Valentin Bejan

Valentin Bejan


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 January 2024 in Life
Verified
Journal Article
Open access
PDF file
RTRazvan Călin Tiutiuca
Razvan Călin Tiutiuca
APAlina Ioana Nastase Puscasu
Alina Ioana Nastase Puscasu
NSNicoleta Stoenescu
Nicoleta Stoenescu
MMMihaela Moscalu
Mihaela Moscalu
Costel BradeaCostel Bradea
Costel Bradea
Alin Mihai VasilescuAlin Mihai Vasilescu
Alin Mihai Vasilescu
Splenic cysts are rare benign lesions of the spleen, often asymptomatic and incidentally discovered during imaging studies. While many splenic cysts remain asymptomatic and do not require intervention, surgical management becomes essential in cases of symptomatic cysts, large cysts, or when malignancy cannot be ruled out. Laparoscopic surgery has emerged as a minimally invasive and effective approach for treating splenic cysts, offering advantages such as shorter hospital stays, reduced postoperative pain, and faster recovery. In this case report, we describe our experience with laparoscopic surgery for a symptomatic splenic cyst in a young patient.

21 May 2022 in Diagnostics
Verified
Journal Article
Open access
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VBValentin Bejan
Valentin Bejan
Marius PislaruMarius Pislaru
Marius Pislaru
VSViorel Scripcariu
Viorel Scripcariu
Colorectal cancer represents one of the most important causes worldwide of cancer related morbidity and mortality. One of the complications which can occur during cancer progression, is peritoneal carcinomatosis. In the majority of cases, it is diagnosed in late stages due to the lack of diagnostic tools capable of revealing the early-stage peritoneal burden. Therefore, still associates with poor prognosis and quality of life, despite recent therapeutic advances. The aim of the study was to develop a fuzzy logic approach to assess the probability of peritoneal carcinomatosis presence using routine blood test parameters as input data. The patient data was acquired retrospective from patients diagnosed between 2010–2021. The developed model focuses on the specific quantitative alteration of these parameters in the presence of peritoneal carcinomatosis, which is an innovative approach as regards the literature in the field and validates the feasibility of using a fuzzy logic approach in the noninvasive diagnosis of peritoneal carcinomatosis.

29 July 2022 in Healthcare
Verified
Journal Article
Open access
PDF file
VBValentin Bejan
Valentin Bejan
EDElena Niculina Dragoi
Elena Niculina Dragoi
Silvia CurteanuSilvia Curteanu
Silvia Curteanu
VSViorel Scripcariu
Viorel Scripcariu
BFBogdan Filip
Bogdan Filip
The incidence of colon, rectal, and colorectal cancer is very high, and diagnosis is often made in the advanced stages of the disease. In cases where peritoneal carcinomatosis is limited, patients can benefit from newer treatment options if the disease is promptly identified, and they are referred to specialized centers. Therefore, an essential diagnostic benefit would be identifying those factors that could lead to early diagnosis. A retrospective study was performed using patient data gathered from 2010 to 2020. The collected data were represented by routine blood tests subjected to stringent inclusion and exclusion criteria. In order to determine the presence or absence of peritoneal carcinomatosis in colorectal cancer patients, three types of machine learning approaches were applied: a neuro-evolutive methodology based on artificial neural network (ANN), support vector machines (SVM), and random forests (RF), all combined with differential evolution (DE). The optimizer (DE in our case) determined the internal and structural parameters that defined the ANN, SVM, and RF in their optimal form. The RF strategy obtained the best accuracy in the testing phase (0.75). Using this RF model, a sensitivity analysis was applied to determine the influence of each parameter on the presence or absence of peritoneal carcinomatosis.

4 June 2024 in Current Oncology
Verified
Journal Article
Open access
PDF file
DMDan Cristian Moraru
Dan Cristian Moraru
MPMihaela Pertea
Mihaela Pertea
SAStefana Avadanei-Luca
Stefana Avadanei-Luca
VBValentin Bejan
Valentin Bejan
PAPanuta S. Andrian
Panuta S. Andrian
VSViorel Scripcariu
Viorel Scripcariu
Background: Abdominoperineal resection (APR)—the standard surgical procedure for low-lying rectal cancer (LRC)—leads to significant perineal defects, posing considerable reconstruction challenges that, in selected cases, necessitate the use of plastic surgery techniques (flaps). Purpose: To develop valuable decision algorithms for choosing the appropriate surgical plan for the reconstruction of perineal defects. Methods: Our study included 245 LRC cases treated using APR. Guided by the few available publications in the field, we have designed several personalized decisional algorithms for managing perineal defects considering the following factors: preoperative radiotherapy, intraoperative position, surgical technique, perineal defect volume, and quality of tissues and perforators. The algorithms have been improved continuously during the entire period of our study based on the immediate and remote outcomes. Results: In 239 patients following APR, the direct closing procedure was performed versus 6 cases in which we used various types of flaps for perineal reconstruction. Perineal incisional hernia occurred in 12 patients (5.02%) with direct perineal wound closure versus in none of those reconstructed using flaps. Conclusion: The reduced rate of postoperative complications suggests the efficiency of the proposed decisional algorithms; however, more extended studies are required to categorize them as evidence-based management guide tools.