Imaging Techniques Research Articles

Neck lumps: Early Detection with Dental Magnetic Resonance Imaging?

Cervical lymphadenopathy can indicate a range of diseases, including infections, inflammation, and neoplastic processes. Accurate diagnosis is crucial for identifying the underlying cause and determining appropriate treatment. Diagnostic procedures include clinical examination, ultrasound, fine needle aspiration, biopsy, and imaging techniques. While conventional imaging methods such as X-ray and computed tomography (CT) have proven useful, they exhibit limitations in sensitivity and specificity, especially for soft tissue structures. Magnetic resonance imaging (MRI) provides superior soft tissue contrast, offering additional critical information for differential diagnosis. This article presents a case study of a 29-year-old male with a cervical mass. Advanced dental MRI protocols, including DESS, SPACE-SPAIR, and SPACE-STIR sequences, have significantly enhanced the imaging capabilities of the den-tomaxillofacial region, enabling the generation of high-resolution images of both hard and soft tissues. Especially, MR OPGs have demonstrated the capacity to identify early signs of potential pathology. These protocols have the potential to enhance early detection, thereby con-tributing to accurate diagnosis and effective treatment planning.

Deep learning based highly accurate transplanted bioengineered corneal equivalent thickness measurement using optical coherence tomography

Corneal transplantation is the primary treatment for irreversible corneal diseases, but due to limited donor availability, bioengineered corneal equivalents are being developed as a solution, with biocompatibility, structural integrity, and physical function considered key factors. Since conventional evaluation methods may not fully capture the complex properties of the cornea, there is a need for advanced imaging and assessment techniques. In this study, we proposed a deep learning-based automatic segmentation method for transplanted bioengineered corneal equivalents using optical coherence tomography to achieve a highly accurate evaluation of graft integrity and biocompatibility. Our method provides quantitative individual thickness values, detailed maps, and volume measurements of the bioengineered corneal equivalents, and has been validated through 14 days of monitoring. Based on the results, it is expected to have high clinical utility as a quantitative assessment method for human keratoplasties, including automatic opacity area segmentation and implanted graft part extraction, beyond animal studies.

Ptychographic Mueller matrix imaging (PMMI): principle and proof-of-concept demonstration.

Quantitative characterization of optical anisotropies is extremely important for wide fields and applications. The Mueller matrix, providing all the polarization-related properties of a medium, is a powerful tool for the comprehensive evaluation of optical anisotropies. Here, we propose a ptychographic Mueller matrix imaging (PMMI) technique, which features the Mueller matrix polarization modulation being introduced into the ptychography. The ptychographic reconstruction is performed for each polarization state, and the Mueller matrix can be determined from the reconstructed polarization-modulated amplitude images. A proof-of-concept of the proposed PMMI is implemented, and both simulations and experiments are conducted to demonstrate the validity of the method. Results indicate that the imaging resolution of the home-built PMMI apparatus achieves 1.550 µm at the wavelength of 633 nm, which is of the highest level for the Mueller matrix imaging to the best of our knowledge. A customized birefringent specimen is characterized, and both retardance and axis azimuth are quantitatively evaluated.

Barriers in Healthcare to the Use of Optical Coherence Tomography Angiography in Multiple Sclerosis.

Optical coherence tomography angiography (OCT-A) is a state-of-the-art imaging technique for the retinal vasculature to accurately segment the capillary network and assign it to retinal layers. OCT-A is a promising technique to better understand neurological diseases with visual system manifestations, such as multiple sclerosis (MS), and to identify and characterize vascular biomarkers. Initial studies suggested vascular changes in MS and its differential diagnoses such as myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) and neuromyelitis optica spectrum disorder (NMOSD). Here we review clinical and technical aspects of OCT-A imaging and discuss the potential for the MS field as well as barriers that need to be overcome before OCT-A can be established in clinical application.

Imaging of peritoneal metastases of ovarian and colorectal cancer: joint recommendations of ESGAR, ESUR, PSOGI, and EANM.

Diagnostic imaging of peritoneal metastases in ovarian and colorectal cancer remains pivotal in selecting the most appropriate treatment and balancing clinical benefit with treatment-related morbidity and mortality. To address the challenges related to diagnostic imaging and detecting and reporting peritoneal metastatic spread, a joint guideline was created by the European Society of Gastrointestinal and Abdominal Radiology (ESGAR), European Society of Urogenital Radiology (ESUR), Peritoneal Surface Oncology Group International (PSOGI), and European Association of Nuclear Medicine (EANM). A targeted literature search was performed and consensus recommendations were proposed using Delphi questionnaires and a five-point Likert scale. A total of three Delphi rounds were performed. Consensus was reached on the position of diagnostic imaging for assessment of operability, treatment response monitoring, and follow-up of peritoneal metastases, optimal imaging modality and their technical imaging requirements depending on the indication and how to optimise communication of imaging results by the report and multidisciplinary board discussion. The complete list of recommendations is provided. These expert consensus statements aim to guide appropriate indications, acquisition, interpretation, and reporting of imaging for operability assessment, treatment response monitoring, and follow-up of peritoneal metastases in ovarian and colorectal cancer patients. Question Staging peritoneal metastases (PM) helps toguide clinical decision-making for colorectal and ovarian cancer patients. How can we optimise the use of imaging techniques to assess PM? Findings Imaging plays a crucial role in the detection, operability assessment, treatment response monitoring, and follow-up of peritoneal metastases in colorectal and ovarian cancer patients. Clinical relevance These expert consensus statements aim to guide appropriate indication, acquisition, interpretation, and reporting of imaging for operability assessment, treatment response monitoring, and follow-up of peritoneal metastases in ovarian and colorectal cancer patients.

Enhanced Computer-Aided Digital Imaging Technique for Predictions in Breast Cancer

Background: Breast cancer (BRCA) is the most frequently diagnosed cancer in women, with a rise in occurrences and fatalities. The field of BRCA prediction and diagnosis has witnessed significant advancements in recent years, particularly emphasizing enhanced computer-aided digital imaging techniques, and has emerged as a powerful ally in the prediction of BRCA through histopathology image analysis. A number of approaches have been suggested in recent years for the categorization of histopathology BRCA images into benign and malignant as it examines the images at cellular level. The histopathology slides must be manually analysed which is time consuming and tiresome and is prone to human error. Additionally, different laboratories occasionally have different interpretation of these images. Methods: This paper focuses on implementing a framework for Computer-Aided digital imaging technique that can serve as a decision support. With recent advancements in computing power the analysis of BRCA histopathology image samples has become easier. Stain normalization (SN), segmentation, feature extraction and classification are the steps to categorize the cancer into benign and malignant. Nuclei segmentation is a crucial step that needs to be taken into account in order to establish malignancy. These are considered essential for early diagnosis of BRCA. A unique method proposed for BRCA prediction is put forward. To maximize the prediction accuracy, the suggested method is integrated with machine learning (ML) techniques and clinical data is used to evaluate the suggested approach. Results: This strategy is adaptable to many cancer types and imaging techniques. The suggested technique is applied to clinical data and is integrated with logistic regression and K-Nearest Neighbor resulting in accuracy of 92.10% and 86.89% respectively for BRCA histopathology images. Conclusion: The objective of this work is to validate the proposed model which takes input as feature pattern for a given label. For the collected clinical samples, the model is able to classify the input as benign or malignant. The proposed model worked efficiently for different BC datasets and performed classification task successfully. Integrating mathematical model (MM) with ML model for interpreting histopathology BRCA is a potential area of research in the field of digital pathology.

Removal of soft tissue foreign bodies in the hand under microscopy: a retrospective observational study

Purpose: Numerous studies have focused on techniques for detecting foreign bodies in soft tissue in the hand, but removal remains a subject of interest. In this study, we describe the microscope-assisted removal of foreign bodies in the hand. Methods: We reviewed records of patients treated for foreign bodies in the hand at our department from July 2013 to May 2023. In 16 patients aged 23 to 55 years, the following variables were analyzed: the cause of trauma; the time interval from trauma to surgery; the location, type, size, and number of foreign bodies; patient complaints; imaging technique; and procedure type. Under local anesthesia, a slit incision was made at the suspected site. Foreign bodies were completely removed using micro-instruments under microscopic guidance. Results: Stab injuries were the most common (n=13), and there was one case each of abrasion, traffic accident, and bee sting. The middle finger (n=5) was the most affected, followed by the thumb (n=4), index (n=3), little finger (n=2), ring finger (n=1), and palm (n=1). Foreign bodies included glass (n=6), wood (n=4), seashell (n=2), fish bone, a pencil tip, a bee stinger, and metal. Their size ranged from 1 to 20 mm. Patient complaints included a foreign body sensation, localized pain, swelling, discoloration, and a skin lesion. X-ray examinations were performed in all cases, and ultrasonography was conducted in five cases. Conclusion: A microscopic approach allows precise, safe, and complete removal of foreign bodies without tissue damage, highlighting the efficacy of this technique in hand surgery.

Detection of Ovarian Tumors Using TVUS Imaging and Segmentation Techniques

Ovarian most cancers remains a giant health subject due to its regularly asymptomatic development until superior stages, where treatment options are confined. Early detection is critical for enhancing affected person outcomes and survival costs. This observe proposes a comprehensive technique leveraging superior photograph processing techniques for the early detection and category of ovarian tumors the usage of trans vaginal ultrasound (TVUS) snap shots. The method starts with preprocessing steps which include median filtering to do away with noise artifacts inclusive of salt and pepper noise from ultrasound photos. Ultimately, picture enhancement techniques are applied to enhance contrast and intensity, observed through binary sample evaluation to signify texture features vital for tumor identification. Photo segmentation is performed the use of okay- manner clustering and gray degree Co-prevalence Matrix (GLCM) analysis to isolate and analyze areas of interest within the ovarian photos. A Convolutional Neural community (CNN) is then hired for correct classification of ovarian tumors as regular, benign, or malignant primarily based on the extracted functions. This approach not handiest enhances the diagnostic accuracy but also minimizes affected person publicity to ionizing radiation, making it appropriate for ordinary medical applications. The proposed methodology represents a considerable advancement within the discipline of ovarian cancer detection, presenting a non-invasive and green way to evaluate ovarian health and facilitate timely intervention. Destiny research directions include refining the set of rules’s performance with large datasets and exploring additional imaging modalities for complete ovarian fitness evaluation.

Fiber anatomy and histological characteristics of the innervation of the triangular fibrocartilage complex.

To evaluate the precise origin of sensory nerves through gross anatomical study of the TFCC, synthesized alongside imaging and histological techniques. Six cadaveric forearm specimens were obtained to map the course and branches of the ulnar nerve through macrodissection. Immunohistochemical staining targeting PGP 9.5 and type IV collagen was performed on frozen TFCC sections to visualize nerve fibers microscopically. Computed tomography, magnetic resonance imaging, and arthrography findings were also reviewed. At the macroscopic level, the articular branches supplying the TFCC originated predominantly from the dorsal branch of the ulnar nerve. Microscopic analysis revealed positive PGP 9.5 expression and discernible neural marker expression, signifying fine nerve fiber ingrowth within the TFCC. Imaging modalities aided the diagnosis of TFCC lesions. The dorsal cutaneous branch of the ulnar nerve, medial cutaneous nerve of the forearm, and volar sensory branch of the ulnar nerve emerged as the principal nerves innervating the TFCC. This study provides anatomical evidence that the TFCC receives innervation from branches of the ulnar nerve and contains sensory nerve fibers. These findings enhance understanding of potential neuropathic pain mechanisms in TFCC injuries and offer insights to guide surgical interventions. Further investigations are warranted to elucidate the clinical implications.

Impact of light polarization on laser speckle contrast imaging with a custom phantom for microvascular flow

Laser speckle contrast imaging (LSCI) is a non-invasive, powerful, and cost-effective imaging technique that has seen widespread adoption across various medical fields, particularly for blood flow imaging. While LSCI provides physicians with valuable insights into changes or occlusions in blood flow, the technique is susceptible to various factors and parameters that can impact measurement sensitivity and signal-to-noise ratio (SNR). These include the scattering of light, which can affect the quality and reliability of the LSCI data. The polarization of light holds significant promise to enhance the performance of LSCI. In this study, we employed polarization manipulation of light to investigate its impact on the performance of LSCI for measuring flow. Focusing on the application of LSCI in microcirculation within capillaries, we examined the effect of polarization control on the technique's flow measurement capabilities using a custom-designed phantom system. This phantom consisted of three tubes with inner diameters of 1.1 mm, 1.6 mm, and 2.8 mm, embedded in a polydimethylsiloxane (PDMS) matrix with optical properties similar to biological tissue. By manipulating the polarization of both the incident and reflected light, alternating between parallel and perpendicular states, we compared the performance of our LSCI system in detecting flow for different tube diameters and depths within the phantom. Our study revealed that while depth is a critical parameter influencing flow detection using LSCI, employing perpendicular polarization (between incident and reflected light) resulted in the lowest measurement error and highest SNR compared to parallel polarization and the absence of polarization control.

Prospective Assessment of VI-RADS with Muscle Invasion in Urinary Bladder Cancer and Its Implication on Re-Resection/Restaging TURBT Patients.

Bladder cancer (BCa) diagnosis relies on distinguishing muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC) forms. Transurethral resection of the bladder tumor (TURBT) is a standard procedure for initial staging and treatment. The Vesical Imaging-Reporting and Data System (VI-RADS) enhances diagnostic accuracy for muscle invasiveness through advanced imaging techniques, potentially reducing reliance on repeat TURBT and improving patient management. We aimed to evaluate the role of VI-RADS in predicting muscle invasiveness in BCa and its potential to predict adverse pathology in high-risk NMIBC to avoid unnecessary repeat TURBT procedures. In this prospective study, we included 62 patients over the age of 18years who underwent TURBT. In a secondary phase, patients selected for restaging TURBT (re-TURBT) were included, but those with T2 tumors or low-risk NMIBC were excluded. Multiparametric magnetic resonance imaging (MRI) examinations were scored by a radiologist using the VI-RADS 5 method, while a pathologist analyzed TURBT and re-TURBT samples for accurate staging. Statistical analysis evaluated the role of VI-RADS in BCa staging. The VI-RADS score was the only predictive factor for muscle invasion in multivariate analysis. Setting the VI-RADS score at >3 resulted in the highest sensitivity, specificity, and diagnostic accuracy, with values of 67.0%, 89.0%, and 78%, respectively. The receiver operating characteristic area under the curve score for VI-RADS for muscle invasion was 85% for stage Ta, 61% for stage T1, and 88% for stage T2, which shows the utility of VI-RADS in the predictiveness of MIBC/NMIBC. VI-RADS is effective in stratifying BCa patients by predicting muscle invasiveness and identifying NMIBC cases that may not need repeat TURBT.

In Vivo Detection of Lymph Nodes Metastasis of ESCC Using CXCR4-Targeted Tracer [64Cu]Cu-NOTA-CP01.

Esophageal squamous cell carcinoma (ESCC) frequently exhibits skip metastasis to lymph nodes; however, non-invasive imaging techniques capable of directly visualizing metastatic lymph nodes (MLN) are still lacking. Although biopsy is the clinical standard method, it is invasive and poses risks to patient health. This study aims to detect MLN in an intralymphatic tumor metastasis model of ESCC using the CXCR4-targeted tracer [64Cu]Cu-NOTA-CP01. The CXCR4 expression in ESCC cell lines was assessed using Western blot and immunofluorescence. An intralymphatic tumor metastasis model was established and monitored using bioluminescence imaging (BLI). Small animal PET studies and biodistribution studies were performed to evaluate the specificity of [64Cu]Cu-NOTA-CP01 for MLN. Histopathology evaluation was employed to check for the presence of metastatic tumor cells and to assess CXCR4 expression levels in the metastatic lymph nodes. The intralymphatic tumor metastasis model was successfully established using the EC109/Luc cell line, which exhibited high CXCR4 expression, as verified by BLI. PET/CT imaging showed that the MLN uptakes in the baseline group were significantly inhibited in the blocking group. The ratios of MLN/muscle and MLN/blood werealso significantly higher in the baseline group than in the blocking group. Ex vivo PET/CT imaging of MLN corroborated the in vivo data. Biodistribution studies further supported the PET imaging studies, showing rapid clearance of the tracer from the blood and major organs, with significantly higher MLN/muscle and MLN/blood ratios in the baseline group compared to the blocking group. Histopathological staining verified positive CXCR4 expression in these lymph nodes containing metastatic tumor cells. Targeting CXCR4 with [64Cu]Cu-NOTA-CP01 for PET imaging of lymph nodes metastasis represents a promising approach that warrants further investigation. These findings have the potential to enhance diagnostic and therapeutic strategies for individuals with lymph nodes metastasis of ESCC.

Advanced Technologies for Teaching Rachana Sharir: Implications for Academic Education

The study of Rachana Sharira is a cornerstone of educational programs in the biological and healthcare fields. It is crucial that the teaching methods and instructional strategies used in this subject effectively prepare students. Traditionally, Rachana Sharira has been taught through a combination of lectures and hands-on practical sessions involving cadaver dissections and pre-dissected specimens. However, with the advent of modern digital technologies, such as smartphones, QR codes, and virtual reality, along with advanced imaging techniques like radiography, ultrasonography, MRI, and CT scans, the landscape of Rachana Sharira education is evolving. This review aims to explore how these innovative tools are being integrated into academic settings to enhance the diversity and effectiveness of Rachana Sharira teaching, ultimately improving students' understanding of the subject and its clinical applications.

Exploring the Interplay of Wavelength, Quantum Yield, and Penetration Depth in In Vivo Fluorescence Imaging.

The intricate interplay between the irradiation wavelength, the fluorophore quantum yield (QY) and penetration depth profoundly influences the efficacy of in vivo fluorescence imaging in various applications. Understanding the complex behavior of fluorescence in vivo, specifically how variations in wavelength affect the QY of commonly used dyes and the depth of imaging is crucial for optimizing fluorescence imaging techniques, as it directly impacts the accuracy and efficiency of imaging in biological tissues. In our study, we explore these dynamics through Monte Carlo simulations conducted under conditions reflective of wide-field fluorescence imaging, examining how variations in wavelength impact the dye's QY and depth of imaging, and consequently, the fluorescence behavior. A transition in the exponential decay of the emission depth exponent is observed around the 500-600nm range, indicating varying degrees of influence of depth on the fluorescence emission. The analysis of the fluorophore's QY reveals wavelength-dependent variations, with the most significant impact observed in the 600-700nm range. Moreover, we continued our investigation to explore multiplexing, unveiling insights into the spacing between identical spots in multiplexing images across various depths and wavelengths.

Blue light reflectance imaging in non-perfusion areas detection: insights from multimodal analysis

DesignA retrospective, cross-sectional image analysis using a convenience sample.SubjectsFive cases selected based on the availability of comprehensive imaging data.MethodsThis study involved a retrospective review of images from five cases, focusing on the use of retinal monochromatic blue light reflectance (BLR) imaging to detect non-perfusion areas. Two cases of sickle-cell retinopathy demonstrated peripheral retinal non-perfusion identified through widefield fluorescein angiography. Three other cases—one with branch retinal vein occlusion, one with branch retinal artery occlusion, and one presenting paracentral acute middle maculopathy showed focal macular non-perfusion detected by structural OCT and OCTA. The areas of nonperfused retinal tissue, confirmed by fluorescein angiography, OCT, and OCTA, were then correlated with findings from the BLR image. This correlation aimed to identify any potential associations between these imaging modalities.Main outcome measuresEnhance understanding of the utilization of retinal monochromatic BLR images as a non-perfusion biomarker.ResultsThe perfusion defects identified through fluorescein angiography were qualitatively correlated with hypo-reflective regions observed in the BLR images. A notable correlation was also observed between the OCTA deep capillary plexus findings and the BLR images. Additionally, areas of retinal thinning identified on structural OCT thickness maps corresponded with the hypo-reflective regions in the BLR images. This indicates the potential of BLR in identifying non-perfused retinal areas.ConclusionsThis study reinforces the evidence, through OCT, OCTA, and angiographic correlation, that the BLR can effectively identify areas of retinal non-perfusion in a non-invasive manner. Further research is warranted to assess the method’s sensitivity, specificity, and limitations. While the interaction of blue light with the retina, leading to specular reflections and scattering, is established, this research represents a pioneering effort in suggesting which specific retinal structures may be implicated in this phenomenon. This novel insight opens avenues for deeper exploration into the underlying mechanisms and potential clinical applications of utilizing the BLR imaging technique for assessing retinal vascular abnormalities.

Diagnostic Utility of Diffusion-Weighted Imaging in Distinguishing Common Pediatric Posterior Fossa Tumors: A Single Center Retrospective Study.

Pediatric posterior fossa tumors pose diagnostic challenges due to their diverse histopathological features and variable clinical presentations. Conventional magnetic resonance imaging (MRI) serves as the initial diagnostic tool; however, additional modalities, such as diffusion-weighted imaging (DWI), are essential for refining tumor classification. This retrospective single-center study aimed to evaluate the diagnostic utility of apparent diffusion coefficient (ADC) parameters in distinguishing between the most common pediatric posterior fossa tumors. Fifty-nine patients under the age of 18 (27 females and 32 males) with histopathologically diagnosed primary posterior fossa tumors underwent pre-treatment conventional and diffusion MRI. Apparent diffusion coefficient values were measured from solid tumor regions and normal cerebellar parenchyma, with subsequent calculation of tumor/normal cerebellar ADC ratios. The median ADC values for pilocytic astrocytomas (PAs) were 1786.2 × 10-6 mm2 /s, ependymomas 1144.9 × 10-6 mm2 /s, and for medulloblastomas 666.1 × 10-6 mm2 /s were significantly different (P < .001 for all three). Similarly, the median ADC ratios demonstrated discriminatory potential, with PAs showing the highest ratio (2.46), followed by ependymomas (1.55) and medulloblastomas (0.89) (P < .001 for all three). Receiver operating characteristic analysis revealed distinct ADC cutoffs and ratios for differentiating all tumor types from each other. Despite limitations, such as a small cohort size and different MRI protocols, our results show that ADC metrics are especially useful for distinguishing between the most common pediatric posterior fossa tumors. We recommend that future studies integrate advanced imaging techniques and larger cohorts to improve diagnostic accuracy.

Heat application in live cell imaging.

Thermal heating of biological samples allows to reversibly manipulate cellular processes with high temporal and spatial resolution. Manifold heating techniques in combination with live-cell imaging were developed, commonly tailored to customized applications. They include Peltier elements and microfluidics for homogenous sample heating as well as infrared lasers and radiation absorption by nanostructures for spot heating. A prerequisite of all techniques is that the induced temperature changes are measured precisely which can be the main challenge considering subcellular structures or multicellular organisms as target regions. This article discusses heating and temperature sensing techniques for live-cell imaging, leading to future applications in cell biology.

LC-OCT for early diagnosis and characterization of dermatologic adverse events to oncologic drugs and correlation to histopathology.

Targeted and immune therapies have recently been associated with the occurrence of multiple cutaneous toxicities, often challenging to differentiate by clinical examination alone without histology. Line-field confocal optical coherence tomography (LC-OCT) is a non-invasive and innovative imaging technique that has been shown to be almost as effective as histology in diagnosing several skin conditions. Our study aimed to assess the effectiveness of LC-OCT in predicting the clinical evolution of early maculopapular eruptions related to antineoplastic targeted therapy and immunotherapy. In the period between May 2023 and December 2023, consecutive patients with clinical cutaneous maculopapular reactions caused by oncologic targeted therapy or immunotherapy were enrolled at the dermatologic outpatient clinic of the Fondazione Policlinico A. Gemelli IRCCS, Rome. Patients underwent clinical dermatological examination, video-dermoscopy, LC-OCT, and incisional skin biopsy of a target cutaneous lesion. To investigate the evolutionary pattern of maculopapular lesions (psoriasic eruption, lichenoid eruption, eczematous eruption, bullous eruption), LC-OCT and histopathological images have been compared based on specific characteristics (hyperkeratosis, acanthosis, spongiosis; papillomatosis; lichenoid inflammatory infiltrate; presence of intraepidermal/subepidermal cleavage plan with formation of a bulla). Eighteen patients were included in this study (11 males, 7 females, median age 64.5). LC-OCT demonstrated an overall concordance with histology of 77.8%, with a Cohen's Kappa of 0.69 (P < 0.0001). Sensitivity exceeded 70%, and specificity was ≥88.2%. The Area Under the Curve (AUC) ranged from 0.9 to 1 for psoriasis and lichenoid eruption and from 0.7 to 0.9 for eczematous and bullous eruption. LC-OCT appears to be a promising tool for the early differential diagnosis of adverse skin reactions related to targeted therapy and immunotherapy, offering the potential to avoid skin biopsies in fragile cancer patients.

Molecular Imaging Biomarkers for Early Cancer Detection: A Systematic Review of Emerging Technologies and Clinical Applications.

Early cancer detection is crucial for improving patient outcomes. Molecular imaging biomarkers offer the potential for non-invasive, early-stage cancer diagnosis. To evaluate the effectiveness and accuracy of molecular imaging biomarkers for early cancer detection across various imaging modalities and cancer types. A comprehensive search of PubMed/MEDLINE, Embase, Web of Science, Cochrane Library, and Scopus was performed, covering the period from January 2010 to December 2023. Eligibility criteria included original research articles published in English on molecular imaging biomarkers for early cancer detection in humans. The risk of bias for included studies was evaluated using the QUADAS-2 tool. The findings were synthesized through narrative synthesis, with quantitative analysis conducted where applicable. In total, 50 studies were included. Positron emission tomography (PET)-based biomarkers showed the highest sensitivity (mean: 89.5%, range: 82-96%) and specificity (mean: 91.2%, range: 85-100%). Novel tracers such as [68Ga]-PSMA for prostate cancer and [18F]-FES for breast cancer demonstrated promising outcomes. Optical imaging techniques showed high specificity in intraoperative settings. Molecular imaging biomarkers show significant potential for improving early cancer detection. Integration into clinical practice could lead to earlier interventions and improved outcomes. Further research is needed to address standardization and cost-effectiveness.

Research Progress of Spectral Imaging Techniques in Plant Phenotype Studies.

Spectral imaging technique has been widely applied in plant phenotype analysis to improve plant trait selection and genetic advantages. The latest developments and applications of various optical imaging techniques in plant phenotypes were reviewed, and their advantages and applicability were compared. X-ray computed tomography (X-ray CT) and light detection and ranging (LiDAR) are more suitable for the three-dimensional reconstruction of plant surfaces, tissues, and organs. Chlorophyll fluorescence imaging (ChlF) and thermal imaging (TI) can be used to measure the physiological phenotype characteristics of plants. Specific symptoms caused by nutrient deficiency can be detected by hyperspectral and multispectral imaging, LiDAR, and ChlF. Future plant phenotype research based on spectral imaging can be more closely integrated with plant physiological processes. It can more effectively support the research in related disciplines, such as metabolomics and genomics, and focus on micro-scale activities, such as oxygen transport and intercellular chlorophyll transmission.