increase/decrease trend, eventually stabilizing. The results show the dependence of two-phase seepage velocity on porosity, while the local seepage velocity is influenced by the distribution and complexity of the pore structure. This emphasizes the need to consider pore distribution and connectivity when studying two-phase flow in undisturbed soil. It is observed that the residual gas phase persists within the pore space, primarily localized at the pore margins and dead spaces. Furthermore, the study identifies that hydrophobic walls repel adjacent fluids, thereby accelerating fluid movement, whereas hydrophilic walls attract fluids, inducing a viscous effect that decelerates fluid flow. Consequently, the two-phase flow rate is found to increase with then-enhanced hydrophobicity. The apex of the water-phase volume fraction is observed under hydrophobic wall conditions, reaching up to 96.40%, with the residual gas-phase constituting 3.60%. The hydrophilic wall retains more residual gas-phase volume fraction than the neutral wall, followed by the hydrophobic wall. Conclusively, the investigations using X-ray CT and LBM demonstrate that the pore structure characteristics and the wettability of the pore walls significantly influence the two-phase seepage process.

Computed Tomography-Based Intratumor Heterogeneity Predicts Response to Immunotherapy Plus Chemotherapy in Esophageal Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: This study explored the intratumor heterogeneity (ITH) of esophageal squamous cell carcinoma (ESCC) using computed tomography (CT) and investigated the value of CT-based ITH in predicting the response to immune checkpoint inhibitor (ICI) plus chemotherapy in patients with ESCC. MATERIALS AND METHODS: This retrospective study included 416 patients with ESCC who received ICI plus chemotherapy at two independent hospitals between January 2019 and July 2022. Multiparametric CT features were extracted from ESCC lesions and screened using hierarchical clustering and dimensionality reduction algorithms. Logistic regression and machine learning models based on selected features were developed to predict treatment response and validated in separate datasets. ITH was quantified using the score calculated by the best-performing model and visualized through feature clustering and feature contribution heatmaps. A gene set enrichment analysis (GSEA) was performed to identify the biological pathways underlying the CT-based ITH. RESULTS: The extreme gradient boosting model based on CT-derived ITH had higher discriminative power, with areas under the receiver operating characteristic curve of 0.864 (95% confidence interval [CI]: 0.774-0.954) and 0.796 (95% CI: 0.698-0.893) in the internal and external validation sets. The CT-based ITH pattern differed significantly between responding and non-responding patients. The GSEA indicated that CT-based ITH was associated with immunity-, keratinization-, and epidermal cell differentiation-related pathways. CONCLUSION: CT-based ITH is an effective biomarker for identifying patients with ESCC who could benefit from ICI plus chemotherapy. Immunity-, keratinization-, and epidermal cell differentiation-related pathways may influence the patient's response to ICI plus chemotherapy.

Multi-scale structural characterization of ceramic-based photonic glasses for structural colors.

Structural colors arise from selective light interaction with (nano)structures, which give them advantages over pigmented colors such as resistance to fading and possibility to be fabricated out of traditional low-cost and non-toxic materials. Since the color arises from the photonic (nano)structures, different structural features can impact their photonic response and thus, their color. Therefore, the detailed characterization of their structural features is crucial for further improvement of structural colors. In this work, we present a detailed multi-scale structural characterization of ceramic-based photonic glasses by using a combination of high-resolution ptychographic X-ray computed tomography and small angle X-ray scattering. Our results uncover the structure-processing-properties' relationships of such nanoparticles-based photonic glasses and point out to the need of a review of the structural features used in simulation models concomitantly with the need for further investigations by experimentalists, where we point out exactly which structural features need to be improved.

In vitro blood sample assessment: investigating correlation of laboratory hemoglobin and spectral properties of dual-energy CT measurements (ρ/Z).

OBJECTIVES: Our study comprised a single-center retrospective in vitro correlation between spectral properties, namely ρ/Z values, derived from scanning blood samples using dual-energy computed tomography (DECT) with the corresponding laboratory hemoglobin/hematocrit (Hb/Hct) levels and assessed the potential in anemia-detection. METHODS: DECT of 813 patient blood samples from 465 women and 348 men was conducted using a standardized scan protocol. Electron density relative to water (ρ or rho), effective atomic number (Zeff), and CT attenuation (Hounsfield unit) were measured. RESULTS: Positive correlation with the Hb/Hct was shown for ρ (r-values 0.37-0.49) and attenuation (r-values 0.59-0.83) while no correlation was observed for Zeff (r-values -0.04 to 0.08). Significant differences in attenuation and ρ values were detected for blood samples with and without anemia in both genders (p value < 0.001) with area under the curve ranging from 0.7 to 0.95. Depending on the respective CT parameters, various cutoff values for CT-based anemia detection could be determined. CONCLUSION: In summary, our study investigated the correlation between DECT measurements and Hb/Hct levels, emphasizing novel aspects of ρ and Zeff values. Assuming that quantitative changes in the number of hemoglobin proteins might alter the mean Zeff values, the results of our study show that there is no measurable correlation on the atomic level using DECT. We established a positive in vitro correlation between Hb/Hct values and ρ. Nevertheless, attenuation emerged as the most strongly correlated parameter with identifiable cutoff values, highlighting its preference for CT-based anemia detection. CLINICAL RELEVANCE STATEMENT: By scanning multiple blood samples with dual-energy CT scans and comparing the measurements with standard laboratory blood tests, we were able to underscore the potential of CT-based anemia detection and its advantages in clinical practice. KEY POINTS: Prior in vivo studies have found a correlation between aortic blood pool and measured hemoglobin and hematocrit. Hemoglobin and hematocrit correlated with electron density relative to water and attenuation but not Zeff. Dual-energy CT has the potential for additional clinical benefits, such as CT-based anemia detection.

Imaging porosity evolution of tight sandstone during spontaneous water imbibition by X-ray Micro-CT.

Water imbibition is an important process in reservoir rocks during hydraulic fracturing and water-based enhanced oil recovery operations. However, the water imbibition behavior in tight sandstones has not been fully understood due to their complex pore structure, including the presence of nano and micron-sized pores and throats, surface properties, and wide variation in mineralogy. The present study focuses on the effect of spontaneous water imbibition on the porosity evolution of a tight sandstone. Within this context, a core of Torrey Buff sandstone was characterized by using a combination of multiscale imaging methods (X-ray Computed Tomography, Scanning Electron Microscopy), laboratory experiments (porosity-permeability measurements), and analytical techniques (X-ray Diffraction, Fourier Transform Infrared Spectroscopy, Scanning Electron Microscopy-Energy Dispersive Spectroscopy, and Thermogravimetry). The studied tight sandstone core has a porosity of 12.3 % and permeability of 2.05mD with minerals of quartz (58 %), clays (kaolinite and illite, 23 %), K-feldspar (7 %), dolomite (7 %) and calcite (5 %). Primary and secondary pores, ranging in size from 60 to 140 µm and 30-50 µm, respectively, are mostly filled with highly-soluble carbonate minerals and hydrophilic illite, which influence the spontaneous water imbibition capacity of the tight sandstone. The multiscale imaging technique indicates that after a 10-h long water imbibition experiment, the average pore size of the tight sandstone increased by 1.28 %, reaching 2.35 % at the rock-water contact and 0.13 % at the top of the core. In other words, throughout the core, the porosity changes upon water imbibition are not uniform but show an almost linear trend. This observation could be explained by the significant contribution of highly-soluble carbonates and hydrophilic illite on the microstructure of the tight sandstone. This study implies that multiscale imaging techniques, crucial in examining spontaneous water imbibition, hold promise for further research in enhanced oil recovery or hydraulic fracking in tight sandstones.

ESR Essentials: characterisation and staging of adnexal masses with MRI and CT-practice recommendations by ESUR.

Ovarian masses encompass various conditions, from benign to highly malignant, and imaging plays a vital role in their diagnosis and management. Ultrasound, particularly transvaginal ultrasound, is the foremost diagnostic method for adnexal masses. Magnetic Resonance Imaging (MRI) is advised for more precise characterisation if ultrasound results are inconclusive. The ovarian-adnexal reporting and data system (O-RADS) MRI lexicon and scoring system provides a standardised method for describing, assessing, and categorising the risk of each ovarian mass. Determining a histological differential diagnosis of the mass may influence treatment decision-making and treatment planning. When ultrasound or MRI suggests the possibility of cancer, computed tomography (CT) is the preferred imaging technique for staging. It is essential to outline the extent of the malignancy, guide treatment decisions, and evaluate the feasibility of cytoreductive surgery. This article provides a comprehensive overview of the key imaging processes in evaluating and managing ovarian masses, from initial diagnosis to initial treatment. It also includes pertinent recommendations for properly performing and interpreting various imaging modalities. KEY POINTS: MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians. CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery. Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.

Relationship between periapical lesions and sinus changes on multi-slice computed tomography sean.

Differentiating orofacial odontogenic pain/disorders from pain/disorders associated with maxillary sinusitis is important to avoid unnecessary dentalprocedures and to properly refer patients to colleagues/dentists and vice versa. AIM: To analyze the association between apical lesions and sinus changes and to evaluate the agreement between the diagnoses of an endodontist, a radiologist, an oral and maxillofacial surgeon, and an otolaryngologist. MATERIALS AND METHOD: 385 axial, coronal, and sagittal MSCT scans were selected using an image archiving andcommunication system (PACS). The examinations had been performed between 2018 and 2022. RESULTS: Apical lesions were observed in 36.10% of sinusitis cases, 73.8% of unilateralsinusitis cases, 48.7% of sinus floor discontinuity cases, and 67.2% of cases in which endodontic treatment had been performed. Agreement between the diagnoses made by the endodontist and those made by the other investigators was high for most study variables (k > 0.60). The exceptions were mucosal thickening, for which agreement between the endodontist and the other investigators was intermediate (k=0.397), and the presence of periapicallesions (k=0.010), previous endodontic treatment (k=0.013), and mucosal thickness (k=0.024), for which agreement between endodontists and radiologists was low. Conclusions: There was an association between sinus changes and apical lesions.

Diferenciar a dor/desordens odontogénicas orofaciais da dor/desordens as sociadas á sinusite maxilar é importante para evitar procedimentos odontológicos desnecessários e para encaminhar adequadamente os pacientes aos colegas/dentistas e vice-versa. OBJETIVO: Analisar a associagdo entre lesoes apicais e alteragóes sinusais e avaliar a concordáncia entre os diagnósticos de um endodontista, um radiologista, um cirurgido bucomaxilofacial e um otorrinolaringologista. MATERIAL E MÉTODO: foram avaliadas 385 imagens. RESULTADOS: Aslesoes apicais foram observadas em 36,10% dos casos de sinusite, em 73,8% dos casos de sinusite unilateral, em 48,7% dos casos de descontinuidade do assoalho do seio e em 67,2%odos casos em que o tratamento endodontico havia sido realizado. A concordancia entre os diagnósticos feitos pelo endodontista e os feitos pelos outros pesquisadores foi alta para a maioria das variáveis do estudo (k > 0,60). As excegoes foram o espessamento da mucosa, para o qual a concordáncia entre o endodontista e os outros pesquisadores foi intermediária (k=0,397) e a presenga delesoes periapicais (k=0,010), tratamento endodontico prévio (k=0,013) e espessura da mucosa (k=0,024), para os quais a concordáncia entre endodontistas e radiologistas foi baixa. CONCLUSÕES: Houve uma associagdo entre as alteragóes sinusais e aslesoes apicais.

The value of the radiological diameter-to-thickness ratio in patients with HER2-positive resectable advanced gastric cancer: implications for long survival and stage migration.

PURPOSE: To investigate the clinical significance and stage migration effect of radiological diameter-to-thickness (DT) ratio in HER2-positive resectable advanced gastric cancer (HER2-p RAGC). METHODS: 369 HER2-p RAGC patients were retrospectively enrolled and information on clinical pathological characteristics, radiological DT ratio, and outcomes [i.e., overall survival (OS) and progression-free survival (PFS)] was collected. Pearson's Chi-square and Student's t-test were employed to compare baseline characteristics. Clinical outcomes were estimated using Kaplan-Meier analysis and Log-rank test. Univariate and multivariate Cox regression models were utilized to analyze independent prognostic factors. RESULTS: HER2-p RAGC patients were stratified into two groups using a DT ratio cutoff value of 4.0 (p < 0.05). Patients with a DT ratio < 4.0 exhibited significantly longer OS (58.0 vs. 31.0 months) and PFS (43.0 vs. 24.0 months) than those with a DT ratio ≥ 4.0. DT ratio significantly predicted prognosis for N0 and II stage patients (p < 0.05). Patients with gastric body and antrum cancers demonstrated longer OS and PFS in the DT ratio < 4.0 group (p = 0.046, 0.017, 0.036 and 0.028). Multivariate Cox proportional hazard model identified age, pathological T category, pathological N category, pathological TNM category and DT ratio as independent prognostic factors. Notably, pStage II patients with a DT ratio ≥ 4.0 exhibited a similar prognosis to pStage III patients with a DT ratio < 4.0 (p = 0.418 for OS, 0.867 for PFS). CONCLUSION: Radiological DT ratio could evaluate the prognosis and detect higher malignant cases in HER2-p RAGC patients. Moreover, DT ratio might guide clinicians make postoperative strategies. TRIAL REGISTRATION: Retrospectively registered.

Quantitative analysis of interstitial lung abnormalities on computed tomography to predict symptomatic radiation pneumonitis after lung stereotactic body radiotherapy.

BACKGROUND AND PURPOSE: Symptomatic radiation pneumonitis (SRP) is a complication of thoracic stereotactic body radiotherapy (SBRT). As visual assessments pose limitations, artificial intelligence-based quantitative computed tomography image analysis software (AIQCT) may help predict SRP risk. We aimed to evaluate high-resolution computed tomography (HRCT) images with AIQCT to develop a predictive model for SRP. MATERIALS AND METHODS: AIQCT automatically labelled HRCT images of patients treated with SBRT for stage I lung cancer according to lung parenchymal pattern. Quantitative data including the volume and mean dose (Dmean) were obtained for reticulation + honeycombing (Ret + HC), consolidation + ground-glass opacities, bronchi (Br), and normal lungs (NL). After associations between AIQCT's quantified metrics and SRP were investigated, we developed a predictive model using recursive partitioning analysis (RPA) for the training cohort and assessed its reproducibility with the testing cohort. RESULTS: Overall, 26 of 207 patients developed SRP. There were significant between-group differences in the Ret + HC, Br-volume, and NL-Dmean in patients with and without SRP. RPA identified the following risk groups: NL-Dmean ≥ 6.6 Gy (high-risk, n = 8), NL-Dmean < 6.6 Gy and Br-volume ≥ 2.5 % (intermediate-risk, n = 13), and NL-Dmean < 6.6 Gy and Br-volume < 2.5 % (low-risk, n = 133). The incidences of SRP in these groups within the training cohort were 62.5, 38.4, and 7.5 %; and in the testing cohort 50.0, 27.3, and 5.0 %, respectively. CONCLUSION: AIQCT identified CT features associated with SRP. A predictive model for SRP was proposed based on AI-detected Br-volume and the NL-Dmean.

Nomogram for the preoperative prediction of Ki-67 expression and prognosis in stage IA lung adenocarcinoma based on clinical and multi-slice spiral computed tomography features.

OBJECTIVE: This study developed and validated a nomogram utilizing clinical and multi-slice spiral computed tomography (MSCT) features for the preoperative prediction of Ki-67 expression in stage IA lung adenocarcinoma. Additionally, we assessed the predictive accuracy of Ki-67 expression levels, as determined by our model, in estimating the prognosis of stage IA lung adenocarcinoma. MATERIALS AND METHODS: We retrospectively analyzed data from 395 patients with pathologically confirmed stage IA lung adenocarcinoma. A total of 322 patients were divided into training and internal validation groups at a 6:4 ratio, whereas the remaining 73 patients composed the external validation group. According to the pathological results, the patients were classified into high and low Ki-67 labeling index (LI) groups. Clinical and CT features were subjected to statistical analysis. The training group was used to construct a predictive model through logistic regression and to formulate a nomogram. The nomogram's predictive ability and goodness-of-fit were assessed. Internal and external validations were performed, and clinical utility was evaluated. Finally, the recurrence-free survival (RFS) rates were compared. RESULTS: In the training group, sex, age, tumor density type, tumor-lung interface, lobulation, spiculation, pleural indentation, and maximum nodule diameter differed significantly between patients with high and low Ki-67 LI. Multivariate logistic regression analysis revealed that sex, tumor density, and maximum nodule diameter were significantly associated with high Ki-67 expression in stage IA lung adenocarcinoma. The calibration curves closely resembled the standard curves, indicating the excellent discrimination and accuracy of the model. Decision curve analysis revealed favorable clinical utility. Patients with a nomogram-predicted high Ki-67 LI exhibited worse RFS. CONCLUSION: The nomogram utilizing clinical and CT features for the preoperative prediction of Ki-67 expression in stage IA lung adenocarcinoma demonstrated excellent performance, clinical utility, and prognostic significance, suggesting that this nomogram is a noninvasive personalized approach for the preoperative prediction of Ki-67 expression.

Multimodal 2D and 3D microscopic mapping of growth cartilage by computational imaging techniques - a short review including new research.

Being able to image the microstructure of growth cartilage is important for understanding the onset and progression of diseases such as osteochondrosis and osteoarthritis, as well as for developing new treatments and implants. Studies of cartilage using conventional optical brightfield microscopy rely heavily on histological staining, where the added chemicals provide tissue-specific colours. Other microscopy contrast mechanisms include polarization, phase- and scattering contrast, enabling non-stained or 'label-free' imaging that significantly simplifies the sample preparation, thereby also reducing the risk of artefacts. Traditional high-performance microscopes tend to be both bulky and expensive.Computational imagingdenotes a range of techniques where computers with dedicated algorithms are used as an integral part of the image formation process. Computational imaging offers many advantages like 3D measurements, aberration correction and quantitative phase contrast, often combined with comparably cheap and compact hardware. X-ray microscopy is also progressing rapidly, in certain ways trailing the development of optical microscopy. In this study, we first briefly review the structures of growth cartilage and relevant microscopy characterization techniques, with an emphasis on Fourier ptychographic microscopy (FPM) and advanced x-ray microscopies. We next demonstrate with our own results computational imaging through FPM and compare the images with hematoxylin eosin and saffron (HES)-stained histology. Zernike phase contrast, and the nonlinear optical microscopy techniques of second harmonic generation (SHG) and two-photon excitation fluorescence (TPEF) are explored. Furthermore, X-ray attenuation-, phase- and diffraction-contrast computed tomography (CT) images of the very same sample are presented for comparisons. Future perspectives on the links to artificial intelligence, dynamic studies andin vivopossibilities conclude the article.

Feasibility of virtual non-iodine coronary calcium scoring on dual source photon-counting coronary CT angiography: a dynamic phantom study.

BACKGROUND: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans. METHODS: In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60-75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI. RESULTS: For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671-0.853). CONCLUSION: In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial. CLINICAL RELEVANCE STATEMENT: Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice. KEY POINTS: Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates. Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed. Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.

Research on the Development of Methods for Detection of Substandard and Falsified Medicines by Clarifying Their Pharmaceutical Characteristics Using Modern Technology.

The existence of substandard and falsified medicines threatens people's health and causes economic losses as well as a loss of trust in medicines. As the distribution of pharmaceuticals becomes more globalized and the spread of substandard and falsified medicines continues worldwide, pharmaceutical security measures must be strengthened. To eradicate substandard and falsified medicines, our group is conducting fact-finding investigations of medicines distributed in lower middle-income countries (LMICs) and on the Internet. From the perspective of pharmaceutics, such as physical assessment of medicines, we are working to clarify the actual situation and develop methods to detect substandard and falsified medicines. We have collected substandard and falsified medicines distributed in LMICs and on the Internet and performed pharmacopoeial tests, mainly using HPLC, which is a basic analytic method. In addition to quality evaluation, we have evaluated the applicability of various analytic methods, including observation of pharmaceuticals using an electron microscope, Raman scattering analysis, near-IR spectroscopic analysis, chemical imaging, and X-ray computed tomography (CT) to detect substandard and falsified medicines, and we have clarified their limitations. We also developed a small-scale quality screening method using statistical techniques. We are engaged in the development of methods to monitor the distribution of illegal medicines and evolve research in forensic and policy science. These efforts will contribute to the eradication of substandard and falsified medicines. Herein, I describe our experience in the development of detection methods and elucidation of the pharmaceutical status of substandard and falsified medicines using novel technologies.

Progress toward the Definition of X-ray Computed Tomography Accuracy in the Characterization of Polymer-Based Lattice Structures.

Lattice structures have become an innovative solution for the improvement of part design, as they are able to substitute solid regions, maintain mechanical capabilities, and reduce material usage; however, dimensional quality control of these geometries is challenging. X-ray computed tomography (XCT) is the most suitable non-destructive metrological technique as it is capable of characterizing internal features and hidden elements. Uncertainty estimation of XCT is still in development, and studies typically use high-resolution calibrated devices such as focal variation microscopes (FVMs) as a reference, focusing on certain parts of the lattice but not the whole structure. In this paper, an estimation of the accuracy of XCT evaluation of a complete lattice structure in comparison to a higher-resolution reference device (FVM) is presented. Experimental measurements are taken on ad hoc designed test objects manufactured in polyamide 12 (PA12) using selective laser sintering (SLS), optimized for the evaluation on both instruments using different cubic-based lattice typologies. The results confirm higher precision on XCT evaluation in both qualitative and quantitative analysis. Even with a lower resolution, XCT is able to characterize details of the surface such as re-entrant features; as well, standard deviations and uncertainties in strut diameter evaluation remain more stable in all cells in XCT, identifying on the other hand reconstruction problems on FVM measurements. Moreover, it is shown that, using XCT, no additional evaluation errors were found in inner cells, suggesting that the measurement of external elements could be representative of the whole structure for metrological purposes.

Prognostic and predictive value of interstitial lung abnormalities and EGFR mutation status in patients with non-small cell lung cancer.

BACKGROUND: To determine the predictive value of interstitial lung abnormalities (ILA) for epidermal growth factor receptor (EGFR) mutation status and assess the prognostic significance of EGFR and ILA in patients with non-small cell lung cancer (NSCLC). METHODS: We reviewed 797 consecutive patients with a histologically proven diagnosis of primary NSCLC from January 2013 to October 2018. Of these, 109 patients with NSCLC were found to have concomitant ILA. Multivariate logistic regression analysis was used to identify the significant clinical and computed tomography (CT) findings in predicting EGFR mutations. Cox proportional hazard models were used to identify significant prognostic factors. RESULTS: EGFR mutations were identified in 22 of 109 tumors (20.2%). Multivariate analysis showed that the models incorporating clinical, tumor CT and ILA CT features yielded areas under the receiver operating characteristic curve (AUC) values of 0.749, 0.838, and 0.849, respectively. When combining the three models, the independent predictive factors for EGFR mutations were non-fibrotic ILA, female sex, and small tumor size, with an AUC value of 0.920 (95% confidence interval[CI]: 0.861-0.978, p < 0.001). In the multivariate Cox model, EGFR mutations (hazard ratio = 0.169, 95% CI = 0.042-0.675, p = 0.012; 692 days vs. 301 days) were independently associated with extended overall survival compared to the wild-type. CONCLUSION: Non-fibrotic ILA independently predicts the presence of EGFR mutations, and the presence of EGFR mutations rather than non-fibrotic ILA serves as an independent good prognostic factor for patients with NSCLC.

Multimodality Imaging Evaluation of Nasal Rhabdomyosarcoma in Adults: A Case Report and Literature Review.

BACKGROUND: Alveolar rhabdomyosarcoma (ARMS) predominantly affects adolescents aged 10-15 years and is distinguished by its high aggressiveness and adverse prognosis compared with other sarcomas. It exhibits a pronounced tendency for lymphatic and hematogenous metastases at early stages. ARMS commonly manifests in the limbs and genitourinary system, with occurrences in the head and neck region being relatively uncommon. The role of CT, MRI, and 18F-FDG positron emission tomography combined with computed tomography (PET/CT) in the diagnostic process of ARMS is yet to be fully established. CASE REPORT: We report the case of a 49-year-old woman who presented with hematological nasal discharge for one month. CT imaging revealed a soft tissue mass in the left nasal cavity. MRI demonstrated a marginally hypo- to isointense signal on T1-weighted images, a hyperintense signal on T2-weighted images, and heterogeneous enhancement post-contrast. 18F-FDG PET/CT identified a hypermetabolic lesion located within the left nasal cavity. Surgical intervention entailed the excision of the left intranasal mass and the skull base lesion. Postoperative pathological analysis indicated ARMS. CONCLUSION: Sinus ARMS is notably malignant and associated with a dismal prognosis. Accurate diagnosis depends on histopathological and immunohistochemical evaluation, complemented by genetic analysis for specific chromosomal translocations and fusion genes. Imaging techniques, including CT, MRI, and PET/CT, are crucial for assessing lesion extent and metastasis, supporting disease diagnosis, informing treatment choices, facilitating surgical planning, and monitoring response to therapy.

Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.

Purpose: To develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs). Material and methods: The study encompassed a cohort of 942 patients, involving examinations of 1076 vertebrae through X-ray, CT, and MRI across three distinct hospitals. The OVFs were categorized as class 0, 1, or 2 based on the Assessment System of Thoracolumbar Osteoporotic Fracture. The dataset was divided randomly into four distinct subsets: a training set comprising 712 samples, an internal validation set with 178 samples, an external validation set containing 111 samples, and a prospective validation set consisting of 75 samples. The ResNet-50 architectural model was used to implement deep transfer learning (DTL), undergoing -pre-training separately on the RadImageNet and ImageNet datasets. Features from DTL and radiomics were extracted and integrated using X-ray images. The optimal fusion feature model was identified through least absolute shrinkage and selection operator logistic regression. Evaluation of the predictive capabilities for OVFs classification involved eight machine learning models, assessed through receiver operating characteristic curves employing the "One-vs-Rest" strategy. The Delong test was applied to compare the predictive performance of the superior RadImageNet model against the ImageNet model. Results: Following pre-training separately on RadImageNet and ImageNet datasets, feature selection and fusion yielded 17 and 12 fusion features, respectively. Logistic regression emerged as the optimal machine learning algorithm for both DLR models. Across the training set, internal validation set, external validation set, and prospective validation set, the macro-average Area Under the Curve (AUC) based on the RadImageNet dataset surpassed those based on the ImageNet dataset, with statistically significant differences observed (P<0.05). Utilizing the binary "One-vs-Rest" strategy, the model based on the RadImageNet dataset demonstrated superior efficacy in predicting Class 0, achieving an AUC of 0.969 and accuracy of 0.863. Predicting Class 1 yielded an AUC of 0.945 and accuracy of 0.875, while for Class 2, the AUC and accuracy were 0.809 and 0.692, respectively. Conclusion: The DLR model, based on the RadImageNet dataset, outperformed the ImageNet model in predicting the classification of OVFs, with generalizability confirmed in the prospective validation set.

CT-derived vertebral bone mineral density is a useful biomarker to predict COVID-19 outcome.

The low vertebral bone computed tomography (CT) Hounsfield unit values measured on CT scans reflect low bone mineral density (BMD) and are known as diagnostic indicators for osteoporosis. The potential prognostic significance of low BMD defined by vertebral bone CT values for the coronavirus disease 2019 (COVID-19) remains unclear. This study aimed to assess the impact of BMD on the clinical outcome in Japanese patients with COVID-19 and evaluate the association between BMD and critical outcomes, such as high-flow nasal cannula, non-invasive and invasive positive pressure ventilation, extracorporeal membrane oxygenation, or death. We examined the effects of COVID-19 severity on the change of BMD over time. This multicenter retrospective cohort study enrolled 1132 inpatients with COVID-19 from the Japan COVID-19 Task Force database between February 2020 and September 2022. The bone CT values of the 4th, 7th, and 10th thoracic vertebrae were measured from chest CT images. The average of these values was defined as BMD. Furthermore, a comparative analysis was conducted between the BMD on admission and its value 3 months later. The low BMD group had a higher proportion of critical outcomes than did the high BMD group. In a subanalysis stratifying patients by epidemic wave according to onset time, critical outcomes were higher in the low BMD group in the 1st-4th waves. Multivariable logistic analysis of previously reported factors associated with COVID-19 severity revealed that low BMD, chronic kidney disease, and diabetes were independently associated with critical outcomes. At 3 months post-infection, patients with oxygen demand during hospitalization showed markedly decreased BMD than did those on admission. Low BMD in patients with COVID-19 may help predict severe disease after the disease onset. BMD may decrease over time in patients with severe COVID-19, and the impact on sequelae symptoms should be investigated in the future.