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BACKGROUND: In recent decades, machine-learning (ML) technologies have advanced the management of high-dimensional and complex cancer data by developing reliable and user-friendly automated diagnostic tools for clinical applications. Immunohistochemistry (IHC) is an essential staining method that enables the identification of cellular origins by analyzing the expression of specific antigens within tissue samples. The aim of this study was to identify a model that could predict histopathological diagnoses based on specific immunohistochemical markers. METHODS: The XGBoost learning model was applied, where the input variable (target variable) was the histopathological diagnosis and the predictors (independent variables influencing the target variable) were the immunohistochemical markers. RESULTS: Our study demonstrated a precision rate of 85.97% within the dataset, indicating a high level of performance and suggesting that the model is generally reliable in producing accurate predictions. CONCLUSIONS: This study demonstrated the feasibility and clinical efficacy of utilizing the probabilistic decision tree algorithm to differentiate tumor diagnoses according to immunohistochemistry profiles.

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Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented in all fields, including medicine. As a relatively new domain, all efforts are directed towards creating algorithms applicable in most medical specialties. Pathology, as one of the most important areas of interest for precision medicine, has received significant attention in the development and implementation of AI algorithms. This focus is especially important for achieving accurate diagnoses. Moreover, immunohistochemistry (IHC) serves as a complementary diagnostic tool in pathology. It can be further augmented through the application of deep learning (DL) and machine learning (ML) algorithms for assessing and analyzing immunohistochemical markers. Such advancements can aid in delineating targeted therapeutic approaches and prognostic stratification. This article explores the applications and integration of various AI software programs and platforms used in immunohistochemical analysis. It concludes by highlighting the application of these technologies to pathologies such as breast, prostate, lung, melanocytic proliferations, and hematologic conditions. Additionally, it underscores the necessity for further innovative diagnostic algorithms to assist physicians in the diagnostic process.

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Chromophobe renal cell carcinoma (CRCC) is a distinct subtype of renal cell carcinoma with unique histological, immunohistochemical, cytogenetic, and ultrastructural features, which usually has a favorable clinical course, with only a small percentage of patients developing recurrence, metastasis, or death due to its complications. Sarcomatoid differentiation can occur in any subtype of renal cell carcinoma and currently represents the transformation into a higher degree of malignancy, its presence being associated with a reserved prognosis, with a reported incidence of average survival of less than 1 year after diagnosis. In this study, we present an unusual case of CRCC with massive sarcomatoid differentiation, which infiltrated the left adrenal gland and was surgically resected. The histological features of this tumor as well as a brief review of literature are presented.

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Artificial Intelligence (AI) has emerged as a transformative technology with immense potential in the field of medicine. By leveraging machine learning and deep learning, AI can assist in diagnosis, treatment selection, and patient monitoring, enabling more accurate and efficient healthcare delivery. The widespread implementation of AI in healthcare has the role to revolutionize patients' outcomes and transform the way healthcare is practiced, leading to improved accessibility, affordability, and quality of care. This article explores the diverse applications and reviews the current state of AI adoption in healthcare. It concludes by emphasizing the need for collaboration between physicians and technology experts to harness the full potential of AI.

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Struma ovarii (SO) is a monodermal teratoma containing at least 50% thyroid tissue. Classically, SO is a hormonally inactive benign neoplasm that occurs in premenopausal women, and has unspecific clinical and imaging features. Its treatment is surgical and its diagnosis is established histopathologically. We report the case of a euthyroid 16-year-old girl presenting with abdominal girth increase. An abdomino-pelvic ultrasound showed a giant multicystic mass with transonic content and multiple septa, and magnetic resonance imaging suggested the diagnosis of right ovarian mucinous cystadenoma. Blood tests showed inflammatory syndrome, iron deficiency anemia, mild hepatocytolysis, and elevated serum CA 125 levels. High-grade fever occurred on the third day of hospitalization, but none of the preoperative tests could identify its origin. Cystectomy was performed, and the histopathological examination revealed benign SO with a few small cysts with purulent content. The patient developed hypothyroidism postoperatively. In conclusion, this case report reunites most of the uncommon features of SO and confirms the superiorityof histopathology in its definitive diagnosis, as well as the suitability of ovarian sparing techniques, as the best treatment option for cystic ovarian pathology in pediatric patients, even in cases of large tumoral size and elevated serum CA 125 levels.

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Paraovarian cysts (POCs) develop within the broad ligament of the uterus. POCs are considered to be giant when the threshold of 150 mm is exceeded. Clinical signs and symptoms occur as a consequence of the pressure effect on adjacent organs or due to complications. Abdominal ultrasonography, computed tomography or magnetic resonance imaging are useful imaging tools, but most often the exact origin of such voluminous cysts is revealed only by surgical exploration. The review aims to appraise and update the diagnostic, the histological aspects and the treatment of the giant POCs in rare cases. We carried out a systematic search in Medline-PubMed, Google Scholar and ResearchGate electronic databases. Twenty-seven papers fulfilling the selection criteria were included in the review. The data extracted included information about first author, year of publication, country, patient age, size and side of the POCs, symptoms, tumoral markers, imaging methods, preoperative diagnosis, surgical management and histopathological findings. Although not very numerous, all the studies highlighted the low incidence of giant POCs, the impossibility of establishing the origin of the cystic mass by clinical and imaging methods even with advanced technical tools and the low risk of torsion (11.1%). Despite the recognized benign nature of POCs, we found an unexpected high percent (25.9%) of borderline giant POCs. Surgical excision is the only treatment option. Ovarian-sparing surgery was performed in 85.1% of the cases, and minimally invasive techniques were applied in only 42.9% of the patients, which demonstrates the need of a high-level laparoscopic expertise. Knowledge of this pathology, its recognition as a possible etiology of an abdominopelvic cyst, and a higher awareness of the possibility of a borderline histology in giant POCs are required for the proper management of these particular cases.

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ABSTRACT The COVID-19 pandemic has a global effect on people's mental health. The SARS-CoV-2 infection is a new source of anxiety, depression, and psycho-emotional changes in people without morbid conditions, with even more important impact on patients with associated diseases. We present the case of a previously diagnosed patient with COVID-19, in which the psychological effects accumulated during hospitalization triggered an autolytic behaviour. The case presented by us and the review of the literature show that serious diseases are frequently associated with depression and emotional disorders, and SARS-CoV-2 infection is no exception

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Endometrial stromal sarcoma (ESS) is a rare tumor, predominantly occurring as a primary tumor of the uterus. Rare cases of primary extrauterine ESS (EESS) have been reported. Low-grade ESS (LG-ESS) is more common than high-grade ESS (HG-ESS). We present five cases of ESS and one case of EESS. All cases received external radiotherapy (EBRT) at the Radiotherapy Department of the Emergency Clinical Hospital 'Sfantul Apostol Andrei' Galati, during 2004-2020. Five cases underwent EBRT in two-dimensional (2D) technique and only one patient received EBRT with three-dimensinal conformational radiotherapy (3DCRT) technique with a linear accelerator, Elekta Synergy. Five patients were referred to postoperative radiotherapy after hysterectomy. The median age of the patients was 57.4 years. One patient was referred to radiotherapy with palliative intent. EESS localized in the retroperitoneum, in the para-aortic region, was identified in one 64-year-old patient with a personal history of hysterectomy and bilateral salpingo-oophorectomy in 1997; EESS was complicated with vertebral extension at the L1-L2 level and spinal cord compression syndrome. ESS represents a rare diagnosis and a high- or low-grade tumor profile is distinguished by immunohistochemistry (IHC) tests. Up to 30% of patients have EESS at presentation. The treatment of ESS is multimodal, its management requiring a multidisciplinary team, and it is different according to the primary tumor location and tumor staging. The role of adjuvant radiotherapy remains controversial in high-grade EESS and due to the rarity of these cases there are limited data concerning the efficacy of adjuvant EBRT available from prospective randomized control clinical trials.

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The article explores the challenges of ensuring voluntary and informed consent which is obtained from potential research subjects in the north-eastern part of Romania. This study is one of the first empirical papers of this nature in Romania. The study used a quantitative survey design using the adapted Quality of Informed Consent (QuIC) questionnaire. The target population consisted of 100 adult persons who voluntarily enrolled in clinical trials. The informed consent form must contain details regarding the potential risks and benefits, the aim of the clinical trial, study design, confidentiality, insurance and contact details in case of additional questions. Our study confirmed that although all required information was included in the ICF, few clinical trial participants truly understood it. We also found that the most important predictive factor for a good subjective and objective understanding of the clinical trial was the level of education. Our study suggests that researchers should consider putting more effort in order to help clinical trials participants achieve a better understanding of the informed consent. In this way they will ensure that participants' decision-making is meaningful and that their interests are protected.

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