bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical and histopathological spectrum of cranial small round cell tumors: An experience from a tertiary care center
Authors: Gupta Pooja , Siraj Fouzia , Shankar K.B , Rawat Manish , Mankotia Dipanker S. , Yadav Vivek , Dagar Amit 
Published: March 2024

Background:
Small round cell tumors (SRCTs) are a group of malignant neoplasms with minimal or no differentiation, characterized by the presence of round cells with high nuclear-cytoplasmic ratio. Although SRCTs can occur in any part of the body, involvement of central nervous system (CNS) is uncommon.

Aim:
We aimed to study the clinicopathological spectrum of cranial SRCT diagnosed in our institute over a period of four years (2016–2019).

Material and Methods:
A retrospective review of medical records (2016–2019) with a morphological diagnosis of cranial SRCT was made. Both intra-axial and extra-axial tumors were included. A total of 60 cases were retrieved, and the clinical and histopathological features were studied. Special cytochemical staining and immunohistochemistry were performed, where needed.

Results:
The mean age at presentation was 18.4 years (range, 1–60 years), with a male-to-female ratio of 2.5:1. The most common site was posterior fossa of brain (n = 28, 47%), followed by dorso-lumbar spine (n = 9, 15%). The most common type of tumor was medulloblastoma (n = 29, 48.3%), followed by Ewing sarcoma (ES)/peripheral primitive neuroectodermal tumor (pPNET) (n = 11, 18.3%), non-Hodgkin lymphoma (NHL) (n = 9, 15%), neuroblastoma (n = 3, 5%), and CNS embryonal tumor, NOS (n = 2, 3.3%). One case each of atypical teratoid rhabdoid tumor (ATRT), rhabdomyosarcoma, pineoblastoma, melanoma, rhabdomyosarcoma, and undifferentiated pleomorphic sarcoma was also documented.

Conclusions:
SRCTs have a variable age of presentation. Their incidence in CNS is low as compared to other organ systems. On light microscopy, the histopathology of these lesions is overlapping, posing a great diagnostic dilemma for the pathologist. The use of ancillary techniques like immunohistochemistry helps in arriving at the correct diagnosis. Treatment strategy and tumor prognosis also vary along the entire spectrum of SRCT, thus making exact characterization essential for proper management.
Protective effects of Panax Ginseng against 131I-induced genotoxicity in patients with differentiated thyroid cancer
Authors: Omrani Vida , Fardid Reza , Alavi Mehrosadat , Haddadi Golamhassan , Takhshid Mohammad Ali 
Published: March 2024

Background:
Radioiodine (131I) therapy (RAIT) is associated with oxidative stress (OS)-induced DNA damage in patients with differentiated thyroid cancer (DTC). The goal of this study was to evaluate the possible ameliorating effects of Panax Ginseng (PG) on RAIT-induced genotoxicity in patients with DTC.

Materials and Methods:
Forty DTC patients who had received 131I (100 to 175 mCi) were enrolled in this study. The patients were randomly classified (n = 10) into control, placebo, PG1 groups (receiving 500 mg/day of PG for 2 days before RAIT), and PG2 group (receiving 500 mg/day of PG for 2 days before to 1 day after RAIT). Blood samples were collected before and 2 days after RAIT. Lymphocyte micronuclei (MN) frequency was measured using the MN assay. Serum total antioxidant capacity (TAC) and ischemia-modified albumin (IMA) were measured using colorimetric assays. Serum albumin, blood urea nitrogen (BUN), creatinine, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were measured using commercial kits.

Results:
The mean of baseline MN frequency was the same in the four groups. RAIT increased the MN frequencies to at least three times the baseline values in the control (39 ± 5) and placebo groups (38 ± 6) (P < 0.001). PG caused a significant decrease in the MN frequencies in the treated groups compared to the control and placebo groups (P < 0.001). RAIT and PG administration had no significant effects on the serum IMA, TAC, and markers of liver and kidney toxicity.

Conclusion:
PG could be considered a useful remedy for the protection against RAIT-induced chromosomal damage in DCT patients.
Breast self-examination practices among young rural women and its associated knowledge and attitudes in Tirunelveli District, Tamil Nadu
Authors: Selvam Mahalakshmi , Sundaram Suresh 
Published: March 2024

Context:
Breast self-examination (BSE) is a simple and cost-effective screening procedure in downstaging breast tumors.

Aim:
To assess the BSE practices and its associated knowledge and attitudes of rural women from Tirunelveli District, Tamil Nadu during the COVID-19 pandemic.

Settings and Design:
A descriptive cross-sectional survey design was employed, and snowball sampling was used to recruit the sample of rural women from Tirunelveli.

Materials and Methods:
Women ages 18–60 willing to take part were included. Data were collected online through a self-developed questionnaire.

Statistical Analysis:
Responses were analyzed using SPSS Version 20. Descriptive statistical analysis was used to present the general details and responses of the rural women through percentages. Using the appropriate tests, the mean differences of the BSE attitudes based on the personal variables were computed using one-way ANOVA.

Results:
A total of 433 rural women (Mean age: 29.20 ± 9.35 years) from Tirunelveli responded to the online Knowledge, Attitude and Practice (KAP) questionnaire. Regular health checkups were undergone by 27.48% of women and 9.24% underwent breast cancer (BC) screening in the past. While 68.36% had heard of BC, 61% knew it could be detected in the early stages. Insufficient knowledge regarding BSE techniques was evident among the women. Knowledge about BC was highest among those earning more than 20,001 INR, women aged 36–45, widowed/separated/divorced women, and diploma graduates. Overall, BSE and BC knowledge score was low, with correspondingly low attitudes and practices.

Conclusion:
Findings showed the KAP among rural Tirunelveli women to be low.
CD146 as a prognostic marker in breast cancer: A meta-analysis
Authors: Sharma Akshita , Somasundaram Indumathi , Chabaud Marcel Blot 
Published: March 2024

Background:
CD146, a cell adhesion molecule, was first discovered in melanoma. Since then, it has been established as a promoter of tumor progression and metastasis. Many recent clinical studies have associated CD146 overexpression with poor prognosis in various cancers. However, clinical relevance of CD146 in prognosis of breast cancer has been poorly studied.

Methods:
We performed meta-analysis of data of all clinical studies associated with the prognostic value of CD146 expression in breast cancer. Relevant studies were retrieved from PubMed database as per the inclusion and exclusion criteria, data were extracted independently and carefully by two reviewers with the help of standardized form, and meta-analysis was performed to correlate CD146 expression with molecular subtypes, lymph node metastasis, and overall survival in breast cancer.

Results:
Our findings suggest that CD146 expression is predominantly found in triple-negative breast cancer subtype (pooled odds ratio = 2.98, 95% confidence interval [CI] =2.19–4.05, P < .00001) and breast tumors overexpressing CD146 have a higher risk of lymph node metastasis (pooled relative risk = 1.64, 95% CI = 1.44–1.87, P < .00001). Furthermore, high expression of CD146 was associated with poor prognosis in breast cancer (pooled hazard ratio = 1.51, 95% CI = 1.21–1.87, P = .0002).

Conclusion:
Overall results suggested that CD146 may be a potential prognostic marker to predict metastatic potential and disease outcomes in breast cancer and can be used as a therapeutic target.
Prognostic factors in T4b gastric cancer after surgery: A more balanced and sequential therapy for patients?
Authors: Nakamura Naohiko , Kinami Shinichi , Kaida Daisuke , Tomita Yasuto , Miyata Takashi , Miyashita Tomoharu , Fujita Hideto , Ueda Nobuhiko , Takamura Hiroyuki 
Published: March 2024

Introduction:
This study aimed to evaluate the prognostic factors in T4b gastric cancer (GC) in order to improve future therapeutic strategies.

Methods:
We retrospectively analyzed the medical records of 43 patients with advanced GC who underwent surgery and were surgically or pathologically diagnosed with T4b GC. The overall survival (OS) rate of patients with T4b GC was analyzed, and univariate and multivariate analyses were performed to identify clinicopathological factors that were independently associated with OS. In addition, we assessed the relationship between postoperative chemotherapy and laboratory parameters 4 weeks post-surgery.

Results:
The proportion of patients with invasion of cancer in organs, including the pancreas, transverse colon, and liver, were 58.1%, 18.6%, and 14.0%, respectively. The proportion of patients who exhibited distant metastases was 44.2%, and R0 resection was achieved in 30.2% of patients. A total of 69.8% of patients underwent postoperative chemotherapy. The median survival rate was 12.3 months. Upon multivariate analysis, the presence of distant metastases (P = 0.01, HR; 3.48), the use of postoperative chemotherapy (P = 0.0004, HR; 0.12), and R0 resection (P < 0.0001, HR; 0.14) were significantly correlated with OS. Patients who did not undergo postoperative chemotherapy showed significantly higher levels of inflammatory parameters and lower levels of nutritional parameters 4 weeks after surgery than those who did.

Conclusions:
We evaluated that the presence of distant metastases was significantly associated with a poor prognosis, and the use of postoperative chemotherapy and R0 resection was significantly associated with a better prognosis in patients with T4b GC. It would be more important for a T4b GC treatment to balance between therapeutic tolerance for postoperative chemotherapy and surgical therapeutic effect.
Characteristics of patients with late recurrence endometrial cancer
Authors: Çakır İlker , Gülseren Varol , Özdemir İsa Aykut , Abacı Hüseyin , Talu Esra Canan Kelten , Çakır Zübeyde Emiralioğlu , Ata Can , Kuru Oğuzhan , Gökçü Mehmet , Sancı Muzaffer , Güngördük Kemal 
Published: March 2024

Aim:
We planned this study to assess endometrial cancer (EC) patients who had late metastasis.

Materials and Methods:
This retrospective study constituted a review of the records of patients who were diagnosed with EC and underwent hysterectomy at the Gynecologic Oncology Clinic between 1996 and 2018. Relapses occurring after the first three years following primary treatment of EC are considered late recurrences. Post-relapse survival (PRS) refers to the time to the last follow-up or the patient’s death after relapse.

Results:
Late metastases were identified in 42 patients, 20 (47.6%) of whom had locoregional recurrence and 22 of whom (52.4%) had extrapelvic recurrence. Median disease-free survival (DFS) times were 61 (range: 43–78) and 65 (range: 48–81) months for the groups with locoregional and extrapelvic recurrences, respectively (P = 0.462). The 5-year PRS rate for the patients was 61.1%, with 63.8% having locoregional and 59.4% having extrapelvic late metastasis (P = 0.969).

Conclusion:
Among the patients with late metastases, those with endometrioid type EC were found to have a better prognosis. It has been shown that locoregional or extrapelvic organ recurrence does not significantly affect survival in patients with late relapse. Although our results are not statistically significant for cases of locoregional late metastases, surgical resection increases survival rates.
Bupropion Associated Immunomodulatory Effects on Peripheral Cytokines in Male with Major Depressive Disorder
Authors: Huang Chih-Chung , Chu Hsuan-Te , Lin Yu-Kai , Tsai Chia-Kuang , Liang Chih-Sung , Yeh Ta-Chuan 
Published: March 2024

Background:
Experimental and clinical studies have reported increased levels of pro-inflammatory cytokines in patients with major depressive disorder (MDD), suggesting that immune system dysregulation may contribute to MDD pathophysiology.

Aim:
Due to the lack of knowledge about the immune potential of antidepressants, this study investigated the immunomodulatory effects of bupropion, a norepinephrine–dopamine reuptake inhibitor.

Methods:
This study involved 18 patients with MDD treated with bupropion (150 mg/d) for 4 weeks and 23 healthy volunteers. All participants underwent multiplex bead-based cytokine assessment before and after bupropion treatment to quantify the following cytokines: interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-13, IL-17, interferon-γ, tumor necrosis factor-α, granulocyte colony-stimulating factor, granulocyte-macrophage CSF, monocyte chemotactic protein-1, and macrophage inflammatory protein-1β.

Results:
Four-week treatment with bupropion significantly increased the levels of IL-1β (P = 0.011), IL-4 (P = 0.019), IL-5 (P = 0.019), IL-7 (P = 0.021), and IL-8 (P = 0.023) compared to the control group. Furthermore, the percentage change in most cytokines, including anti-inflammatory cytokines such as IL-4, IL-5, IL-10, and IL-13, was significantly increased after bupropion treatment.

Conclusion:
The promoted synthesis of anti-inflammatory cytokines to surpass the pro-inflammatory cytokines may be a crucial step in the treatment of MDD patients with bupropion.
Cephalometric Prediction of Risk Factors for Mandibular Third Molar Impaction
Authors: Lee Wei-Cheng , Yuh Da-Yo , Sung Cheng-En , Wu Yu-Chiao , Chen Ying-Wu , Chen Wei-Liang 
Published: March 2024

Background:
Mandibular third molar impaction in adult patients is one of the most common problems in dental practice. However, limited data are available on the association between mandibular third molar impaction and craniofacial skeletal problems.

Aim:
This study aimed to establish a prediction model to evaluate the risk factors for mandibular third molar impaction.

Methods:
Panoramic and lateral cephalometric radiographs of orthodontic patients aged ≥20 years were obtained from the Tri-Service General Hospital. The radiographs were analyzed by a single examiner. Panoramic radiographs were used to evaluate the mandibular third molar impaction. Lateral cephalometric radiographs were used to evaluate five linear and six angular measurements to define the facial pattern of the participants. The association between cephalometric measurements and mandibular third molar impaction was determined using one-way analysis of variance and logistic regression analysis.

Results:
This study included 60 participants. The incidence of mandibular third molar impaction was associated with the mandibular plane angle (MPA) and mandibular length (Co-Gn) (P < 0.001). The presence of mandibular third molar impaction was found to gradually increase with increasing MPA and decreasing mandibular length.

Conclusion:
Individuals with a greater MPA and lesser mandibular length had a higher incidence of mandibular third molar impaction.
Novel Artificial Intelligence Tool for Real-time Patient Identification to Prevent Misidentification in Health Care
Authors: Rajurkar Shriram , Verma Teerthraj , Mishra S P , Bhatt MLB 
Published: March 2024

Purpose:
Errors in the identification of true patients in a health-care facility may result in the wrong dose or dosage being given to the wrong patient at the wrong site during radiotherapy sessions, radiopharmaceutical administration, radiological scans, etc. The aim of this article is to reduce the error in the identification of correct patients by implementation of the Python deep learning-based real-time patient identification program.

Materials and Methods:
The authors utilized and installed Anaconda Prompt (miniconda 3), Python (version 3.9.12), and Visual Studio Code (version 1.71.0) for the design of the patient identification program. In the field of view, the area of interest is merely face detection. The overall performance of the developed program is accomplished over three steps, namely image data collection, data transfer, and data analysis, respectively. The patient identification tool was developed using the OpenCV library for face recognition.

Results:
This program provides real-time patient identification information, together with the other preset parameters such as disease site, with a precision of 0.92%, recall rate of 0.80%, and specificity of 0.90%. Furthermore, the accuracy of the program was found to be 0.84%. The output of the in-house developed program as “Unknown” is provided if a patient’s relative or an unknown person is found in restricted region.

Interpretation and Conclusions:
This Python-based program is beneficial for confirming the patient’s identity, without manual interventions, just before therapy, administering medications, and starting other medical procedures, among other things, to prevent unintended medical and health-related complications that may arise as a result of misidentification.
PAHPhysRAD: A Digital Imaging and Communications in Medicine Research Tool for Segmentation and Radiomic Feature Extraction
Authors: Arrington Daniel , Motley Ryan , Colbert Zachery Morton , Lehman Margot , Ramachandran Prabhakar 
Published: March 2024

Introduction:
Segmentation and analysis of organs at risks (OARs) and tumor volumes are integral concepts in the development of radiotherapy treatment plans and prediction of patients’ treatment outcomes.

Aims:
To develop a research tool, PAHPhysRAD, that can be used to semi- and fully automate segmentation of OARs. In addition, the proposed software seeks to extract 3214 radiomic features from tumor volumes and user-specified dose-volume parameters.

Materials and Methods:
Developed within MATLAB, PAHPhysRAD provides a comprehensive suite of segmentation tools, including manual, semi-automatic, and automatic options. For semi-autosegmentation, meta AI’s Segment Anything Model was incorporated using the bounding box methods. Autosegmentation of OARs and tumor volume are implemented through a module that enables the addition of models in Open Neural Network Exchange format. To validate the radiomic feature extraction module in PAHPhysRAD, radiomic features extracted from gross tumor volume of 15 non-small cell lung carcinoma patients were compared against the features extracted from 3D Slicer™. The dose-volume parameters extraction module was validated using the dose volume data extracted from 28 tangential field-based breast treatment planning datasets. The volume receiving ≥20 Gy (V20) for ipsilateral lung and the mean doses received by the heart and ipsilateral lung, were compared against the parameters extracted from Eclipse.

Results:
The Wilcoxon signed-rank test revealed no significant difference between the majority of the radiomic features derived from PAHPhysRAD and 3D Slicer. The average mean lung and heart doses calculated in Eclipse were 5.51 ± 2.28 Gy and 1.64 ± 1.98 Gy, respectively. Similarly, the average mean lung and heart doses calculated in PAHPhysRAD were 5.45 ± 2.89 Gy and 1.67 ± 2.08 Gy, respectively.

Conclusion:
The MATLAB-based graphical user interface, PAHPhysRAD, offers a user-friendly platform for viewing and analyzing medical scans with options to extract radiomic features and dose-volume parameters. Its versatility, compatibility, and potential for further development make it an asset in medical image analysis.
Deep Learning-based Lung dose Prediction Using Chest X-ray Images in Non-small Cell Lung Cancer Radiotherapy
Authors: Aoyama Takahiro , Shimizu Hidetoshi , Koide Yutaro , Kamezawa Hidemi , Fukunaga Jun-Ichi , Kitagawa Tomoki , Tachibana Hiroyuki , Suzuki Kojiro , Kodaira Takeshi 
Published: March 2024

Purpose:
This study aimed to develop a deep learning model for the prediction of V20 (the volume of the lung parenchyma that received ≥20 Gy) during intensity-modulated radiation therapy using chest X-ray images.

Methods:
The study utilized 91 chest X-ray images of patients with lung cancer acquired routinely during the admission workup. The prescription dose for the planning target volume was 60 Gy in 30 fractions. A convolutional neural network-based regression model was developed to predict V20. To evaluate model performance, the coefficient of determination (R
2), root mean square error (RMSE), and mean absolute error (MAE) were calculated with conducting a four-fold cross-validation method. The patient characteristics of the eligible data were treatment period (2018–2022) and V20 (19.3%; 4.9%–30.7%).

Results:
The predictive results of the developed model for V20 were 0.16, 5.4%, and 4.5% for the R
2, RMSE, and MAE, respectively. The median error was −1.8% (range, −13.0% to 9.2%). The Pearson correlation coefficient between the calculated and predicted V20 values was 0.40. As a binary classifier with V20 <20%, the model showed a sensitivity of 75.0%, specificity of 82.6%, diagnostic accuracy of 80.6%, and area under the receiver operator characteristic curve of 0.79.

Conclusions:
The proposed deep learning chest X-ray model can predict V20 and play an important role in the early determination of patient treatment strategies.
Improvement of Whole-body Bone Planar Images on a Bone-dedicated Single-photon Emission Computed Tomography Scanner by Blind Deconvolution Algorithm
Authors: Wang Zhexin , Liu Hui , Cheng Li , Lyu Zhenlei , Gao Lilei , Jiang Nianming , He Zuoxiang , Liu Yaqiang 
Published: March 2024

Purpose:
We have developed a bone-dedicated collimator with higher sensitivity but slightly degraded resolution on single-photon emission computed tomography (SPECT) for planar bone scintigraphy, compared with conventional low-energy high-resolution collimator. In this work, we investigated the feasibility of using the blind deconvolution algorithm to improve the resolution of planar images on bone scintigraphy.

Materials and Methods:
Monte Carlo simulation was performed with the NCAT phantom for modeling bone scintigraphy on the clinical dual-head SPECT scanner (Imagine NET 632, Beijing Novel Medical Equipment Ltd.) equipped with the bone-dedicated collimator. Maximum likelihood estimation method was used for the blind deconvolution algorithm. The initial estimation of point spread function (PSF) and iteration number for the method were determined by comparing the deblurred images obtained from different input parameters. We simulated different tumors in five different locations and with five different diameters to evaluate the robustness of the initial inputs. Furthermore, we performed chest phantom studies on the clinical SPECT scanner. The quantified increased contrast ratio (CR) between the tumor and the background was evaluated.

Results:
The 2 mm PSF kernel and 10 iterations provided a practical and robust deblurred image on our system. Those two inputs can generate robust deblurred images in terms of the tumor location and size with an average increased CR of 21.6%. The phantom studies also demonstrated the ability of blind deconvolution, using those two inputs, with increased CRs of 17%, 17%, 22%, 20%, and 13% for lesions with diameters of 1 cm, 2 cm, 3 cm, 4 cm, and 5 cm, respectively.

Conclusions:
It is feasible to use the blind deconvolution algorithm to deblur the planar images for SPECT bone scintigraphy. The appropriate values of the PSF kernel and the iteration number for the blind deconvolution can be determined using simulation studies.