Search Results (60)

Early diagnosis of pancreatic cancer, particularly in intraductal papillary mucinous neoplasm (IPMN), remains challenging despite advances in imaging and biomarkers. Pancreatic adenocarcinoma (PDAC) has a high mortality rate; therefore, its early detection and adequate interventions are necessary to improve the disease outcome. Most IPMNs are asymptomatic and discovered incidentally. Magnetic resonance imaging (MRI) is a preferred tool for diagnosing malignant IPMNs, with a sensitivity of 90.7–94.1% and a specificity of 84.7–87.2% in detecting mural nodules > 5 mm, a strong predictor of high-risk lesions. Radiomics further enhances diagnostic accuracy (sensitivity 91–96%, specificity 78–81%), especially when combined with CA 19-9, which has lower sensitivity (73–90%) but higher specificity (79–95%). Computed tomography (CT), though less effective for small mural nodules, remains widely used; its accuracy improves with radiomics and clinical variables (sensitivity 90.4%, specificity 74%). Conventional endoscopic ultrasonography (EUS) shows lower performance (sensitivity 60%, specificity 80%), but its advanced variations have improved outcomes. Contrast-enhanced EUS (CE-EUS) visualizes mural nodules with more than 90% sensitivity and involvement of the main pancreatic duct, with a sensitivity of 83.5% and a specificity of 87%. EUS–fine-needle aspiration (EUS-FNA) allows cyst fluid analysis; however, CEA, glucose, and KRAS/GNAS mutations show poor value for malignancy risk. Cytology has low sensitivity (28.7–64.8%) but high specificity (84–94%) in diagnostic malignant changes and strongly affects further management. EUS–through-the-needle biopsy (EUS-TTNB) yields high diagnostic accuracy (sensitivity 90%, specificity 95%) but carries a range of 2–23% adverse events, which limits its wide use. EUS–confocal laser endomicroscopy (EUS-nCLE) provides real-time microscopic evaluation, detecting malignant IPMN with a sensitivity of 90% and a specificity of 73%, though its availability is limited. New emerging biomarkers available in cyst fluid or blood include mucins, miRNA panels (sensitivity 66.7–89%, specificity 89.7–100%), lipidomics, and cancer metabolite profiling, with diagnostic accuracy approaching 89–91%. Pancreatoscopy (POP) enables direct main pancreatic duct (MPD) visualization and biopsy with a sensitivity of 64–100% and a specificity of 75–100%, though adverse events occur in around 12% cases. Combining advanced imaging, EUS-based tissue acquisition, and novel biomarkers holds promise for earlier and more accurate detection of malignant IPMN, potentially improving PDAC outcomes. Full article

Manual tissue documentation is a critical step in the field of pathology that sets the stage for microscopic analysis and significantly influences diagnostic outcomes. In routine practice, technicians verbally dictate descriptions of specimens during gross examination; these are later transcribed into macroscopic reports. Fragment sizes are measured manually with rulers; however, these measurements are often inconsistent for small, irregular biopsies. No photographic record is captured for traceability. To address these limitations, we propose a proof-of-concept framework that automates the image capture and documentation of biopsy and resection cassettes. It integrates a custom imaging platform and a segmentation pipeline leveraging the YOLOv8 and YOLOv9 architectures to improve accuracy and efficiency. The framework was tested in a real clinical context and was evaluated on two datasets of 100 annotated images each, achieving a mask mean Average Precision (mAP) of 0.9517 ± 0107 and a tissue fragment spatial accuracy of 96.20 ± 1.37%. These results demonstrate the potential of our framework to enhance the standardization, reliability, and speed of macroscopic documentation, contributing to improved traceability and diagnostic precision. Full article

Endometriosis is a clinical entity affecting up to 10% of women of reproductive age, characterized by ectopic endometrial tissue outside the uterine cavity. While extrapelvic endometriosis has been documented, pancreatic endometriosis remains extremely rare and poses significant diagnostic challenges due to its similarity to other pancreatic diseases. At the same time, splenic mesothelial cysts are also rare and typically benign. This report presents a unique case of pancreatic endometriosis coexisting with a splenic mesothelial cyst in a 31-year-old woman. The patient presented to the emergency department with complaints of persistent epigastric and low back pain. She noted having similar symptoms approximately a year prior. Her past medical history was otherwise unremarkable, and there was no known family history of pancreatic disease or neoplasms. Initial imaging revealed a 3.8 cm cystic lesion in the pancreatic tail, with features suggestive of mucinous cystadenoma. Following clinical evaluation and confirmation of the cyst’s nature through endoscopic ultrasound-guided biopsy, the patient subsequently underwent laparoscopic distal pancreatectomy and splenectomy due to worsening symptoms. Gross examination revealed a multilocular pancreatic cyst with a smooth, hemorrhagic wall. Microscopic analysis showed the cyst to be lined by cuboidal to columnar epithelium, consistent with pancreatic endometriosis, confirmed by immunohistochemical staining. The spleen showed cystic formations, diagnosed as a multifaceted mesothelial cyst. In conclusion, this report is the first to document the coexistence of pancreatic endometriosis and splenic mesothelial cysts, highlighting the importance of accurate imaging and pathologic evaluation in the diagnosis of these rare conditions. Early diagnosis and surgical intervention lead to favorable outcomes, reinforcing the importance of comprehensive diagnostic strategies. Full article

Background: The standard diagnostic approach for prostate cancer (PCa) diagnosis consists of serum prostate-specific antigen (PSA) testing, digital rectal examination (DRE) and image-guided targeted biopsies. Given the invasive nature, potential adverse events and costs associated with these techniques, alternative approaches have been investigated, specifically with serum and urine assays. The work presented here is intended to further validate a novel noninvasive optical technique for PCa detection, targeting the VPAC genomic receptors that are overexpressed on prostate cancer’s malignant cells (MC), in non-DRE voided urine. Methods: Patients (N = 62) who had image-guided biopsy and histologically confirmed localized PCa, and who were scheduled for radical prostatectomy, provided a non-DRE voided urine sample prior to surgery. Urine was cytocentrifuged and cells fixed on a glass slide, incubated with 0.5 μg TP4303 (a receptor-specific fluorophore developed in our laboratory with high affinity for VPAC), excess washed and treated with 4,6-diamidodino-2-phenylindole (DAPI) for nuclear staining. The field of cells on each slide was analyzed using a Zeiss AX10 Observer microscope (20×). The total number of cells and MC were then counted, and the florescent intensity around each MC was measured using Zeiss software. Additionally, non-DRE voided urine samples collected from clinically determined BPH patients (N = 97), were also analyzed similarly. Results: Urine samples from 62 patients were processed and analyzed. Mean PSA levels by Gleason grade (GG) group were 6.5 ± 4.1 ng/mL for GG1 (N = 10), 7.2 ± 3.8 for GG2 (N = 31), 13.2 ± 14.6 for GG3 (N = 13), 6.2 ± 2.2 for GG4 (N = 2) and 50.2 ± 104.9 for GG5 (N = 6). Like the PSA, % MC shed (66.7 ± 27.7) in voided urine and the fluorescent intensity (35.8 ± 5.7) were highest in patients with GG5 prostate cancer. All PCa patients in GG1 to GG5 shed MC in voided urine with increasing % of MC and increasing fluorescence intensity which correlated with the increasing GG for PCa. For BPH, the specificity for the assay was 89.6% (95% CI:81.9–94.9%), PPV was 0.0% and NPV was 100% (95.9% CI, 95.9–100%). Conclusions: These data indicate the following: (i) PCa MC shed in non-DRE voided urine can be detected by targeting VPAC receptors, (ii) MC are shed in non-DRE voided urine with increasing quantity, corresponding to the severity of the disease, and (iii) this non-DRE voided urine optical assay provides a simple, noninvasive, and reliable method for the preliminary detection of PCa with potentially a lower cost than the currently available pre-biopsy detection technologies. Full article

Background: Ex vivo fluorescence laser scanning microscopes (FCMs) allow digital tissue imaging directly from fresh, unfixed specimens without the need for conventional histological slide preparation. To date, no data have been reported on the use of FCMs in the endoscopy suite for immediate evaluation of endoscopic ultrasound (EUS)/endobronchial ultrasound (EBUS) fine needle aspiration/biopsy (FNA-B) specimens of lung lesions and/or mediastinal lymph nodes. Objectives: The aim of this study was to evaluate the performance of the FCM Vivascope 2500 (Vivascope, Munich, Germany) in providing real-time adequacy assessment and diagnostic information on the digital images of fresh unprocessed EUS/EBUS FNA-B specimens and to compare it with the corresponding final histological sections of formalin-fixed and paraffin-embedded cell blocks. Methods and Results: Thirty-two patients (50% male; 71 ± 8 years old) were enrolled between May 2023 and June 2024. In 28/32 (87.5%) patients, samples were defined as adequate at Vivascope evaluation, and in 20/28 (71.4%) patients, samples were classified as malignant. At final cytohistological evaluation, 87.5% of specimens were defined as adequate and 20/28 (71.4%) were diagnosed as malignant. There was perfect agreement between the Vivascope assessment of adequacy and the final cytohistological assessment on the same specimen (k Cohen 1). From a diagnostic point of view, perfect agreement was found between the two techniques in the identification of malignant neoplasms (k Cohen 1). Conclusions: The use of FCM could provide rapid information on both the adequacy and malignancy of the sample obtained during EBUS tissue acquisition (EBUS-TA), with minimal or no preparation and without destroying or losing the tissue. This technique allows for obtaining representative material in EBUS/EUS for lung cancer staging and is expected to change the turnaround time from biopsy sampling to diagnostic characterization of the tumor, ultimately improving patient management both at diagnosis and at restaging in follow up. Full article

Background and Aim: Ex vivo fluorescence confocal microscopy (FCM) systems are innovative optical imaging tools that create virtual high-resolution histological images without any standard tissue processing, either freezing or fixing in formalin and embedding in paraffin. These systems have opened an era that would revolutionize pathological examination by providing rapid, real-time assessments across various pathology subspecialties, potentially replacing conventional methods that are tissue- and time-consuming. This study aimed to present the first utilization of FCM in pediatric surgical oncology, focusing on assessing the benefits, particularly in facilitating rapid and accurate diagnosis. Methods: This preliminary study comprised five consecutive patients undergoing surgical biopsy for disease characterization and surgical strategy selection. After biopsy, tissue samples were prepared and analyzed using FCM without sectioning. A pathologist who evaluated macroscopic and microscopic images, once obtained remotely, could promptly indicate any interventions that require timeliness. Samples were then evaluated with conventional methods. Results: All five lesions were deemed suitable for evaluation. Preliminary diagnoses utilizing FCM included atypical Spitz nevus (1), Wilm’s tumor (1), lymph node reactive hyperplasia (1), malignant germ cell tumor of the testis (1), and Hodgkin’s lymphoma (1). Final histopathological analyses revealed atypical Spitz nevus (1), Wilm’s tumor (1), hyperplastic lymphadenopathy with a prevalent marginal pattern (1), mixed nonseminomatous malignant germinal neoplasm consisting of embryonal carcinoma (90%) and yolk sac tumor (10%), and Hodgkin’s lymphoma nodular sclerosis variant (1). In the case of diagnosis of atypical Spitz nevus, the widening of the resection margins was performed in the same surgery. In the case of testicular neoplasm, radical orchiectomy was performed. A high level of agreement between FCM evaluation and definitive histological examination was observed for all parameters evaluated. Conclusions: FCM represents a significant advancement in pathological imaging technology, offering potential benefits in enhancing traditional tissue processing methods. This preliminary report marks the first application of FCM in pediatric surgical oncology. Our findings underscore the promising role of FCM as an adjunctive tool in pediatric oncology, facilitating prompt diagnosis and treatment initiation. Full article

Background: The invasion of glioblastoma cells beyond the visible tumor margin depicted by conventional neuroimaging is believed to mediate recurrence and predict poor survival. Radiomic biomarkers that are associated with the direction and extent of tumor infiltration are, however, non-existent. Methods: Patients from a single center with newly diagnosed glioblastoma (n = 7) underwent preoperative Q-space magnetic resonance imaging (QSI; 3T, 64 gradient directions, b = 1000 s/mm²) between 2018 and 2019. Tumors were manually segmented, and patterns of inter-voxel coherence spatially intersecting each segmentation were generated to represent tumor-associated tractography. One patient additionally underwent regional biopsy of diffusion tract- versus non-tract-associated tissue during tumor resection for RNA sequencing. Imaging data from this cohort were compared with a historical cohort of n = 66 glioblastoma patients who underwent similar QSI scans. Associations of tractography-derived metrics with survival were assessed using t-tests, linear regression, and Kaplan–Meier statistics. Patient-derived glioblastoma xenograft (PDX) mice generated with the sub-hippocampal injection of human-derived glioblastoma stem cells (GSCs) were scanned under high-field conditions (QSI, 7T, 512 gradient directions), and tumor-associated tractography was compared with the 3D microscopic reconstruction of immunostained GSCs. Results: In the principal enrollment cohort of patients with glioblastoma, all cases displayed tractography patterns with tumor-intersecting tract bundles extending into brain parenchyma, a phenotype which was reproduced in PDX mice as well as in a larger comparison cohort of glioblastoma patients (n = 66), when applying similar methods. Reconstructed spatial patterns of GSCs in PDX mice closely mirrored tumor-associated tractography. On a Kaplan–Meier survival analysis of n = 66 patients, the calculated intra-tumoral mean diffusivity predicted the overall survival (p = 0.037), as did tractography-associated features including mean tract length (p = 0.039) and mean projecting tract length (p = 0.022). The RNA sequencing of human tissue samples (n = 13 tumor samples from a single patient) revealed the overexpression of transcripts which regulate cell motility in tract-associated samples. Conclusions: QSI discriminates tumor-specific patterns of inter-voxel coherence believed to represent white matter pathways which may be susceptible to glioblastoma invasion. These findings may lay the groundwork for future work on therapeutic targeting, patient stratification, and prognosis in glioblastoma. Full article

This article introduces a case of pelvic actinomycosis, which is easily confused with an ovarian malignant tumor. These images are from a 52-year-old woman who was admitted to hospital with difficulty defecating. Colonoscopy and biopsy indicated inflammatory changes within the intestinal tract, but the anti-inflammatory treatment was not effective. Later, she was readmitted due to abdominal pain and emaciation, and laboratory findings revealed mild anemia and inflammation. Various tumor markers are normal. CT suggested inflammatory lesions in the sigmoid colon and upper rectum. PET-CT considered a high metabolic mass originating from the mesentery. Ultrasound scan revealed a mixed-echo mass adjacent to the right side of the uterus, poorly demarcated from the rectum and right ovary, suggesting a neoplastic lesion. A biopsy of the right ovarian mass indicated suppurative inflammation, with negative antacid staining and microscopic observation of yellowish sulfur granules, suggestive of Actinomyces infection. Following a 12-month treatment regimen involving the removal of an intrauterine device and administration of penicillin, the patient’s condition markedly improved. Pelvic actinomycosis is usually characterized by abdominal pain accompanied by an abdominal mass, which is often related to an intrauterine device (IUD), and is very difficult to distinguish from pelvic tumors and tuberculosis, so it is necessary for doctors to understand its clinical and imaging features. Full article

Onychomycosis is a common fungal nail infection that is difficult to diagnose due to its similarity to other nail conditions. Accurate identification is essential for effective treatment. The current gold standard methods include microscopic examination with potassium hydroxide, fungal cultures, and Periodic acid-Schiff biopsy staining. These conventional techniques, however, suffer from high turnover times, variable sensitivity, reliance on human interpretation, and costs. This study examines the potential of integrating AI (artificial intelligence) with visualization tools like dermoscopy and microscopy to improve the accuracy and efficiency of onychomycosis diagnosis. AI algorithms can further improve the interpretation of these images. The review includes 14 studies from PubMed and IEEE databases published between 2010 and 2024, involving clinical and dermoscopic pictures, histopathology slides, and KOH microscopic images. Data extracted include study type, sample size, image assessment model, AI algorithms, test performance, and comparison with clinical diagnostics. Most studies show that AI models achieve an accuracy comparable to or better than clinicians, suggesting a promising role for AI in diagnosing onychomycosis. Nevertheless, the niche nature of the topic indicates a need for further research. Full article

This paper proposes a full-automatic high-efficiency Mueller matrix microscopic imaging (MMMI) system based on the tissue microarray (TMA) for cancer inspection for the first time. By performing a polar decomposition on the sample’s Mueller matrix (MM) obtained by a transmissive MMMI system we established, the linear phase retardance equivalent waveplate fast-axis azimuth and the linear phase retardance are obtained for distinguishing the cancerous tissues from the normal ones based on the differences in their polarization characteristics, where three analyses methods including statistical analysis, the gray-level co-occurrence matrix analysis (GLCM) and the Tamura image processing method (TIPM) are used. Previous MMMI medical diagnostics typically utilized discrete slices for inspection under a high-magnification objective (20×–50×) with a small field of view, while we use the TMA under a low-magnification objective (5×) with a large field of view. Experimental results indicate that MMMI based on TMA can effectively analyze the pathological variations in biological tissues, inspect cancerous cervical tissues, and thus contribute to the diagnosis of postoperative cancer biopsies. Such an inspection method, using a large number of samples within a TMA, is beneficial for obtaining consistent findings and good reproducibility. Full article

Acute lymphoblastic leukemia, commonly referred to as ALL, is a type of cancer that can affect both the blood and the bone marrow. The process of diagnosis is a difficult one since it often calls for specialist testing, such as blood tests, bone marrow aspiration, and biopsy, all of which are highly time-consuming and expensive. It is essential to obtain an early diagnosis of ALL in order to start therapy in a timely and suitable manner. In recent medical diagnostics, substantial progress has been achieved through the integration of artificial intelligence (AI) and Internet of Things (IoT) devices. Our proposal introduces a new AI-based Internet of Medical Things (IoMT) framework designed to automatically identify leukemia from peripheral blood smear (PBS) images. In this study, we present a novel deep learning-based fusion model to detect ALL types of leukemia. The system seamlessly delivers the diagnostic reports to the centralized database, inclusive of patient-specific devices. After collecting blood samples from the hospital, the PBS images are transmitted to the cloud server through a WiFi-enabled microscopic device. In the cloud server, a new fusion model that is capable of classifying ALL from PBS images is configured. The fusion model is trained using a dataset including 6512 original and segmented images from 89 individuals. Two input channels are used for the purpose of feature extraction in the fusion model. These channels include both the original and the segmented images. VGG16 is responsible for extracting features from the original images, whereas DenseNet-121 is responsible for extracting features from the segmented images. The two output features are merged together, and dense layers are used for the categorization of leukemia. The fusion model that has been suggested obtains an accuracy of 99.89%, a precision of 99.80%, and a recall of 99.72%, which places it in an excellent position for the categorization of leukemia. The proposed model outperformed several state-of-the-art Convolutional Neural Network (CNN) models in terms of performance. Consequently, this proposed model has the potential to save lives and effort. For a more comprehensive simulation of the entire methodology, a web application (Beta Version) has been developed in this study. This application is designed to determine the presence or absence of leukemia in individuals. The findings of this study hold significant potential for application in biomedical research, particularly in enhancing the accuracy of computer-aided leukemia detection. Full article

The cellularity assessment in bone marrow biopsies (BMBs) for the diagnosis of Philadelphia chromosome (Ph)-negative myeloproliferative neoplasms (MPNs) is a key diagnostic feature and is usually performed by the human eyes through an optical microscope with consequent inter-observer and intra-observer variability. Thus, the use of an automated tool may reduce variability, improving the uniformity of the evaluation. The aim of this work is to develop an accurate AI-based tool for the automated quantification of cellularity in BMB histology. A total of 55 BMB histological slides, diagnosed as Ph- MPN between January 2018 and June 2023 from the archives of the Pathology Unit of University “Luigi Vanvitelli” in Naples (Italy), were scanned on Ventana DP200 or Epredia P1000 and exported as whole-slide images (WSIs). Fifteen BMBs were randomly selected to obtain a training set of AI-based tools. An expert pathologist and a trained resident performed annotations of hematopoietic tissue and adipose tissue, and annotations were exported as .tiff images and .png labels with two colors (black for hematopoietic tissue and yellow for adipose tissue). Subsequently, we developed a semantic segmentation model for hematopoietic tissue and adipose tissue. The remaining 40 BMBs were used for model verification. The performance of our model was compared with an evaluation of the cellularity of five expert hematopathologists and three trainees; we obtained an optimal concordance between our model and the expert pathologists’ evaluation, with poorer concordance for trainees. There were no significant differences in cellularity assessments between two different scanners. Full article

Nonlinear microscopy (NM) enables us to investigate the morphology or monitor the physiological processes of the skin through the use of ultrafast lasers. Fiber (or fiber-coupled) lasers are of great interest because they can easily be combined with a handheld, scanning nonlinear microscope. This latter feature greatly increases the utility of NM for pre-clinical applications and in vivo tissue imaging. Here, we present a fiber-coupled, sub-ps Ti–sapphire laser system being optimized for in vivo, stain-free, 3D imaging of skin alterations with a low thermal load of the skin. The laser is pumped by a low-cost, 2.1 W, 532 nm pump laser and delivers 0.5–1 ps, high-peak-power pulses at a ~20 MHz repetition rate. The spectral bandwidth of the laser is below 2 nm, which results in a low sensitivity for dispersion during fiber delivery. The reduction in the peak intensity due to the increased pulse duration is compensated by the lower repetition rate of our laser. In our proof-of-concept imaging experiments, a ~1.8 m long, commercial hollow-core photonic bandgap fiber was used for fiber delivery. Fresh and frozen skin biopsies of different skin alterations (e.g., adult hemangioma, basal cell cancer) and an unaffected control were used for high-quality, two-photon excitation fluorescence microscopy (2PEF) and second-harmonic generation (SHG) z-stack (3D) imaging. Full article

Exosomes distributed by extracellular vesicles carry various information highly consistent with cells, becoming a new type of biomarker for tumor screening. However, although conventional characterization technologies can quantify size and morphology for exosomes, they are limited in related fields such as function tracing, protein quantification at unit point, and microstructural information. In this paper, firstly, different exosome characterization methods are systematically reviewed, such as dynamic light scattering, nanoparticle tracking analysis, flow cytometry, electron microscope, and emerging super-resolution imaging technologies. Then, advances in applications are described one by one. Last but not least, we compare the features of different technologies for exosomes and propose that super-resolution imaging technology can not only take into account the advantages of conventional characterization techniques but also provide accurate, real-time, and super-resolution quantitative analysis for exosomes. It provides a fine guide for exosome-related biomedical research, as well as application in liquid biopsy and analysis techniques. Full article

Fungal keratitis is a relatively rare yet severe ocular infection that can lead to profound vision impairment and even permanent vision loss. Rapid and accurate diagnosis plays a crucial role in the effective management of the disease. A patient’s history establishes the initial clinical suspicion since it can provide valuable clues to potential predisposing factors and sources of fungal exposure. Regarding the evaluation of the observed symptoms, they are not exclusive to fungal keratitis, but their timeline can aid in distinguishing fungal keratitis from other conditions. Thorough clinical examination of the affected eye with a slit-lamp microscope guides diagnosis because some clinical features are valuable predictors of fungal keratitis. Definitive diagnosis is established through appropriate microbiological investigations. Direct microscopic examination of corneal scrapings or biopsy specimens can assist in the presumptive diagnosis of fungal keratitis, but culture remains the gold standard for diagnosing fungal keratitis. Advanced molecular techniques such as PCR and MALDI-ToF MS are explored for their rapid and sensitive diagnostic capabilities. Non-invasive techniques like in vivo confocal microscopy (IVCM) and optical coherence tomography (OCT) are useful for real-time imaging. Every diagnostic technique has both advantages and drawbacks. Also, the selection of a diagnostic approach can depend on various factors, including the specific clinical context, the availability of resources, and the proficiency of healthcare personnel. Full article