Diagnostics最新文献

Background/Objectives: Biliary tract cancer (BTC) is a rare but aggressive malignancy that requires surgical treatment. However, postoperative recurrence rates are high, and reliable predictors of recurrence are limited. This study aimed to investigate the effectiveness of cell-free DNA (cfDNA) and circulating tumor cells (CTCs) in predicting early recurrence after curative surgery and complete adjuvant therapy in patients with BTC. Methods: Twenty-four patients who underwent R0 and R1 resections and completed adjuvant therapy for BTC between September 2019 and March 2022 were followed up until March 2024. Patients were categorized into early recurrence (ER) and non-ER groups, using one year as the cutoff for recurrence. Results: The combination score derived from ultrashort fragments of cfDNA, vimentin-positive CTCs, and carbohydrate antigen (CA) 19-9 levels showed a statistically significant difference between the ER and non-ER groups (p-value < 0.001). The receiver operating characteristic curve from the combination score and CA 19-9 levels yielded areas under the curve of 0.891 and 0.750, respectively. Conclusions: Although further research is required, these findings suggest that cfDNA and CTCs may increase the accuracy of predicting postoperative recurrence in patients with BTC.

Objectives: The integration of machine learning and radiomics in medical imaging has significantly advanced diagnostic and prognostic capabilities in healthcare. This study focuses on developing and validating an artificial intelligence (AI) model using U-Net architectures for the accurate detection and segmentation of spinal metastases from computed tomography (CT) images, addressing both osteolytic and osteoblastic lesions.

Methods: Our methodology employs multiple variations of the U-Net architecture and utilizes two distinct datasets: one consisting of 115 polytrauma patients for vertebra segmentation and another comprising 38 patients with documented spinal metastases for lesion detection.

Results: The model demonstrated strong performance in vertebra segmentation, achieving Dice Similarity Coefficient (DSC) values between 0.87 and 0.96. For metastasis segmentation, the model achieved a DSC of 0.71 and an F-beta score of 0.68 for lytic lesions but struggled with sclerotic lesions, obtaining a DSC of 0.61 and an F-beta score of 0.57, reflecting challenges in detecting dense, subtle bone alterations. Despite these limitations, the model successfully identified isolated metastatic lesions beyond the spine, such as in the sternum, indicating potential for broader skeletal metastasis detection.

Conclusions: The study concludes that AI-based models can augment radiologists' capabilities by providing reliable second-opinion tools, though further refinements and diverse training data are needed for optimal performance, particularly for sclerotic lesion segmentation. The annotated CT dataset produced and shared in this research serves as a valuable resource for future advancements.

Background: Early cancer detection is crucial for improving patient outcomes. Molecular imaging biomarkers offer the potential for non-invasive, early-stage cancer diagnosis.

Objectives: To evaluate the effectiveness and accuracy of molecular imaging biomarkers for early cancer detection across various imaging modalities and cancer types.

Methods: 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.

Results: 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.

Conclusions: 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.

Background: CMV reactivation represents a frequent complication after HSCT. The aim of this study was to describe the incidence of CMV reactivation in a pediatric HSCT cohort and analyze the potential impact of recipient/donor-related or transplant-related factors on this complication. Furthermore, we analyzed the management of CMV reactivation in order to purpose criteria for pre-emptive therapy.

Methods: Allogeneic HSCTs, performed at IRCCS Istituto Gaslini between 2012 and 2022, were included in this analysis. CMV-DNAemia was regularly monitored. Risk stratification was based on donor/recipient serological status and additional potential risk factors were considered: haploidentical transplant; any HSCT subsequent to the first; acute and chronic GvHD; steroids; and other immunosuppressive therapies. We described also the approach for pre-emptive therapy during the period 2012-2019.

Results: A total of 214 allogeneic HSCTs were performed in 189 patients. In total, 100 (46.7%) HSCTs were complicated by at least one reactivation. CMV reactivation was significantly associated with high serological risk and steroid treatment. Pre-emptive therapy was administered in 59/69 (85.5%) HSCTs during 2012-2019. In the presence of predefined risk conditions, therapy was started at a median viremia of 2050 copies/mL. No difference was observed in OS between patients with CMV reactivation versus patients who did not present this complication.

Conclusions: These results suggest the potential effectiveness of the approach used in providing pre-emptive therapy based on viral load monitoring and individualized risk factors.

Objective: The study aimed to evaluate the interobserver agreement among glaucoma subspecialists in diagnosing glaucoma and to explore the causes of diagnostic discrepancies. Methods: Three experienced glaucoma subspecialists independently assessed frequency domain optical coherence tomography, fundus color photographs, and static perimetry results from 464 eyes of 275 participants, adhering to unified glaucoma diagnostic criteria. All data were collected from the Wenzhou Glaucoma Progression Study between August 2014 and June 2021. Results: The overall interobserver agreement among the three experts was poor, with a Fleiss' kappa value of 0.149. The kappa values interobserver agreement between pairs of experts ranged from 0.133 to 0.282. In 50 cases, or approximately 10.8%, the three experts reached completely different diagnoses. Agreement was more likely in cases involving larger average cup-to-disc ratios, greater vertical cup-to-disc ratios, more severe visual field defects, and thicker retinal nerve fiber layer measurements, particularly in the temporal and inferior quadrants. High myopia also negatively impacted interobserver agreement. Conclusions: Despite using unified diagnostic criteria for glaucoma, significant differences in interobserver consistency persist among glaucoma subspecialists. To improve interobserver agreement, it is recommended to provide additional training on standardized diagnostic criteria. Furthermore, for cases with inconsistent diagnoses, long-term follow-up is essential to confirm the diagnosis of glaucoma.

Background/Objectives: Spinal conditions, such as fractures and herniated intervertebral discs (HIVDs), are often challenging to diagnose due to overlapping clinical symptoms and the difficulty in assessing their functional impact. Accurate differentiation between these conditions is crucial for effective treatment, particularly in the context of preoperative anesthesia evaluation, where understanding the underlying condition can influence anesthesia planning and pain management. Methods and Materials: This study presents a Support Vector Machine (SVM) model designed to distinguish between spinal fractures and HIVDs using key clinical predictors, including age, gender, preoperative Visual Analog Scale (VAS) pain scores, and the number of spinal fractures. A retrospective analysis was conducted on a dataset of 199 patients diagnosed with these conditions. The SVM model, using a radial basis function (RBF) kernel, classified the conditions based on the selected predictors. Model performance was evaluated using precision, recall, accuracy, and the Kappa index, with Leave-One-Out (LOO) cross-validation applied to ensure robust results. Results: The SVM model achieved a precision of 92.1% for fracture cases and 91.2% for HIVDs, with recall rates of 98.1% for fractures and 70.5% for HIVDs. The overall accuracy was 92%, and the Kappa index was 0.76, indicating substantial agreement. The analysis revealed that age and VAS pain scores were the most critical predictors for accurately diagnosing these conditions. Conclusions: These results highlight the potential of the SVM model with an RBF kernel to reliably differentiate between spinal fractures and HIVDs using routine clinical data. Future work could enhance model performance by incorporating additional clinical parameters relevant to preoperative anesthesia evaluation.

Objectives: To assess the feasibility of 5.0 T magnetic resonance imaging (MRI) in characterizing pancreatic cystic lesions (PCLs), compared with 3.0 T MRI and multidetector computed tomography (MDCT). Methods: Thirty-five patients with PCLs underwent 5.0 T MR alongside 3.0 T MR or MDCT. Two observers measured subjective and objective image quality scores. The consistency of two observers between 5.0 T and 3.0 T was calculated by intraclass correlation coefficients. The characteristics of PCLs and their specific diagnosis, as well as benignity/malignancy, were evaluated across MDCT, 3.0 T, and 5.0 T MRI. Results: The 5.0 T MR demonstrated significantly higher subjective image quality and SNR on T1WI compared to that in 3.0 T MR (p < 0.05). The 5.0 T MRI identified more cyst lesions than the 3.0 T MRI (40 and 32) and MDCT (82 and 56). The sensitivity, specificity, and accuracy for differentiating benign from malignant lesions with 5.0 T MRI (75%, 100%, and 91.4%, respectively) surpassed those of 3.0 T MRI and MDCT. The accuracy of the specific diagnosis of PCLs at 5.0 T MRI (80%) was superior to 3.0 T MRI and MDCT. Conclusions: 5.0 T MRI exhibits certain superiority in delineating details of PCLs and in clinical diagnostic accuracy, outperforming MDCT and 3.0 T MRI while maintaining sufficient image quality.

Background/Objectives: Digital mammography (DM) has long been the standard for breast cancer screening, while digital breast tomosynthesis (DBT) offers an advanced 3D imaging modality capable of generating 2D Synthetic Mammography (SM) images. Despite SM's potential to reduce radiation exposure, many clinics favor DM, with DBT and SM, due to its perceived diagnostic reliability. This study investigates whether radiologists can replace DM with SM in breast cancer screening and diagnosis or if both modalities are necessary. Methods: We retrospectively analyzed DM and SM images from 375 women aged 40-65 who underwent DM with DBT at King Khaled University Hospital from 2020-2022. Three radiologists evaluated the images using ACR BI-RADS, assessing diagnostic accuracy via the area under the receiver operating characteristic (ROC) curve (AUC). The agreement in cancer conspicuity, breast density, size, and calcifications were measured using weighted kappa (κ). Results: Among 57 confirmed cancer cases and 290 cancer-free cases, DM demonstrated higher sensitivity (82.5% vs. 78.9%) and diagnostic accuracy (AUC 0.800 vs. 0.783, p < 0.05) compared to SM. However, SM detected more suspicious calcifications in cancer cases (75.6% vs. 51.2%, p < 0.05). Agreement was fair for conspicuity (κ = 0.288) and calcifications (κ = 0.409), moderate for density (κ = 0.591), and poor for size (κ = 0.254). Conclusions: while SM demonstrates enhanced effectiveness in detecting microcalcifications, DM still proves superior in overall diagnostic accuracy and image clarity. Therefore, although SM offers certain advantages, it remains slightly inferior to DM and cannot yet replace DM in breast cancer screening.

Intraplacental choriocarcinoma (IC) is a gestational trophoblastic neoplasia located within the placenta. Due to its silent presentation, more than half of the cases are diagnosed incidentally. An association with fetomaternal hemorrhage (FMH), stillbirth, and intrauterine growth restriction has been found. The aim of this review is to describe the clinical management of this rare condition stemming from a case report of an incidental diagnosis following an emergency cesarean section, and taking into account the available literature. Emergency interventions and examination of the placenta, even for the smallest IC lesion can ensure timely treatment and improve maternal and fetal outcomes.

Background: Although risk factors associated with maternal postpartum depression (PPD) have been recognized, it is still unknown how some newborn characteristics could influence the appearance of PPD.

Aim: Our research aimed to unravel the impact of a newborn's features on women with PPD.

Methods: The study was conducted in the Obstetrics and Gynecology Department at our University Emergency County Hospital, between August 2019 and April 2021. We included 904 women from the second day of the postpartum period, divided into two groups: women with PPD (n = 236) and control (i.e., women without PPD, n = 668), by using the Edinburg Postpartum Depression Scale. Characteristic information on the newborns (i.e., the months in which they were born, premature delivery, birth weight, or sex) was evaluated.

Results: Our results suggest that the winter season (i.e., December and January months, p = 0.01) births and male newborns (p = 0.02) were strongly related with the appearance of depressive symptoms during the postpartum period.

Conclusions: Therefore, our study sustains that women who give birth to male newborns in the winter season are more prone to developing PPD. This should be analyzed by all public health care systems in order to prevent such a condition earlier in certain groups of women.