Search Results (410)

Accurate and consistent forensic bruise assessment is critical in ensuring positive clinical and legal outcomes for victims of violence. In this study, a framework for automated bruise detection is presented that, for the first time, integrates narrowband alternate-light-source (ALS) forensic imaging and ambient white light imaging. This evaluation framework is designed to address long-standing issues with respect to equitable performance across skin tones and lighting scenarios via a combination of novel model diagnostic strategies. In particular, skin-tone balancing during training and testing, threshold-sensitivity analysis, and embedding-similarity partitioning are employed to quantify the model robustness and deployment trade-offs that arise in forensic image analysis. Models were implemented with ImageNet-pretrained backbones and trained on a unique, multi-annotator full-consensus dataset comprising both white-light and ALS (415 nm and 450 nm) images. The protocol emphasizes three axes of operational relevance: (1) illumination composition in training (W/ALS ratio); (2) subgroup fairness via targeted balancing; and (3) model operating-point selection (confidence and IoU thresholds) informed by confidence-stability metrics and bootstrapped uncertainty estimates. Systematic W/ALS ratio sweeps indicate peak accuracy under ALS-dominant training and declining performance as the proportion of white-light images increases within the training set. Skin-tone balancing reduced failure rates for darker skin tones but increased overprediction in some demographic subgroups. Embedding-similarity and seen/unseen injury analyses demonstrate inflated generalization under image-level partitioning. Ultimately, the findings suggest that future researchers and developers should employ injury-level data partitioning and ensure a weighted balance of ALS images during training. Full article

Background/Objectives: Esophageal cancer is one of the major global causes of cancer mortality, and the 5-year survival rate remains below 20% because many cases are detected late. In this study, a Spectral-Aided Vision Enhancer (SAVE) algorithm was utilized to convert conventional white-light endoscopic images (WLI) into hyperspectral-like narrow-band imaging (NBI) images for machine-learning classification of Dysplasia, Normal, and Squamous Cell Carcinoma (SCC). Methods: A total of 762 WLI images obtained from Kaohsiung Medical University were augmented to 1074 using the Al bumentations library, employing vertical flipping, horizontal flipping, and rotations. The SAVE conversion pipeline employs a 24-patch Macbeth color checker for calibration, γ-correction, CIE XYZ transformation, and multivariate regression to interpolate spectral bands, yielding an average color difference of 2.79 (CIEDE2000) from true NBI. The training outcomes and performance metrics illustrate the versatility of the machine learning/deep learning models—Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN)—which were trained and evaluated on both the original WLI and SAVE datasets. Performance metrics were analyzed based on precision, recall, accuracy, and F1-score. Results: The CNN sample achieved an accuracy of 100 percent on SAVE data, compared to 93 percent for WLI. The accuracy of RF improved, with WLI at 91% and SAVE at 96%, while SVM increased from 79% to 84%. These improvements indicate the diagnostically valuable spectral variations that can be amplified with SAVE, resulting in significant enhancements in pre-cancer/SCC sensitivity. Conclusions: The proposed SAVE method demonstrates significant potential for enhancing endoscopic imaging and advancing computer-aided diagnosis in esophageal cancer screening, with applicability in other gastrointestinal imaging scenarios as well. Full article

With the continuous development of complex marine hydrocarbon reservoirs, broadband seismic data have shown growing advantages in revealing abundant stratigraphic information. Affected by acquisition conditions and stratigraphic attenuation, the acquired seismic data commonly suffer from narrow bandwidth, and conventional broadband processing techniques are incapable of optimizing the overall frequency band. This study proposes a coordinated high- and low-frequency broadband compensation method based on adaptive weight fusion to effectively extend the frequency bandwidth of seismic data. Firstly, wavefield separation is used to suppress ghost reflections, compensate low-frequency effective signals, and restore the continuity of the low-frequency spectrum. Then, based on the spectrum extrapolation method of maximum entropy spectrum estimation, a spectrum prediction model is established to achieve the continuation of high-frequency effective signals. Finally, in combination with the signal-to-noise ratio of each frequency band, the adaptive weight fusion algorithm is applied for weighted summation. The acquired broadband seismic data feature a continuous spectrum and balanced energy, greatly improving seismic imaging quality. Comparative results obtained using conventional processing methods verify that the proposed method can significantly improve stratigraphic continuity and wave group characteristics. Full article

Background/Objectives: Ulcerative colitis (UC)-associated neoplasia (UCAN) often presents as flat lesions with indistinct margins, and biopsy sensitivity is limited. Therefore, we evaluated endoscopic criteria to distinguish UCAN from sporadic neoplasia, assessing the accuracy of endoscopic ultrasonography (EUS) for invasion depth and the role of endoscopic submucosal dissection (ESD) as a “total biopsy.” Methods: We reviewed 212 endoscopically treated neoplastic lesions in UC-affected mucosa (April 2016–January 2025). We compared preoperative diagnoses using macroscopic type, pit pattern, and the Japan Narrow-Band Imaging Expert Team classification with final histology. We compared depth estimates with pathology in 10 UCAN-suspected lesions undergoing EUS. Lesions < 2 cm underwent conventional endoscopic resection, whereas those ≥ 2 cm underwent ESD. Results: No UCAN was found in 189 lesions < 2 cm. Among 23 ESD lesions, 8 suspected sporadic lesions were non-UCAN. Of 15 UCAN-suspected lesions, 8 were UCAN, 6 sporadic, and 1 inflammatory. For positive T1b or deeper invasion, the sensitivity, specificity, positive and negative predictive values, and overall accuracy of EUS were 50.0%, 100%, 100%, 88.9%, and 90.0%, respectively. EUS depth assessment agreed with pathology in 9/10 cases; nine lesions were T1a or shallower, and one was T1b. Third-layer thickening occurred in two lesions—both UCAN—including the T1b cancer. In ESD cases, redness and a VI pit pattern were independent predictors of UCAN. Conclusions: EUS-based depth assessment is useful for determining optimal treatment strategies. Beyond therapy, ESD enables comprehensive histologic assessment of the entire lesion, functioning as a total biopsy to guide management while preserving bowel function. Full article

Background: Early detection of oral potentially malignant disorders (OPMDs) and early-stage oral squamous cell carcinoma (OSCC) remains a major clinical challenge, as initial lesions often present with subtle or nonspecific findings during conventional white-light examination. Narrow-band imaging (NBI) enhances visualization of mucosal microvasculature and may improve the identification of dysplastic and malignant transformation. Methods: A narrative review of the literature was conducted in the PubMed, Scopus and Google Scholar databases. Studies published between January 2012 and January 2025 evaluating clinical applications of NBI in oral mucosal lesions, OPMDs, or OSCC were included. Results: NBI enhances visualization of intraepithelial papillary capillary loops (IPCLs), whose morphological alterations correlate with epithelial dysplasia and malignant transformation. Evidence suggests high diagnostic sensitivity (up to 87–100%) and specificity (approximately 83–96%) for detecting high-grade dysplasia and early OSCC. NBI also improves biopsy site selection, reduces sampling error, and supports surveillance of high-risk patients. Conclusions: NBI represents a valuable adjunctive diagnostic tool in oral medicine and dentistry. Although it does not replace histopathological examination, its integration into clinical assessment may enhance early cancer detection and improve management of patients with OPMDs. Full article

This study investigates subauroral phenomena during the main phase of the 10 May 2024 geomagnetic storm using a combination of ground-based observations from the WD IZMIRAN observatory (magnetometer, ionosonde, and all-sky imager) and Global Self-consistent Model of the Thermosphere, Ionosphere, Protonosphere (GSM TIP) simulations. During 18:00–20:00 UT, we identified the simultaneous occurrence of ionospheric signatures of Polarization Jets (PJ)/Sub-Auroral Ion Drifts (SAID) and Strong Thermal Emission Velocity Enhancement (STEVE) over Kaliningrad, consistent with previously reported PJ/SAID identification from DMSP drift velocity measurements. This identification is supported by: (1) characteristic purple emissions (clearly visible in all three channels) moving rapidly westward; (2) U-shaped structures in ionogram sequences; (3) the reproduction of supersonic westward plasma drifts within a narrow latitudinal band by the first-principles model; and (4) observed and simulated significant Ne depletion. The estimated ion drift velocity from all-sky imaging (assuming an emission altitude of 200 km) is consistent with GSM TIP simulations, which predicted PJ/SAID velocities of ~750 m/s driven by a latitudinally narrow (~3°) but longitudinally extended (>50°) poleward electric field (40 mV/m). Simulations reveal that this PJ/SAID phenomenon causes a reversal of the zonal thermospheric wind at 250 km and induces Ne disturbances across the 200–700 km altitude range. The electron temperature enhancement (up to 1500 K) exhibits a “falling drop” shape, peaking at 350 km, while ion heating exceeds 150 K. The neutral temperature shows a dual response: frictional heating at 120–160 km and localized cooling at 175–250 km due to drop in electron density. Additionally, an increase in atomic oxygen concentration was predicted within the 90–200 km range across the PJ/SAID longitudinal sector. Full article

Background: The plantaris muscle (PM) shows substantial variability in its proximal belly attachments. Although often deemed vestigial, specific variants may narrow or reshape the popliteal corridor and contribute to vascular (popliteal artery entrapment syndromes, PAES) and neural conflict (TN, CPN, sural nerves). Despite abundant anatomical descriptions of the plantaris, its contribution to neurovascular compression has not been organised into a classification-linked, imaging-integrated framework. Objective: To synthesise adult and foetal anatomical data with clinical–radiological evidence into a classification-linked framework that stratifies vascular and neural compression risk by proximal PM variants, and to propose an integrated risk matrix and variant-directed diagnostic/operative pathway. Methods: Narrative, classification-centred review centred on the Olewnik schema (Types I–VI) and multi-headed/accessory variants. We mapped variant geometry to (1) physiological compromise on provoked Doppler US and (2) anatomical correlates on MRI/MR angiography (MRA) (axial “band sign”), deriving graded risk for vascular and neural axes and an integrated, action-oriented grade per limb. Results: Baseline risk is low for canonical/compact footprints (Type I–IA, Type V), moderate for capsular-junction patterns (Types II/III), and potentially higher-risk for lateral linkage (Type IV; iliotibial band (ITB)/Kaplan fibres continuity) and multi-headed configurations (duplication, bifurcation, ≥3–4 heads; accessory proximal slips). The integrated matrix upgrades risk for a clear band sign, reproducible compromise on provoked Doppler US, or multi-headed/Type IV anatomy and downgrades when rigorous provocation is negative and muscle volume is small. We provide a variant-indexed imaging checklist, common pitfalls (e.g., Type IV misread as ITB thickening; multi-headed variants misread as cyst/tumour), and operative checkpoints to target capsular clefts, lateral bands, tunnels, and accessory slips. Conclusions: A classification-linked, imaging-integrated approach clarifies which proximal PM variants are plausibly associated with neurovascular entrapment (based on case-level evidence) and aligns work-up with targeted decompression and may improve diagnostic precision and inform surgical planning. Clinical relevance: The framework operationalises variant naming in reports, standardises dynamic provocation and axial mapping, and prioritises variants considered higher risk (Type IV; multi-headed) for early multidisciplinary review. Given that most clinical signals derive from case reports/series (Level IV), these recommendations are inferential and should be applied with clinical judgement. Full article

Background: Artificial intelligence (AI) is increasingly applied in pulmonary endoscopy, including diagnostic bronchoscopy, interventional pulmonology and endobronchial imaging. Advances in computer vision, machine learning and robotic systems have expanded the potential for automated lesion detection, navigation to peripheral pulmonary lesions, and real-time procedural support. However, the current evidence base remains heterogeneous, and translational challenges persist. Methods: This review summarizes current applications and developments of AI across white-light bronchoscopy (WLB), image-enhanced bronchoscopy (e.g., narrow-band imaging and autofluorescence imaging), endobronchial ultrasound (EBUS), virtual and robotic bronchoscopies, and workflow optimization and training. The authors also examine the methodological limitations, regulatory considerations, and implementation barriers that affect translation into routine practice. Results: Reported developments include deep learning-based models for mucosal abnormality detection, lymph-node characterization during EBUS-guided transbronchial needle aspiration (EBUS-TBNA), improved lesion localization, and reduction in operator-dependent variability. Additionally, AI-assisted simulation platforms and decision-support tools are reshaping training paradigms. Nevertheless, most studies remain retrospective or single-center, with limited external validation, dataset heterogeneity, unclear model explainability, and incomplete integration into clinical workflows. Conclusions: AI has the potential to support lesion detection, navigation, and training in pulmonary endoscopy. However, robust prospective validation, standardized datasets, transparent model reporting, robust data governance, multidisciplinary collaboration, and careful integration into clinical practice are required before widespread adoption. Full article

Parameters of reflected light, measured in narrow or broad spectral bands, are widely analyzed for remote and proximal sensing of plant responses to stressors. Specifically, parameters of reflectance in red (R), green (G), and blue (B) spectral bands measured using simple color images can be sensitive to characteristics of plants. The conventional view is that RGB reflectance primarily reveals long-term changes in plants (days, weeks, etc.). In this study, we investigated light-induced changes in RGB reflectance in wheat (Triticum aestivum L.) and pea (Pisum sativum L.) leaves. Illumination increased this reflectance for about 10 min in wheat and about 15–20 min in pea; these changes relaxed after light intensity was decreased. The changes in RGB reflectance were strongly related to the effective quantum yield of photosystem II and non-photochemical quenching of chlorophyll fluorescence under high light intensity; these relations were absent under low light intensity. We hypothesized that changes in both RGB reflectance and photosynthetic parameters were related to the light-induced changes in chloroplast localization. A simple mathematical model of optical properties and photosynthesis in leaves was developed; results of the model-based analysis supported the proposed hypothesis. Experimental analysis of the dynamics of light transmittance additionally supported this hypothesis. Our results thus show that RGB imaging can be sensitive to fast changes in plants. Full article

Soil health monitoring is critical for the sustainable management of the black soil region, a key resource for global food security. However, traditional field surveys are constrained by high operational costs, limited spatial coverage, and low temporal frequency, making them inadequate for high-resolution and time-sensitive soil monitoring. The recently launched ZY1-02E satellite, equipped with an advanced hyperspectral imager, offers a new potential data source, yet its capability for quantitative soil modelling requires rigorous cross-sensor validation. This study conducts a cross-sensor evaluation of ZY1-02E and its predecessor, ZY1-02D, for mapping soil organic matter (SOM) and soil texture (sand, silt, and clay) in Northeast China. Optimal spectral indices were constructed through exhaustive band combination and correlation screening, and quantitative inversion models were established using a hybrid framework integrating Random Frog feature selection with Gaussian Process Regression (GPR) and Boosting Trees, based on synchronous ground observations. Results demonstrate strong cross-sensor consistency, with spectral indices showing significant linear correlations (${\mathrm{R}}^2>0.65$) between ZY1-02E and ZY1-02D. Furthermore, the quantitative retrieval models applied to ZY1-02E imagery achieved robust performance, with cross-sensor retrieval consistency exceeding ${\mathrm{R}}^2=0.60$ for all parameters and SOM exhibiting the highest agreement (${\mathrm{R}}^2=0.74$). These findings confirm the radiometric stability and algorithm transferability of ZY1-02E, demonstrating its capability to generate soil parameter products comparable to ZY1-02D without extensive model recalibration. The validated interoperability of the twin-satellite constellation substantially enhances temporal observation capacity during the narrow bare-soil window, effectively mitigating cloud-induced data gaps in high-latitude agricultural regions. Importantly, the enhanced monitoring framework provides a scalable technical paradigm for high-frequency hyperspectral soil mapping, offering critical spatial decision support for precision fertilization, soil degradation mitigation, and conservation tillage management in the Mollisol belt. Full article

Wide-swath longwave infrared (LWIR) imaging from Low Earth Orbit (LEO) demands fast optics and rectilinear (F-tan) mapping for thermal mapping and multi-frame registration. Achieving an F/1.2 aperture with a 112° diagonal field of view (FOV) and distortion within ±5% is challenging, as mapping constraints and field-dominant off-axis aberrations become strongly coupled at large chief-ray angles. The low-distortion target is not only a geometric specification, but also a practical requirement that reduces peripheral compression, helps maintain edge-detail consistency, and lowers digital de-warping effort in the processing pipeline. While traditional LWIR secondary imaging is predominantly restricted to narrow-field cooled systems for cold-stop constraints, the proposed architecture utilizes a curved intermediate image to effectively decouple mapping formation in the field-dominant front objective from aperture-dominant correction in the rear group. Using chalcogenide glasses, the lens achieves a 5.7 mm effective focal length within a 186.9 mm total track. Analysis over the 8–12 μm band confirms performance approaching the diffraction limit at the 50 lp/mm Nyquist frequency alongside stable geometric fidelity across the full field. Thermal analysis from −40 °C to 80 °C and Monte Carlo tolerance analysis demonstrate stable imaging performance and manufacturing feasibility, confirming the effectiveness of the proposed design approach. Full article

High quality factor (Q factor) resonant metasurfaces enable efficient mid-infrared (MIR) upconversion, yet their narrow operating bandwidths severely limit practical broadband detection and imaging applications. Although high Q magnetic toroidal dipole (MTD) modes exhibit outstanding momentum space ($k$-space) stability in linear optics, their application in nonlinear processes has primarily been confined to degenerate second-harmonic generation (SHG), leaving complex non-degenerate processes such as sum-frequency generation (SFG) largely unexplored. Here, we propose a tunable MIR upconversion platform based on an all-dielectric gallium phosphide (GaP) dimer metasurface. Breaking the in-plane symmetry to trigger Brillouin zone folding excites robust MTD quasi-guided modes (MTD-QGM), tightly confining the locally enhanced optical fields within the highly nonlinear GaP nanostructure. Synchronizing this high Q resonance with a spatially overlapping pump mode yields an exceptional SFG conversion efficiency of $7.9\times {10}^{-4}$, successfully translating a 3101.8 nm MIR signal to the 903 nm near-infrared band. Crucially, the intrinsic $k$-space stability of the MTD-QGM enables continuous, broadband upconversion through simple angle tuning. This mechanism effectively overcomes the narrow-band limitations characteristic of typical symmetry-protected resonators, establishing a robust paradigm for room-temperature MIR detection. Full article

To be acceptable for precision agriculture applications, satellite imagery must be converted to surface reflectance. To be economical, the analytics must be delivered completely by automation and free of error to preserve farmer trust. CMAC (closed-form method for atmospheric correction) software was tested for this application along with established applications, Sen2Cor and FORCE—all three software packages seek to retrieve Sentinel-2 surface reflectance. Forty-three Sentinel-2 images were selected of farmland near Burley, Idaho, corrected by this software and evaluated as reflectance time series extracted from three irrigated corn fields. NDVI of irrigated corn presented an ideal test of precision and accuracy for surface reflectance retrieval. If accurate and precise, a plotted time series will smoothly display logistic growth during crop establishment followed by a plateau, then gradual senesce before harvest: divergences from this pattern indicate errors. CMAC followed the expected smooth pattern for this dataset while, in both FORCE and Sen2Cor, divergence occurred both above and below the CMAC time series for NDVI and from individual spectral band reflectance. These divergences were systematic and directly related to the degree of atmospheric effect—overcorrecting when clear, under-correcting when hazy. Only CMAC provided surface reflectance with the accuracy required for precision agriculture: applicable for Sentinel-2 as Tier 1 data and when haze or cloud- affected and unreliable, as Tier 2 infill from daily smallsat data. Additional analyses of the CMAC-corrected dataset were performed that were also applicable to Tier 2 daily-cadence smallsat data. Further analysis of this dataset indicated that, applied as NDVI, the application of broadband NIR, though sensitive to atmospheric water vapor, exhibited minimal errors compared to NDVI from narrowband NIR. These CMAC-corrected data provided an application to index crop start dates and were capable of distinguishing the uncorrectable data of cloud, cloud shadow, or extreme haze for removal under complete automation. Full article

Background/Objectives: Psoriatic disease is a systemic inflammatory condition associated with increased cardiometabolic risk, but the impact of contemporary systemic therapies and narrowband ultraviolet B (NB-UVB) phototherapy on vascular and systemic inflammatory markers remains incompletely characterized. We aimed to systematically synthesize prospective evidence on treatment-associated changes in vascular inflammation and systemic inflammatory biomarkers in adults with moderate-to-severe psoriatic disease. Specifically, we evaluated changes assessed by 18F-FDG PET/CT imaging and circulating biomarkers following biologic therapies or NB-UVB phototherapy. Methods: We systematically searched MEDLINE, Embase, Web of Science, Scopus, and CENTRAL from inception to 31 January 2026 for prospective interventional and observational studies in adults with psoriasis or psoriatic arthritis treated with biologic agents targeting TNF-α, IL-12/23, IL-17, or IL-23, or with NB-UVB phototherapy. Eligible studies were required to report serial assessments of vascular inflammation by 18F-FDG PET/CT (typically aortic target-to-background ratio) and/or systemic inflammatory markers (high-sensitivity C-reactive protein, interleukin-6, TNF-α, GlycA, or hematologic indices such as the neutrophil-to-lymphocyte ratio) over at least 8 weeks of follow-up. We imposed no language restrictions and included only full-text, peer-reviewed prospective studies. Risk of bias was evaluated using RoB 2 for randomized trials and ROBINS-I for nonrandomized studies. Random-effects meta-analyses were prespecified for outcomes reported by at least two clinically comparable studies; however, because of substantial heterogeneity in reporting and methodology, effect estimates were summarized using a structured narrative synthesis. Results: Thirteen prospective studies (n ≈ 900 adults, published 2015–2025) met inclusion criteria, including four studies with serial 18F-FDG PET/CT imaging and one additional PET/CT study providing baseline observational data on vascular inflammation, as well as eight biomarker-focused prospective cohorts. Across randomized mechanistic trials and observational studies, biologic therapies reduced aortic target-to-background ratio by approximately 6–12% over 12–24 weeks (e.g., mean change from 2.42 to 2.18 with TNF-α inhibition and from 2.51 to 2.20 with IL-17 blockade), and no study reported worsening of PET-derived vascular indices under effective systemic treatment. Biologic and other systemic therapies produced concordant reductions in hs-CRP (typically by 30–50%), IL-6, TNF-α, GlycA, and blood-count-derived indices including neutrophil-to-lymphocyte ratio, with biomarker improvements frequently paralleling reductions in cutaneous disease activity and cardiometabolic risk markers. Two NB-UVB cohorts demonstrated significant hs-CRP reductions of roughly 20–30% and modulation of vitamin D-related inflammatory proteins, suggesting systemic anti-inflammatory effects, although these changes appeared less pronounced than with biologic therapy and were not accompanied by vascular imaging. Conclusions: Contemporary systemic psoriasis therapies, particularly biologic agents targeting the IL-23/Th17 axis and TNF-α, are associated with consistent reductions in aortic vascular inflammation and broad improvements in systemic inflammatory biomarkers, whereas NB-UVB phototherapy confers more modest but measurable systemic anti-inflammatory effects, although the current evidence does not allow differentiation between individual biologic classes in terms of magnitude of effect. Although reductions in vascular and systemic inflammatory markers were observed across therapies targeting TNF-α, IL-12/23, IL-17, and IL-23, the small number of mechanistic imaging studies and absence of head-to-head comparisons do not allow robust differentiation between biologic classes or support a uniform class effect. The convergence of imaging and biomarker data reinforces psoriasis as a clinically relevant model of inflammation-driven atherosclerosis and supports the concept that effective control of psoriatic inflammation may contribute to cardiovascular risk modification, highlighting the need for integrated cardiovascular risk assessment in routine care. However, the imaging evidence base remains limited to four small mechanistic PET/CT studies with relatively short follow-up, which constrains the strength and generalizability of conclusions regarding vascular inflammation. Larger, adequately powered, event-driven prospective trials with standardized imaging and biomarker endpoints are needed to determine whether these vascular and systemic anti-inflammatory effects translate into reduced cardiovascular events in psoriatic disease; because of methodological and reporting heterogeneity across the 13 included studies, these conclusions are based on a structured narrative synthesis rather than a formal quantitative meta-analysis. PROSPERO registration number: CRD420261296646. Full article

Background/Objectives: The early detection of oral squamous cell carcinoma (OSCC), especially when in the presence of oral potentially malignant disorders (OPMDs), may be challenging and would assist in improving poor OSCC survival rates reported in the literature. We conducted a systematic review to evaluate the utility of adjunctive aids that could assist during clinical examination of the oral cavity to identify suspicious mucosal lesions. Methods: Three databases (CENTRAL, PubMed/MEDLINE, Embase) were screened, limiting results from 2015 to November 2025. Inclusion criteria were: articles written in English; investigating the diagnostic accuracy of diagnostic visual aids compared to conventional oral examination under white light in the assessment of oral mucosal lesions. Extracted data were analysed narratively. Studies not reporting diagnostic accuracy using biopsy results as the gold standard were excluded. Results: The search produced 137 articles; after removing duplicates, 105 were screened through inclusion/exclusion criteria, leading to 17 papers included in the review. Eight articles investigated diagnostic accuracy of narrow band imaging (NBI), seven visually enhanced lesion scopes (VELscopes), one Glasses for Oral Cancer Curing Light Exposed Screening (GOCCLES), one ViziLite chemiluminescence system, and two toluidine blue (TB). Conclusions: High study heterogeneity and lack of randomized clinical trials limit the conclusions of this review. In this context, among the investigated visual aids for expert use, NBI (sensitivity 85–100%, specificity 75–98%) emerges as the most promising tool (VELscope sensitivity 76–87.1%, specificity 21.4–90%; GOCCLES 66%, 48%; ViziLite 77.3%, 27.8%, TB 56.8–91%, 65.3–68%), due to its ability to highlight sub epithelial vascular abnormalities, considered as early indicators of dysplastic or neoplastic progression even. None of the investigated visual aids seem suited for screening purposes/use by the general dentist. Full article