Is there enough evidence supporting the clinical adoption of clear cell likelihood score (ccLS)? An updated systematic review and meta-analysis.

OBJECTIVE: To review the evidence for clinical adoption of clear cell likelihood score (ccLS) for identifying clear cell renal cell carcinoma (ccRCC) from small renal masses (SRMs). METHODS: We distinguished the literature on ccLS for identifying ccRCC via systematic search using PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data until 31 March, 2024. The risk of bias and concern on application was assessed using the modified quality assessment of diagnostic accuracy studies (QUADAS-2) tool. The level of evidence supporting the clinical adoption of ccLS for identifying ccRCC was determined based on meta-analyses. RESULTS: Eight MRI studies and three CT studies were included. The risk of bias and application were mainly related to the index test and flow and timing, due to incomplete imaging protocol, unclear rating process, and inappropriate interval between imaging and surgery. The diagnostic odds ratios (95% confidence intervals) of MRI and CT ccLS were 14.69 (9.71-22.22; 6 studies, 1429 SRM, 869 ccRCC), and 5.64 (3.34-9.54; 3 studies, 296 SRM, 147 ccRCC), respectively, for identifying ccRCC from SRM. The evidence level for clinical adoption of MRI and CT ccLS were both rated as weak. MRI ccLS version 2.0 potentially has better diagnostic performance than version 1.0 (1 study, 700 SRM, 509 ccRCC). Both T2-weighted-imaging with or without fat suppression might be suitable for MRI ccLS version 2.0 (1 study, 111 SRM, 82 ccRCC). CONCLUSION: ccLS shows promising diagnostic performance for identifying ccRCC from SRM, but the evidence for its adoption in clinical routine remains weak. CRITICAL RELEVANCE STATEMENT: Although clear cell likelihood score (ccLS) demonstrates promising performance for detecting clear cell renal cell carcinoma, additional evidence is crucial to support its routine use as a tool for both initial diagnosis and active surveillance of small renal masses. KEY POINTS: Clear cell likelihood score is designed for the evaluation of small renal masses. Both CT and MRI clear cell likelihood scores are accurate and efficient. More evidence is necessary for the clinical adoption of a clear cell likelihood score.

The policies on the use of large language models in radiological journals are lacking: a meta-research study.

OBJECTIVE: To evaluate whether and how the radiological journals present their policies on the use of large language models (LLMs), and identify the journal characteristic variables that are associated with the presence. METHODS: In this meta-research study, we screened Journals from the Radiology, Nuclear Medicine and Medical Imaging Category, 2022 Journal Citation Reports, excluding journals in non-English languages and relevant documents unavailable. We assessed their LLM use policies: (1) whether the policy is present; (2) whether the policy for the authors, the reviewers, and the editors is present; and (3) whether the policy asks the author to report the usage of LLMs, the name of LLMs, the section that used LLMs, the role of LLMs, the verification of LLMs, and the potential influence of LLMs. The association between the presence of policies and journal characteristic variables was evaluated. RESULTS: The LLM use policies were presented in 43.9% (83/189) of journals, and those for the authors, the reviewers, and the editor were presented in 43.4% (82/189), 29.6% (56/189) and 25.9% (49/189) of journals, respectively. Many journals mentioned the aspects of the usage (43.4%, 82/189), the name (34.9%, 66/189), the verification (33.3%, 63/189), and the role (31.7%, 60/189) of LLMs, while the potential influence of LLMs (4.2%, 8/189), and the section that used LLMs (1.6%, 3/189) were seldomly touched. The publisher is related to the presence of LLM use policies (p < 0.001). CONCLUSION: The presence of LLM use policies is suboptimal in radiological journals. A reporting guideline is encouraged to facilitate reporting quality and transparency. CRITICAL RELEVANCE STATEMENT: It may facilitate the quality and transparency of the use of LLMs in scientific writing if a shared complete reporting guideline is developed by stakeholders and then endorsed by journals. KEY POINTS: The policies on LLM use in radiological journals are unexplored. Some of the radiological journals presented policies on LLM use. A shared complete reporting guideline for LLM use is desired.

Low-dose Ultra-high-resolution Photon-Counting Detector CT for Visceral Artery CT Angiography: A Preliminary Study.

RATIONALE AND OBJECTIVES: To validate the image quality of low-dose ultra-high-resolution (UHR) scanning mode of photon-counting detector CT (PCD-CT) for visceral artery computed tomography angiography (CTA). MATERIAL AND METHODS: We prospectively enrolled 57 patients each in the full dose (FD) and low-dose (LD) protocols, respectively, to undergo abdominal CT scans using the UHR mode on a PCD-CT system (NAEOTOM Alpha), between April 2023 and September 2023. Both the FD data and LD data were then reconstructed into two series of images: (a) 0.2 mm slice thickness, reconstruction kernel Bv48, quantum iterative reconstruction (QIR) 4; (b)1 mm slice thickness, Bv40, QIR 3. The signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of seven arteries were objectively measured. The image noise, vessel sharpness, overall quality, and visibility of nine arteries were subjectively assessed by three radiologists. RESULTS: The SNRs and CNRs of 0.2 mm reconstruction set was inferior to that of 1 mm reconstruction set (p < 0.001 for all the arteries and noise), however, the image quality of 0.2 mm reconstruction set was higher than that of 1 mm reconstruction set in qualitative evaluation especially for tiny arteries in Volume-rendered (VR) image (p < 0.001). The SNRs and CNRs were not significantly higher for FD group than LD group on the same slice thickness except for SNRs of common hepatic artery, splenic artery and bilateral renal arteries in 0.2 mm reconstruction set. In the comparison on image quality between normal weight and overweight patients within the same reconstruction set, the results showed that low-dose scan did not significantly impact the image quality in overweight patients. The ratings of visibility of nine visceral arteries were not significantly different among FD and LD at the same thickness reconstruction set except for superior mesenteric artery (p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in axial image; p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in coronal image, respectively) and left gastric artery (p = 0.002 and p < 0.001 for 0.2 mm and 1 mm reconstruction set in VR image, respectively). CONCLUSION: The low-dose UHR scanning mode of PCD-CT has proven to be adequate for the clinical evaluation of visceral arteries. Utilizing a reconstruction with a slice thickness of 0.2 mm could enhance arterial depiction, particularly for small vessels.

Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

BACKGROUND: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined. PURPOSE: To determine the optimal settings of the DLIR algorithm for abdominal low-keV VMI. MATERIAL AND METHODS: The portal-venous phase computed tomography (CT) scans of 109 participants with 152 lesions were reconstructed into four image series: VMI at 50 keV using adaptive statistical iterative reconstruction (Asir-V) at 50% blending (AV-50); and VMI at 40 keV using AV-50 and DLIR at medium (DLIR-M) and high strength (DLIR-H). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of nine anatomical sites were calculated. Noise power spectrum (NPS) using homogenous region of liver, and edge rise slope (ERS) at five edges were measured. Five radiologists rated image quality and diagnostic acceptability, and evaluated the lesion conspicuity. RESULTS: The SNR and CNR values, and noise and noise peak in NPS measurements, were significantly lower in DLIR images than AV-50 images in all anatomical sites (all P < 0.001). The ERS values were significantly higher in 40-keV images than 50-keV images at all edges (all P < 0.001). The differences of the peak and average spatial frequency among the four reconstruction algorithms were significant but relatively small. The 40-keV images were rated higher with DLIR-M than DLIR-H for diagnostic acceptance (P < 0.001) and lesion conspicuity (P = 0.010). CONCLUSION: DLIR provides lower noise, higher sharpness, and more natural texture to allow 40 keV to be a new standard for routine VMI reconstruction for the abdomen and DLIR-M gains higher diagnostic acceptance and lesion conspicuity rating than DLIR-H.

Numerical simulation study of nanoparticle diffusion in gray matter.

Purpose: Nanomedicine-based approaches have shown great potential in the treatment of central nervous system diseases. However, the fate of nanoparticles (NPs) within the brain parenchyma has not received much attention. The complexity of the microstructure of the brain and the invisibility of NPs make it difficult to study NP transport within the grey matter. Moreover, regulation of NP delivery is not fully understood. Methods: 2D interstitial system (ISS) models reflecting actual extracellular space (ECS) were constructed. A particle tracing model was used to simulate the diffusion of the NPs. The effect of NP size on NP diffusion was studied using numerical simulations. The diffusion of charged NPs was explored by comparing experimental and numerical simulation data, and the effect of cell membrane potential on the diffusion of charged NPs was further studied. Results: The model was verified using previously published experimental data. Small NPs could diffuse efficiently into the ISS. The diffusion of charged NPs was hindered in the ISS. Changes in cell membrane potential had little effect on NP diffusion. Conclusion: This study constructed 2D brain ISS models that reflected the actual ECS and simulated the diffusion of NPs within it. The study found that uncharged small NPs could effectively diffuse within the ISS and that the cell membrane potential had a limited effect on the diffusion of charged NPs. The model and findings of this study can aid the design of nanomedicines and nanocarriers for the diagnosis and treatment of brain diseases.

Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT.

BACKGROUND: To assess the improvement of image quality and diagnostic acceptance of thinner slice iodine maps enabled by deep learning image reconstruction (DLIR) in abdominal dual-energy CT (DECT). METHODS: This study prospectively included 104 participants with 136 lesions. Four series of iodine maps were generated based on portal-venous scans of contrast-enhanced abdominal DECT: 5-mm and 1.25-mm using adaptive statistical iterative reconstruction-V (Asir-V) with 50% blending (AV-50), and 1.25-mm using DLIR with medium (DLIR-M), and high strength (DLIR-H). The iodine concentrations (IC) and their standard deviations of nine anatomical sites were measured, and the corresponding coefficient of variations (CV) were calculated. Noise-power-spectrum (NPS) and edge-rise-slope (ERS) were measured. Five radiologists rated image quality in terms of image noise, contrast, sharpness, texture, and small structure visibility, and evaluated overall diagnostic acceptability of images and lesion conspicuity. RESULTS: The four reconstructions maintained the IC values unchanged in nine anatomical sites (all p > 0.999). Compared to 1.25-mm AV-50, 1.25-mm DLIR-M and DLIR-H significantly reduced CV values (all p < 0.001) and presented lower noise and noise peak (both p < 0.001). Compared to 5-mm AV-50, 1.25-mm images had higher ERS (all p < 0.001). The difference of the peak and average spatial frequency among the four reconstructions was relatively small but statistically significant (both p < 0.001). The 1.25-mm DLIR-M images were rated higher than the 5-mm and 1.25-mm AV-50 images for diagnostic acceptability and lesion conspicuity (all P < 0.001). CONCLUSIONS: DLIR may facilitate the thinner slice thickness iodine maps in abdominal DECT for improvement of image quality, diagnostic acceptability, and lesion conspicuity.

Association between quadriceps fat pad edema and patellofemoral osteoarthritis: a quantitative Q-Dixon-based magnetic resonance imaging (MRI) analysis.

Background: Anterior knee pain (AKP) is a common symptom of patellofemoral osteoarthritis (PFOA). There is limited prospective evidence supporting the relationships between patellofemoral maltracking parameters, AKP, and PFOA. Thus, this prospective cross-sectional study aimed to determine the association between quadriceps fat pad (QFP) edema and patellofemoral maltracking in patients with chronic AKP and to evaluate the feasibility and diagnostic performance of a PFOA assessment using fat fraction (FF) and T2* based on Q-Dixon. Methods: This was a cross-sectional study with prospective data collection. Patients with chronic AKP were recruited from an orthopedic outpatient magnetic resonance imaging (MRI) waiting room at Shanghai Tongren Hospital between November 1, 2022, and April, 30, 2023. Exclusion criteria included age of <18 years, knee trauma, major internal derangement, prior surgery/arthroscopy, pre-existing joint diseases, and contraindications to MRI. MRI was performed using a 3.0-T instrument, and patellofemoral maltracking parameters were measured. Patellofemoral feature-relevant items, including patellar cartilage defects, patellar bone marrow lesions (BMLs), patellar osteophytes, anterior femoral osteophytes, Hoffa synovitis, and synovitis-effusion, from the semi-quantitative MRI Osteoarthritis Knee Score (MOAKS) were measured. The Anterior Knee Pain Scale (AKPS) was used to assess pain and function. FF/T2* measurement differences between groups and their associations with maltracking metrics, osteoarthritis grading based on the Iwano grading system, MOAKS, and AKPS, were investigated. Based on Iwano grading, the participants were categorized as having no-PFOA (n=40), mild PFOA (n=40), and advanced PFOA (n=40). Chi-squared and one-way analysis of variance were used to assess potential differences between the groups. Spearman's correlation test was used to analyze the correlation between the morphological parameters, AKPS, Iwano grade, MOAKS, and MRI quantitative values. Receiver operating characteristic (ROC) curves assessed the area under the curve (AUC), sensitivity, and specificity of quantitative values for distinguishing PFOA from no-PFOA. Results: Among the 120 included patients, those in the mild (86.2±8.5) and advanced (83.9±9.5) PFOA groups had significantly lower AKPS scores than those in the no-PFOA group (88.8±7.3) (P=0.03). The mean FF and T2* values of the QFP were significantly higher in the no-PFOA group than those in the mild and advanced PFOA groups (P<0.001 for FF and P=0.02 for T2*). Quantitative data on the QFP and patellofemoral maltracking parameters showed no association. FF (r=-0.686, P<0.001) and T2* (r=-0.314, P=0.008) showed a negative correlation with the Iwano grade. The AUCs for PFOA diagnosis were 0.906 [95% confidence interval (CI), 0.853-0.960] (FF) and 0.744 (95% CI, 0.657-0.831) (T2*). Conclusions: QFP FF and T2* were not associated with patellofemoral maltracking parameters but with increased PFOA in patients with AKP, suggesting that QFP abnormalities play a role in PFOA. Therefore, a quantitative QFP assessment (FF and T2*) based on Q-Dixon technology could be a convenient and reliable new imaging biomarker for PFOA severity during clinical diagnosis, treatment, and follow-up.

Just give the contrast? Appraisal of guidelines on intravenous iodinated contrast media use in patients with kidney disease.

OBJECTIVE: To appraise the quality of guidelines on intravenous iodinated contrast media (ICM) use in patients with kidney disease, and to compare the recommendations among them. METHODS: We searched four literature databases, eight guideline libraries, and ten homepages of radiological societies to identify English and Chinese guidelines on intravenous ICM use in patients with kidney disease published between January 2018 and June 2023. The quality of the guidelines was assessed with the Scientific, Transparent, and Applicable Rankings (STAR) tool. RESULTS: Ten guidelines were included, with a median STAR score of 46.0 (range 28.5-61.5). The guidelines performed well in "Recommendations" domain (31/40, 78%), while poor in "Registry" (0/20, 0%) and "Protocol" domains (0/20, 0%). Nine guidelines recommended estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73 m2 as the cutoff for referring patients to discuss the risk-benefit balance of ICM administration. Three guidelines further suggested that patients with an eGFR < 45 mL/min/1.73 m2 and high-risk factors also need referring. Variable recommendations were seen in the acceptable time interval between renal function test and ICM administration, and that between scan and repeated scan. Nine guidelines recommended to use iso-osmolar or low-osmolar ICM, while no consensus has been reached for the dosing of ICM. Nine guidelines supported hydration after ICM use, but their protocols varied. Drugs or blood purification therapy were not recommended as preventative means. CONCLUSION: Guidelines on intravenous ICM use in patients with kidney disease have heterogeneous quality. The scientific societies may consider joint statements on controversial recommendations for variable timing and protocols. CRITICAL RELEVANCE STATEMENT: The heterogeneous quality of guidelines, and their controversial recommendations, leave gaps in workflow timing, dosing, and post-administration hydration protocols of contrast-enhanced CT scans for patients with kidney diseases, calling for more evidence to establish a safer and more practicable workflow. KEY POINTS: • Guidelines concerning iodinated contrast media use in kidney disease patients vary. • Controversy remains in workflow timing, contrast dosing, and post-administration hydration protocols. • Investigations are encouraged to establish a safer iodinated contrast media use workflow.

Bioinformatics and Experimental Study Revealed LINC00982/ miR-183-5p/ABCA8 Axis Suppresses LUAD Progression.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major health challenge worldwide with an undesirable prognosis. LINC00982 has been implicated as a tumor suppressor in diverse human cancers; however, its role in LUAD has not been fully characterized. METHODS: Expression level and prognostic value of LINC00982 were investigated in pan-cancer and lung cancer from The Cancer Genome Atlas (TCGA) project. Differential expression analysis based on the LINC00982 expression level was performed in LUAD followed by gene set enrichment analysis (GSEA) and functional enrichment analyses. The association between LINC00982 expression and tumor immune microenvironment characteristics was evaluated. A potential ceRNA regulatory axis was identified and experimentally validated. RESULTS: We found that LINC00982 expression was downregulated and correlated with poor prognosis in LUAD. Enrichment analyses revealed that LINC00982 could inhibit DNA damage repair and cell proliferation, but enhance tumor metabolic reprogramming. We identified a competing endogenous RNA network involving LINC00982, miR-183-5p, and ATP-binding cassette subfamily A member 8 (ABCA8). Luciferase assays confirmed that miR-183-5p can interact with LINC00982 and ABCA8. Forced miR-183-5p expression reduced LINC00982 transcript levels and suppressed ABCA8 expression. CONCLUSIONS: Our findings revealed the LINC00982/miR-183-5p/ABCA8 axis as a potential therapeutic target in LUAD.

Impacts of Adaptive Statistical Iterative Reconstruction-V and Deep Learning Image Reconstruction Algorithms on Robustness of CT Radiomics Features: Opportunity for Minimizing Radiomics Variability Among Scans of Different Dose Levels.

This study aims to investigate the influence of adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) on CT radiomics feature robustness. A standardized phantom was scanned under single-energy CT (SECT) and dual-energy CT (DECT) modes at standard and low (20 and 10 mGy) dose levels. Images of SECT 120 kVp and corresponding DECT 120 kVp-like virtual monochromatic images were generated with filtered back-projection (FBP), ASIR-V at 40% (AV-40) and 100% (AV-100) blending levels, and DLIR algorithm at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) strength levels. Ninety-four features were extracted via Pyradiomics. Reproducibility of features was calculated between standard and low dose levels, between reconstruction algorithms in reference to FBP images, and within scan mode, using intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). The average percentage of features with ICC > 0.90 and CCC > 0.90 between the two dose levels was 21.28% and 20.75% in AV-40 images, and 39.90% and 35.11% in AV-100 images, respectively, and increased from 15.43 to 45.22% and from 15.43 to 44.15% with an increasing strength level of DLIR. The average percentage of features with ICC > 0.90 and CCC > 0.90 in reference to FBP images was 26.07% and 25.80% in AV-40 images, and 18.88% and 18.62% in AV-100 images, respectively, and decreased from 27.93 to 17.82% and from 27.66 to 17.29% with an increasing strength level of DLIR. DLIR and ASIR-V algorithms showed low reproducibility in reference to FBP images, while the high-strength DLIR algorithm provides an opportunity for minimizing radiomics variability due to dose reduction.

The endorsement of general and artificial intelligence reporting guidelines in radiological journals: a meta-research study.

BACKGROUND: Complete reporting is essential for clinical research. However, the endorsement of reporting guidelines in radiological journals is still unclear. Further, as a field extensively utilizing artificial intelligence (AI), the adoption of both general and AI reporting guidelines would be necessary for enhancing quality and transparency of radiological research. This study aims to investigate the endorsement of general reporting guidelines and those for AI applications in medical imaging in radiological journals, and explore associated journal characteristic variables. METHODS: This meta-research study screened journals from the Radiology, Nuclear Medicine & Medical Imaging category, Science Citation Index Expanded of the 2022 Journal Citation Reports, and excluded journals not publishing original research, in non-English languages, and instructions for authors unavailable. The endorsement of fifteen general reporting guidelines and ten AI reporting guidelines was rated using a five-level tool: "active strong", "active weak", "passive moderate", "passive weak", and "none". The association between endorsement and journal characteristic variables was evaluated by logistic regression analysis. RESULTS: We included 117 journals. The top-five endorsed reporting guidelines were CONSORT (Consolidated Standards of Reporting Trials, 58.1%, 68/117), PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses, 54.7%, 64/117), STROBE (STrengthening the Reporting of Observational Studies in Epidemiology, 51.3%, 60/117), STARD (Standards for Reporting of Diagnostic Accuracy, 50.4%, 59/117), and ARRIVE (Animal Research Reporting of In Vivo Experiments, 35.9%, 42/117). The most implemented AI reporting guideline was CLAIM (Checklist for Artificial Intelligence in Medical Imaging, 1.7%, 2/117), while other nine AI reporting guidelines were not mentioned. The Journal Impact Factor quartile and publisher were associated with endorsement of reporting guidelines in radiological journals. CONCLUSIONS: The general reporting guideline endorsement was suboptimal in radiological journals. The implementation of reporting guidelines for AI applications in medical imaging was extremely low. Their adoption should be strengthened to facilitate quality and transparency of radiological study reporting.

Robustness of Quantitative Diffusion Metrics from Four Models: A Prospective Study on the Influence of Scan-Rescans, Voxel Size, Coils, and Observers.

BACKGROUND: Quantitative diffusion metrics provide additional microstructural information of diseases. The robustness of quantitative diffusion metrics should be established before clinical application. PURPOSE: To evaluate the variability and reproducibility of quantitative diffusion MRI metrics. STUDY TYPE: Prospective. POPULATION: 14 volunteers (7 men; median age, range, 28, 26-59 years). FIELD STRENGTH/SEQUENCE: 3.0-T/Diffusion spectrum imaging. ASSESSMENT: Brain MRI studies were performed four times per subject: involving different combinations of coil types and voxel sizes. Regions of interest of 13 brain anatomical sites were drawn by one observer twice and another observer once to allow interobserver and intraobserver reproducibility assessment. Twenty-five quantitative metrics were calculated using four diffusion models. STATISTICAL TESTS: The variability was evaluated with coefficients of variation (CV), and quartile coefficient of dispersion (QCD). The reproducibility was assessed with intraclass correlation coefficient (ICC), and concordance correlation coefficient (CCC). Wilcoxon signed rank test was used to compare the influence of factors on robustness of quantitative diffusion metrics. A two-tailed P < 0.05 was considered statistically significant. RESULTS: The variability of quantitative diffusion metrics showed CV of 2.4%-68.2%, and QCD of 0.6%-48.2%, respectively. The reproducibility of scans using 20-channel coils with voxels of 2 × 2 × 2 mm3 and 3 × 3 × 3 mm3 , respectively (ICC 0.03-0.84, CCC 0.03-0.84) was significantly worse than that of repeated scans using a 20-channel coil with a voxel size of 2 × 2 × 2 mm3 (ICC of 0.74-0.97, CCC 0.74-0.97) and that of scans using 20- and 64-channel coils, respectively, with a voxel size of 2 × 2 × 2 mm3 (ICC 0.59-0.95, CCC 0.59-0.95). The intraobserver reproducibility (ICC 0.49-0.94, CCC 0.49-0.94) was significantly better than the interobserver reproducibility (ICC 0.28-0.91, CCC 0.28-0.91). DATA CONCLUSION: Our study indicated that the voxel size has a greater influence on the reproducibility of quantitative diffusion metrics than scan-rescans and coils. The reproducibility within one observer was higher than that between two observers. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Unveiling the role of hypoxic macrophage-derived exosomes in driving colorectal cancer progression.

The crosstalk between tumor cells and macrophages under hypoxic conditions has been acknowledged as a pivotal determinant in the progression of colorectal cancer (CRC). Previous research has underscored the significance of exosomes derived from hypoxic tumor cells in facilitating tumor progression through inducing the polarization of macrophages towards the M2-like phenotype. The precise influence of hypoxic macrophage-derived exosomes (HMDEs) on the progression of CRC has not yet been fully elucidated. The objective of this study was to investigate the role of HMDEs in the progression of CRC. We discovered that there was an elevated release of exosomes derived from macrophages in hypoxic conditions. Additionally, the hypoxia-induced macrophage-derived exosomes played a crucial role in promoting the progression of CRC. We have also demonstrated that HMDEs have the ability to induce cell cycle transition and inhibit cell apoptosis, thereby promoting the growth of CRC cells. Furthermore, the underlying molecular mechanisms of these effects have been identified. The overexpression of Hif-1α results in its direct interaction with distinct regions (-521- -516 bp and -401- -391 bp) of the Hsp90 promoter during hypoxic circumstances. This binding event led to the overexpression of Hsp90 and the subsequent elevation of Hsp90 protein levels within HMDEs. Importantly, the crucial interaction between Hsp90 and Lats1 resulted in the deactivation of Lats1 and the inhibition of Yap phosphorylation. Ultimately, this series of events lead to the deactivation of the Hippo signaling pathway. Our in vivo and in vitro studies presented compelling evidence for the crucial role of hypoxic macrophage-derived exosomal Hsp90 in promoting CRC progression through the inhibition of the Hippo signaling pathway. These findings represented a significant advancement in our comprehension of the complex interplay between macrophages and CRC cells under hypoxic conditions.

Long-term, real-time and label-free live cell image processing and analysis based on a combined algorithm of CellPose and watershed segmentation.

Developing a rapid and quantitative method to accurately evaluate the physiological abilities of living cells is critical for tumor control. Many experiments have been conducted in the field of biology in an attempt to measure the proliferation and movement abilities of cells, but existing methods cannot provide real-time and objective data for label-free cells. The quantitative imaging technique, including an automatic segmentation algorithm for individual label-free cells, has been a breakthrough in this regard. In this study, we develop a combined automatic image processing algorithm of CellPose and watershed segmentation for the long-term and real-time imaging of label-free cells. This method shows strong reliability in cell identification regardless of cell densities, allowing us to obtain accurate information about the number and proliferation ability of the target cells. Additionally, our results also suggest that this method is a reliable way to assess real-time data on drug cytotoxicity, cell morphology, and cell movement ability.

Association among peripatellar fat pad edema and related patellofemoral maltracking parameters: a case-control magnetic resonance imaging study.

BACKGROUND: The peripatellar fat pads are critical for protective cushioning during movement, and their endocrine function has been shown to affect osteoarthritis. Magnetic resonance imaging (MRI) is frequently used to visualize edema of the peripatellar fat pads due to injury. In this study, we aimed to assess the relationship between peripatellar fat pad edema and patellofemoral maltracking MRI parameters and investigate the association among cases of peripatellar fat pad edema. METHODS: Age- and sex-matched peripatellar fat pad edema cases were identified and divided into superolateral Hoffa, quadriceps, and prefemoral groups. Images were assessed according to tibial tuberosity lateralization, trochlear dysplasia, patellar alta, patellar tilt, and bisect offset. McNemar's test or paired t-tests and Spearman's correlation were used for statistical analysis. Interobserver agreement was assessed with the intraclass correlation coefficient. RESULTS: Of 1210 MRI scans, 50, 68, and 42 cases were in the superolateral Hoffa, quadriceps, and prefemoral groups, respectively. Subjects with superolateral Hoffa fat pad edema had a lower lateral trochlear inclination (p = 0.028), higher Insall-Salvati (p < 0.001) and modified Insall-Salvati (p = 0.021) ratios, and lower patellotrochlear index (p < 0.001) than controls. The prefemoral group had a lower lateral trochlear inclination (p = 0.014) and higher Insall-Salvati (p < 0.001) and modified Insall-Salvati (p = 0.004) ratios compared with the control group. In contrast, the patellotrochlear index (p = 0.001) was lower. Mean patellar tilt angle (p = 0.019) and mean bisect offset (p = 0.005) were significantly different between cases and controls. The quadriceps group showed no association. Superolateral Hoffa was positively correlated with prefemoral (p < 0.001, r = 0.408) and negatively correlated with quadriceps (p < 0.001, r = -0.500) fat pad edema. CONCLUSIONS: Superolateral Hoffa and prefemoral fat pad edemas were associated with patellar maltracking parameters. Quadriceps fat pad edema and maltracking parameters were not associated. Superolateral Hoffa fat pad edema was positively correlated with prefemoral and negatively correlated with quadriceps fat pad edema.

Characterization of the substernal space with computed tomography imaging in patients with and without median sternotomy: Assessing a novel implant location for extravascular defibrillation lead placement.

BACKGROUND: Implantable cardioverter-defibrillators (ICDs) provide clinically significant therapy for the prevention of sudden cardiac death. This study aimed to characterize the substernal space using computed tomography (CT) in patients with and without prior midline sternotomy to investigate the feasibility of substernal ICD lead implantation in post-sternotomy patients. METHODS: High-quality electrocardiogram-gated CT images from 100 patients (71% male, average body mass index 23.5 ± 2.9) were retrospectively collected, including 50 patients with prior midline sternotomy (S-group) and 50 patients with no prior sternotomy (NS-group). Distances were measured from the retrosternal surface to the epicardial surface of the heart and segmented into four regions from the xiphoid tip and superiorly along the sternum. RESULTS: Results generally showed a measurable but narrower average sternum-to-heart distance in the prior sternotomy group compared to the non-sternotomy group in all four regions (p < .05). In the S-group, the sternum-to-heart distances across all regions ranged from 0 to 32.0 mm, while in the NS-group, the distances ranged from 0 to 39.9 mm. CONCLUSION: Small but measurable separations between the heart and sternum were observed in patients with prior sternotomy, particularly near the xiphoid region, indicating the potential viability of extravascular substernal ICD lead implantation in post-sternotomy patients.

An overview of meta-analyses on radiomics: more evidence is needed to support clinical translation.

OBJECTIVE: To conduct an overview of meta-analyses of radiomics studies assessing their study quality and evidence level. METHODS: A systematical search was updated via peer-reviewed electronic databases, preprint servers, and systematic review protocol registers until 15 November 2022. Systematic reviews with meta-analysis of primary radiomics studies were included. Their reporting transparency, methodological quality, and risk of bias were assessed by PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 2020 checklist, AMSTAR-2 (A MeaSurement Tool to Assess systematic Reviews, version 2) tool, and ROBIS (Risk Of Bias In Systematic reviews) tool, respectively. The evidence level supporting the radiomics for clinical use was rated. RESULTS: We identified 44 systematic reviews with meta-analyses on radiomics research. The mean ± standard deviation of PRISMA adherence rate was 65 ± 9%. The AMSTAR-2 tool rated 5 and 39 systematic reviews as low and critically low confidence, respectively. The ROBIS assessment resulted low, unclear and high risk in 5, 11, and 28 systematic reviews, respectively. We reperformed 53 meta-analyses in 38 included systematic reviews. There were 3, 7, and 43 meta-analyses rated as convincing, highly suggestive, and weak levels of evidence, respectively. The convincing level of evidence was rated in (1) T2-FLAIR radiomics for IDH-mutant vs IDH-wide type differentiation in low-grade glioma, (2) CT radiomics for COVID-19 vs other viral pneumonia differentiation, and (3) MRI radiomics for high-grade glioma vs brain metastasis differentiation. CONCLUSIONS: The systematic reviews on radiomics were with suboptimal quality. A limited number of radiomics approaches were supported by convincing level of evidence. CLINICAL RELEVANCE STATEMENT: The evidence supporting the clinical application of radiomics are insufficient, calling for researches translating radiomics from an academic tool to a practicable adjunct towards clinical deployment.

The prognostic value of myocardial salvage index by cardiac magnetic resonance in ST-segment elevation myocardial infarction patients: a systematic review and meta-analysis.

OBJECTIVE: To assess the prognostic value of myocardial salvage index (MSI) by cardiac magnetic resonance (CMR) in ST-segment elevation myocardial infarction (STEMI) patients. METHODS: We systematically searched PubMed, Embase, Web of Science, Cochrane Central, China National Knowledge Infrastructure, and Wanfang Data to identify primary studies reporting MSI in STEMI patients with major adverse cardiovascular events (MACE) comprised of death, myocardial reinfarction, and congestive heart failure. The MSI and MACE rates were pooled. The bias of risk was assessed using the Quality In Prognosis Studies tool. The evidence level was rated based on the meta-analysis of hazard ratio (HR) and 95% confidence interval (CI) of MSI for predicting MACE. RESULTS: Eighteen studies were included covering twelve unique cohorts. Eleven cohorts measured MSI using T2-weighted imaging and T1-weighted late gadolinium enhancement, while one cohort applied T2-mapping and T1-mapping. The pooled MSI (95% CI) was 44% (39 to 49%; 11 studies, 2946 patients), and the pooled MACE rate (95% CI) was 10% (7 to 14%; 12 studies, 311/3011 events/patients). Seven prognostic studies overall showed low risk of bias. The HR (95% CI) per 1% increase of MSI for MACE was 0.95 (0.92 to 0.98; 5 studies, 150/885 events/patients), and HR (95% CI) of MSI < median versus MSI > median for MACE was 5.62 (3.74 to 8.43; 6 studies, 166/1570 events/patients), both rated as weak evidence. CONCLUSIONS: MSI presents potential in predicting MACE in STEMI patients. The prognostic value of MSI using advanced CMR techniques for adverse cardiovascular events needs further investigation. CLINICAL RELEVANCE STATEMENT: Seven studies supported the MSI to serve as a predictor for MACE in STEMI patients, indicating its potential as a risk stratification tool to help manage expectations for these patients in clinical practice. KEY POINTS: • The pooled infarct size (95% CI) and area at risk (95% CI) were 21% (18 to 23%; 11 studies, 2783 patients) and 38% (34 to 43%; 10 studies, 2022 patients), respectively. • The pooled rates (95% CI) of cardiac mortality, myocardial reinfarction, and congestive heart failure were 2% (1 to 3%; 11 studies, 86/2907 events/patients), 4% (3 to 6%; 12 studies, 127/3011 events/patients), and 3% (1 to 5%; 12 studies, 94/3011 events/patients), respectively. • The HRs (95% CI) per 1% increase of MSI for cardiac mortality and congestive heart failure were 0.93 (0.91 to 0.96; 1 study, 14/202 events/patients) and 0.96 (0.93 to 0.99; 1 study, 11/104 events/patients), respectively, but the prognostic value of MSI for myocardial re-infraction has not been measured.

A systematic review of radiomics in giant cell tumor of bone (GCTB): the potential of analysis on individual radiomics feature for identifying genuine promising imaging biomarkers.

PURPOSE: To systematically assess the quality of radiomics research in giant cell tumor of bone (GCTB) and to test the feasibility of analysis at the level of radiomics feature. METHODS: We searched PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data to identify articles of GCTB radiomics until 31 July 2022. The studies were assessed by radiomics quality score (RQS), transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) statement, checklist for artificial intelligence in medical imaging (CLAIM), and modified quality assessment of diagnostic accuracy studies (QUADAS-2) tool. The radiomic features selected for model development were documented. RESULTS: Nine articles were included. The average of the ideal percentage of RQS, the TRIPOD adherence rate and the CLAIM adherence rate were 26%, 56%, and 57%, respectively. The risk of bias and applicability concerns were mainly related to the index test. The shortness in external validation and open science were repeatedly emphasized. In GCTB radiomics models, the gray level co-occurrence matrix features (40%), first order features (28%), and gray-level run-length matrix features (18%) were most selected features out of all reported features. However, none of the individual feature has appeared repeatably in multiple studies. It is not possible to meta-analyze radiomics features at present. CONCLUSION: The quality of GCTB radiomics studies is suboptimal. The reporting of individual radiomics feature data is encouraged. The analysis at the level of radiomics feature has potential to generate more practicable evidence for translating radiomics into clinical application.

Robustness of radiomics features of virtual unenhanced and virtual monoenergetic images in dual-energy CT among different imaging platforms and potential role of CT number variability.

OBJECTIVES: To evaluate robustness of dual-energy CT (DECT) radiomics features of virtual unenhanced (VUE) image and virtual monoenergetic image (VMI) among different imaging platforms. METHODS: A phantom with sixteen clinical-relevant densities was scanned on ten DECT platforms with comparable scan parameters. Ninety-four radiomic features were extracted via Pyradiomics from VUE images and VMIs at energy level of 70 keV (VMI70keV). Test-retest repeatability was assessed by Bland-Altman analysis. Inter-platform reproducibility of VUE images and VMI70keV was evaluated by coefficient of variation (CV) and quartile coefficient of dispersion (QCD) among platforms, and by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) between platform pairs. The correlation between variability of CT number radiomics reproducibility was estimated. RESULTS: 92.02% and 92.87% of features were repeatable between scan-rescans for VUE images and VMI70keV, respectively. Among platforms, 11.30% and 28.39% features of VUE images, and 15.16% and 28.99% features of VMI70keV were with CV < 10% and QCD < 10%. The average percentages of radiomics features with ICC > 0.90 and CCC > 0.90 between platform pairs were 10.00% and 9.86% in VUE images and 11.23% and 11.23% in VMI70keV. The CT number inter-platform reproducibility using CV and QCD showed negative correlations with percentage of the first-order radiomics features with CV < 10% and QCD < 10%, in both VUE images and VMI70keV (r2 0.3870-0.6178, all p < 0.001). CONCLUSIONS: The majority of DECT radiomics features were non-reproducible. The differences in CT number were considered as an indicator of inter-platform DECT radiomics variation. Critical relevance statement: The majority of radiomics features extracted from the VUE images and the VMI70keV were non-reproducible among platforms, while synchronizing energy levels of VMI to reduce the CT number value variability may be a potential way to mitigate radiomics instability.