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Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence

Development of the zebrafish foveal analogue: a quantitative atlas of high-acuity zone growth and retinal regionalisation.

The vertebrate retina contains specialised regions for high-acuity vision, exemplified by the human fovea and its zebrafish analogue, the high-acuity zone (HAZ). Despite the widespread use of zebrafish to model retinal disease, a stage-resolved quantitative reference describing normal eye, photoreceptor layer (PRL) and lens growth has been lacking. Here, we apply contrast-enhanced micro-computed tomography (micro-CT) to construct the first three-dimensional micro-CT normative atlas of wild-type zebrafish eye development across five larval stages [3, 5, 7, 10 and 18 days post-fertilisation (dpf)], mapping circumferential PRL thickness, eye and lens morphology, and compartment growth rates. Regional PRL thickening within the temporo-ventral region of the expected HAZ emerged by 5 dpf and was sustained by a localised redistribution of growth, persisting and extending towards the optic nerve through 18 dpf. The PRL, lens and eye grew through four phases, alternating between disproportionate PRL expansion and coordinated growth, while the eye remodelled from a nasal-dominant to a temporo-ventral-dominant form. This regional specialisation was protracted relative to gross ocular growth and could proceed independently of it, paralleling the extended postnatal maturation of the human fovea. This atlas provides a quantitative baseline for distinguishing disease-induced changes from normal variation, supporting zebrafish models of foveal hypoplasia and related disorders.

Animals

Comparative in silico analysis of Apis mellifera immune responses to Varroa destructor and Tropilaelaps mercedesae: Common and mite-specific molecular signatures.

Parasitic mites Varroa destructor and Tropilaelaps mercedesae represent major threats to global honey bee (Apis mellifera) health and productivity, yet comparative molecular insights into host responses remain limited. To address this, we systematically compiled published studies (2015-2025) reporting genes associated with honey bee interactions with V. destructor (11 studies, 87 genes), T. mercedesae (4 studies, 35 genes), and hygienic behavior (6 studies, 44 genes). Gene identifiers were harmonized to the Amel_HAv3.1 genome assembly, yielding three non-redundant sets: 64 Varroa-associated, 34 Tropilaelaps-associated, and 44 hygienic behavior-associated genes. Venn analysis identified 10 overlapping genes (including A0A088A8D5, A0A088ADL8, ABAE_APIME, Def1, Def2, Gapdh, HYTA_APIME, Imd, LOC726783, and Vg), suggesting conserved defense mechanisms, while 41 and 24 genes were uniquely associated with Varroa and Tropilaelaps, respectively. Enrichment analyses revealed Varroa-responsive genes were enriched in immune processes, chitin catabolism, and signaling pathways (Toll/Imd, MAPK, Wnt). Tropilaelaps-associated genes were enriched for antibacterial defense and stress response, with Toll/Imd signaling as the sole significantly enriched pathway. Overlapping genes reinforced core innate immunity activation. Protein-protein interaction network centrality analysis identified key hub genes: Def1, HYTA_APIME, ABAE_APIME, PPO, Imd, PGRP-LC, Vg for Varroa; and ACPH1_APIME, MRJP1, Vg, LOC726783 for Tropilaelaps. Results demonstrate that, despite differences in mite biology, honey bees show a conserved immune response against both parasites, centered on antibacterial defense, humoral immunity, and activation of the Toll/Imd pathway. Although limited by the in-silico nature and research asymmetries reflecting Tropilaelaps' emergence, this curated resource establishes a comprehensive framework for elucidating shared and distinct molecular defense mechanisms. Ultimately, this approach prioritizes diagnostic markers and candidate genes for functional validation and breeding strategies to enhance colony resilience against mite‑driven disease globally.

Animals

Emerging Principles in Spatial Functional Genomics.

Spatial transcriptomic and proteomic atlases have enabled mapping of gene programs within intact tissues, but these measurements remain largely descriptive and do not define the mechanisms controlling tissue biology. Pooled CRISPR screening provides scalable causal interrogation of gene function but remains largely confined to dissociated systems that lack spatial context. In vivo spatial functional genomics (SFG) bridges these approaches by integrating genetic perturbations with in situ transcriptomic and proteomic readouts to measure gene function within intact tissue ecosystems. By preserving spatial organization, SFG enables interpretation of perturbations through effects on cell-cell interactions, diffusible signals, multicellular niches, and tissue architecture. Here, we outline key design axes of SFG: perturbation strategy, barcoding strategy, and phenotypic readout. We discuss computational challenges, including spatial autocorrelation, neighborhood dependence, and context-aware null modeling, and highlight how SFG reveals non-cell-autonomous, architecture-dependent mechanisms of gene function, advancing toward predictive models of tissue organization and gene function.

Genomics

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans

Implicit and explicit statistical learning in reading: Evidence from a randomized controlled-learning study and computational modeling.

A key challenge in reading acquisition is understanding how learners extract the complex probabilistic mappings between print, meaning, and sound. Statistical learning (SL) theory offers a mechanistic account of how such mappings are acquired, whether implicitly through exposure or explicitly through instruction. We conducted a randomized controlled-learning study in Chinese, a writing system characterized by multiple sub-lexical regularities linking orthography, semantics, and phonology. Ninety-five 2nd-3rd graders with or at risk for dyslexia were randomly assigned to one of three groups: an implicit-SL training group exposed to repeated lexical and sublexical orthography-semantics-phonology associations, an explicit-SL training group receiving the same input plus explicit instruction on the sublexical print-sound mapping, and a no-SL control group. Both SL groups outperformed controls on the characters they were trained on, as well as on untrained characters that required generalization. However, only the explicit group demonstrated abstraction of print-sound mapping to novel items. Neural network simulations further revealed distinct mechanisms supporting implicit and explicit SL, consistent with a dual-system account of reading acquisition. Together, these findings (1) clarify how implicit and explicit learning distinctly support the discovery of statistical structure in written language and (2) underscore the implicit-explicit dual learning mechanism underlying reading acquisition.

Humans

Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.

This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.

Neoplasms

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans

Shielding performance and clinical applicability of lead-free materials in computed tomography.

Owing to the high radiation exposure associated with computed tomography (CT) examinations and the image quality degradation caused by conventional radiation shielding materials, this study evaluated the dose reduction performance and image quality maintenance potential of a newly developed lead-free composite shielding material. This material was composed of bismuth, tungsten, tungsten carbide, aluminium, and polyurethane. Phantom-based dose measurements demonstrated that the shielding material achieved dose reduction rates ranging from 17.6% to 37.6%, depending on tube voltage. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and changes in tube current-time product (mAs) under a scout-based automatic exposure control (AEC) protocol were analysed according to the presence or absence of the shielding material across regions. For the clinical evaluation, CT scans were performed on four patients. Furthermore, the images were reviewed to evaluate whether this material affected image quality. The shielding material exhibited radiation reduction levels comparable to those reported in previous studies. SNR and CNR analyses showed minor statistical variations in certain regions; however, most differences were not statistically significant, and even significant differences remained within a range that did not compromise diagnostic image quality. Under the scout-based AEC protocol, the use of the shielding material resulted in less than 1% variation in mAs values. No visually perceptible artefacts or clinically significant image quality degradation were observed. The proposed composite shielding material demonstrated the potential to mitigate some limitations of conventional shielding materials and showed preliminary clinical feasibility as an adjunctive strategy for radiation dose reduction in CT examinations.

Radiation Protection

The utility of 18F-fluorodeoxyglucose PET/computed tomography in relapsing polychondritis: a systematic review and meta-analysis.

Relapsing polychondritis is a rare chronic autoimmune inflammation of the cartilage associated with life-threatening respiratory complications. Currently, no clear role of imaging modalities such as 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) is defined in the literature. This systematic review and meta-analysis provide current evidence on the PET-positivity rate and utility in relapsing polychondritis. Prospective or retrospective studies with more than five patients of suspected relapsing polychondritis who underwent 18F-FDG PET/CT during their management and reported a PET-positivity rate were included. Low-sample-size studies describing chondritis due to other aetiologies or utilizing PET-based radiopharmaceuticals other than FDG were excluded. A systematic search using relevant keywords was conducted across four databases (PubMed, Embase, Scopus and Web of Science) to include studies up to 25 April 2025. The Joanna Briggs Institute critical appraisal tools were used for risk-of-bias analysis. Data were analysed using the R software package (v4.3.1; 2023). Out of 962 articles, three with a total of 97 patients were included. With a pooled PET-positivity rate of 94% [95% confidence interval (CI): 73-99%, I2 = 0%, P = 0.76] and a pooled baseline SUVmax of 4.0 (95% CI: 3.5-4.6, I2 = 32%, P = 0.23), 18F-FDG PET identified asymptomatic cartilage involvement in more than 25% patients and PET parameters correlated well with inflammatory markers. It had a higher positivity rate for inaccessible sites, such as peripheral airways, and was crucial in treatment monitoring. The pooled PET-positivity rate of 18F-FDG PET in relapsing polychondritis is high but requires prospective large-sample-size studies to explore the diagnostic accuracy and prognostic implications of 18F-FDG PET in relapsing polychondritis.

Polychondritis, Relapsing

Baseline Computed Tomography Coronary Angiography and Polygenic Risk Profiles in Adults With Type 2 Diabetes: A Cross-Sectional Analysis From the VOLTAIRE Study.

AIMS: To characterise baseline clinical, anatomical, and genetic cardiovascular risk profiles in participants enrolled in the VOLTAIRE (Evaluation of Polygenic Scores and CT Imaging in Risk Factor Modification in Patients with Type 2 Diabetes) study and examine concordance across these domains. METHODS: This analysis included adults with T2D who completed baseline computed tomography coronary angiography (CTCA) and polygenic risk score (PRS) assessment prior to randomisation in the VOLTAIRE study. Coronary atherosclerosis was evaluated using coronary artery calcium (CAC) score and CTCA-derived stenosis severity. Clinical risk was assessed using the New Zealand Society for the Study of Diabetes 5-year cardiovascular risk calculator. Polygenic risk for coronary artery disease was assessed using a genome-wide PRS and categorised into tertiles. RESULTS: Among 126 participants with T2D (mean age 57.5 ± 8.7 years; 62.7% male), coronary atherosclerotic burden was highly heterogeneous: 34.9% had CAC = 0, whereas 19.8% had CAC ≥ 400. Moderate-to-severe coronary stenosis (≥ 50%) was present in 40.5% of participants overall, including 20.4% of those classified as low clinical risk. PRS distribution was variable (low 37.3%, intermediate 35.7%, high 27.0%). Overlap between anatomical, genetic, and clinical domains was limited, with only 8.7% of participants classified as high risk across all three. CONCLUSIONS: Substantial heterogeneity and limited overlap exist between anatomical, genetic, and clinical cardiovascular risk measures in T2D. These findings support a multimodal approach to risk assessment integrating imaging and genetic profiling. TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov; ID: NCT07091162.

Aged

Novel non-contrast computed tomography parameters for predicting spontaneous stone passage and surgical requirement in ureteral stones: The role of ureteral wall thickness and dilatation ratio.

We investigated the predictive value of standard non-contrast computed tomography (NCCT) measurements, the ureteral dilatation ratio (DDR) and intraluminal urine stasis markers, for spontaneous stone passage (SSP) versus surgical intervention in patients with ureteral stones. We also evaluated ureteral wall thickness (UWT) as a practical clinical marker. This retrospective study included 461 patients diagnosed with ureteral stones via NCCT. Patients were categorised into two groups based on clinical outcomes: the spontaneous passage group (MET; n&#x2009;=&#x2009;229) and the endoscopic surgery group (URS; n&#x2009;=&#x2009;232). Stone volume, stone density (HU), UWT, DDR and intraluminal urine attenuation values were measured for all patients. Independent risk factors were identified using a multivariate logistic regression model and clinical cut-off values were determined via ROC curve analysis. Stone volume, density, UWT and hydronephrosis grade were all significantly higher in the URS group. Multivariate regression analysis revealed that increased UWT (OR: 5.03, 95% CI: 3.66-6.90; p&#x2009;<&#x2009;0.001) was the strongest independent predictor of surgery. Higher DDR (OR: 1.88; p&#x2009;=&#x2009;0.003), advanced hydronephrosis, stone volume, and density also increased surgical risk. A UWT cut-off &#x2265;&#x2009;2.97&#xa0;mm predicted surgery with 84.8% sensitivity and 84.3% specificity (AUC: 0.872). A DDR cut-off >&#x2009;1.79 yielded 81.7% specificity and 40.4% sensitivity. UWT weakly correlated with stone volume (r&#x2009;=&#x2009;0.145), indicating wall thickening reflects an inflammatory response rather than a mere mechanical consequence. UWT is a superior predictor of SSP failure, supported by increased DDR as a highly specific complementary risk factor. These parameters could help clinicians to identify patients who would benefit from early surgical counselling and intervention rather than prolonged conservative management.

Humans

Comprehensive assessment of vasospastic angina using coronary computed tomography angiography: synergistic value of the presence of myocardial bridge, perivascular inflammation, and myocardial extracellular volume fraction.

AIMS: Coronary computed tomography angiography (CCTA) has evolved beyond anatomical assessment to include sophisticated tissue characterization. While an elevated perivascular fat attenuation index around the right coronary artery (FAI-RCA) is known to reflect coronary inflammation in vasospastic angina (VSA), recurrent vasospasms may also induce chronic subclinical myocardial injury and subsequent remodelling, potentially associated with an increased myocardial extracellular volume fraction (ECV). However, the diagnostic integration of ECV and FAI-RCA for identifying VSA in patients with angina with non-obstructive coronary arteries (ANOCA) remains to be elucidated. METHODS AND RESULTS: This study included consecutive ANOCA patients who underwent CCTA with a dedicated ECV protocol, followed by an invasive spasm provocation test. Comprehensive CCTA analysis quantified both FAI-RCA and the transmural ECV gradient (the difference between endocardial and epicardial ECV: ECVEndo - ECVEpi). Of the 100 patients analysed (mean age: 65.3 &#xb1; 11.8 years; 55% male), 27 were diagnosed with VSA. Multivariable logistic regression analysis identified transmural ECV gradient [odds ratio (OR): 1.12, 95% confidence interval (CI): 1.01-1.25], presence of myocardial bridging (MB) (OR: 3.49, 95% CI: 1.25-9.74), and high FAI-RCA (> -70.95 Hounsfield units [HU]) (OR: 5.79, 95% CI: 2.06-16.30) as significant independent predictors of VSA (all P < 0.05). Notably, the integration of transmural ECV gradient provided incremental diagnostic value beyond FAI-RCA and MB, as assessed by the Net Reclassification Improvement and Integrated Discrimination Improvement. CONCLUSION: A multi-parametric CCTA approach potentially identifies patients at high risk for VSA. The significant association of the transmural ECV gradient with VSA suggests that myocardial remodelling imaging provides a novel diagnostic window into the cumulative myocardial impact of vasospasm, independent of active adipose tissue inflammation and the presence of MB.

Humans

Linked-color imaging with computer-aided detection and the proximal adenoma miss rate: a randomized tandem trial.

BACKGROUND AND AIMS: Linked-color imaging (LCI) aids the detection and characterization of lesions. Computer-aided detection (CADe) systems have been introduced to improve lesion detection during colonoscopy. Although several studies have been reported regarding LCI, few have investigated the combination of LCI and CADe. This study aimed to evaluate the efficacy of LCI with CADe colonoscopy compared to conventional white-light colonoscopy. METHODS: A single-center, randomized tandem trial was conducted. Participants referred for first-time colonoscopy after fecal immunochemical test (FIT)-positive, asymptomatic screening, or surveillance colonoscopy were randomized (1:1) to undergo CADe-assisted colonoscopy of LCI or white-light imaging (WLI) in the right side of the colon. The primary outcome was adenoma miss rate (AMR) in the right side of the colon. Secondary outcomes included polyp miss rate (PMR), diminutive adenoma miss rate (dAMR), sessile serrated lesion miss rate (SSLMR), advanced adenoma miss rate, advanced neoplasia miss rate, flat-type lesion miss rate (FMR), and the differences in miss rates based on expertise. RESULTS: Among 232 randomized participants, 209 were analyzed (LCI/CADe: 102; WLI: 107). AMR (WLI: 39% vs LCI/CADe: 20%; P = .001), PMR (42% vs 18%; P < .001), and dAMR (42% vs 21%; P = .003) were significantly lower in the LCI/CADe arm, particularly among experts. SSLMR (46% vs 0%), advanced AMR (30% vs 0%), advanced neoplasia miss rate (25% vs 0%), and FMR (27% vs 5.6%) were lower in LCI/CADe, although without statistical significance. CONCLUSIONS: Compared to conventional colonoscopy, LCI with CADe colonoscopy resulted in a statistically significant decrease, especially in AMR. (UMIN 000050685).

Humans

In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5&#x202f;kcal/mol, Wogonin (-9.3&#x202f;kcal/mol) and Xanthohumol (-8.1&#x202f;kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans

Photon-counting detector computed tomography (PCD-CT) in multiple myeloma: a systematic review and trial sequential meta-analysis on image quality and radiation dose.

OBJECTIVES: To systematically review and perform a meta-analysis comparing the effects of PCD-CT versus EID-CT on image quality (sharpness) and radiation dose (CTDIvol) in patients with bone lesions due to multiple myeloma&#xa0;(MM). METHODS: A comprehensive search of PubMed, Embase, Scopus, and Cochrane Central was conducted from inception to October 2025. Studies comparing PCD-CT and EID-CT in MM patients were included. Methodological quality was assessed using ROBINS-I, and the certainty of evidence was assessed using GRADE. RESULTS: A total of 41 studies were identified that matched our search criteria. After duplicate removal and screening, five studies (n = 170 patients) were included in the systematic review, with four contributing to the meta-analysis. PCD-CT showed a significant pooled mean difference in image sharpness (mean difference, + 0.99 points; 95% CI, 0.62-1.37; p < 0.001). PCD-CT also demonstrated a reduction in radiation dose (mean difference, -4.95 milligrays; 95% CI, -8.39 to -1.50; p = 0.005). Trial sequential analysis (TSA) confirmed stability of pooled estimates, with conclusive evidence for image sharpness improvement, and suggestive yet incomplete evidence for radiation dose reduction. CONCLUSION: Compared to EID-CT in MM, PCD-CT significantly improves subjective image sharpness as supported by trial sequential analysis. Conventional meta-analysis suggested a reduction in radiation dose with PCD-CT; however, trial sequential analysis indicated that the cumulative evidence remains inconclusive. Further large-scale studies are suggested to confirm the magnitude of the radiation dose reduction benefit.

Humans