Vol 28, No 4 (2025)
- Year: 2025
- Published: 11.03.2026
- Articles: 5
- URL: https://rjmseer.com/1560-9537/issue/view/14507
- DOI: https://doi.org/10.17816/MSER.284
Original study articles
Correlation between pelvic MRI findings and functional disorders after multimodal treatment of rectal cancer
Abstract
BACKGROUND: The number of patients under long-term follow-up who have been treated for rectal cancer (RC) continues to increase annually. A distinctive feature of surgical treatment is that, in addition to its primary therapeutic effect, it is invariably associated with operative trauma of varying severity. Patient quality of life may be remarkably impaired by the development of low anterior resection syndrome (LARS), which leads to social and occupational maladaptation. Previous studies have demonstrated the importance of pelvic magnetic resonance imaging (MRI) for accurate assessment of RC at the stage of primary diagnosis; however, the use of an original pelvic MRI protocol for the evaluation of functional disorders in this patient population has not previously been investigated.
AIM: To perform a correlation analysis between pelvic MRI findings after multimodal treatment of RC, the patterns and timing of scar–fibrotic changes in the presacral space following anterior and low anterior resection of the rectum, and functional disorders manifested as LARS.
METHODS: The study presents MRI findings from 40 patients after multimodal treatment of locally advanced RC stages T3 (crm+)–4N0–2M0, including neoadjuvant radiotherapy and systemic cytotoxic therapy. The subsequent treatment stage, performed 3–4 months later, consisted of sphincter-preserving surgery in the form of anterior or low anterior rectal resection. Pelvic MRI changes observed 3–24 months after multimodal treatment were analyzed, including presacral fibrosis and pelvic organ prolapse, and correlated with the severity of LARS assessed using the validated Low Anterior Resection Syndrome (LARS) score questionnaire.
RESULTS: The severity of presacral scar formation demonstrated a strong positive correlation (0.912) with substantial functional impairment according to the LARS questionnaire. A moderate inverse correlation was observed with tumor location less than 5 cm from the anal verge (−0.329) and with the postoperative period of up to 6 months (−0.356).
CONCLUSION: Knowledge of post-radiation and postoperative pelvic MRI patterns and the characteristics of scar–fibrotic changes allows prediction of the development of functional disorders in the form of low anterior resection syndrome. Follow-up of patients with pelvic scarring should be individualized, with determination of optimal intervals between imaging examinations to enable monitoring and prediction of functional recovery of the rectal sphincter apparatus.
181-188
On medical and social support for relatives of patients with cancer
Abstract
BACKGROUND: The problem of adequate medical and social support in oncological disease is relevant not only because of high cancer mortality rates but also because cancer often require complex and sometimes aggressive treatment with an initially unfavorable prognosis. In such circumstances, relatives of patients become actively involved in care and support, frequently experiencing psychoemotional, physical, and financial difficulties, which makes them both potential and actual recipients of various forms of assistance.
AIM: To develop proposals for the prevention of health disorders among family members of patients with cancer.
METHODS: The study included 300 relatives of patients receiving specialized oncological care. Data were collected using a specially designed questionnaire. Informed consent for participation in the studt was an inclusion criterion. Statistical analysis was performed using applied programs in Microsoft Office Excel.
RESULTS: All respondents reported experiencing stress related to their relative’s oncological disease; 161 individuals (53.6%) experienced constant stress, 43 (14.3%) several times per week, and 96 (32.1%) less frequently. Persistent fatigue and exhaustion were constantly experienced by every fourth respondent (75; 25.0%), and by 54 respondents (17.9%) several times per week; feelings of helplessness or despair related to the condition of the ill relative were reported by 96 respondents (32.1%) constantly and by 54 respondents (17.9%) several times per week. Anxiety and worry about the relative’s health were constantly present in 139 participants of survey (46.4%) and frequently in 86 (28.6%). Irritability was reported by 75 respondents (25.0%), and depressive symptoms by 11 (3.6%). Emotional problems were more pronounced among women. Substantial financial difficulties were reported by half of the respondents. At the time of the survey, 118 respondents (39.3%) were satisfied with their lives, 115 (38.3%) were partially satisfied, and 67 (22.4%) were dissatisfied. Full access to medical and social support for patients with cancer was reported by 107 respondents (35.7%), whereas access to medical and informational support was reported by 139 (46.4%). The most frequently identified unmet need was psychological support (214 respondents; 71.4 per 100 surveyed).
CONCLUSION: Expanding access to palliative and social care for patients with cancer (particularly in rural and remote regions) represents an important direction for the prevention of health disorders and rehabilitation of patients’ relatives.
189-199
Reviews
Modern approaches to comprehensive rehabilitation and disability assessment criteria for patients with post-stroke cognitive impairment
Abstract
Post-stroke cognitive impairment (PSCI) represents a considerable medical and social problem, acting as a key factor contributing to increased disability among patients who have experienced stroke. Current epidemiological data indicate a high prevalence of PSCI, reaching up to 96% when comprehensive neuropsychological testing is applied. The socioeconomic burden of PSCI is associated with an increased risk of mortality, the development of affective disorders, and the need for long-term specialized care, as well as substantial direct and indirect economic losses (Fragment 7). The aim of this review is to analyze current scientific evidence regarding effective approaches to comprehensive rehabilitation and the improvement of disability assessment (DA) criteria for patients with PSCI. The authors conducted a scientific data search covering the period from 2018 to 2025 in international bibliographic databases, including PubMed / Ovid MEDLINE, ScienceDirect, Google Scholar, and eLIBRARY. As a result, 77 relevant studies were selected for analysis. The review of the scientific data demonstrates that modern rehabilitation of patients with PSCI is based on the principles of a multidisciplinary approach integrating cognitive training, dosed physical activity, noninvasive neuromodulation, and psychotherapeutic support. Combined rehabilitation strategies aimed at modulating neuroplasticity mechanisms have been shown to be the most effective. It was found that the existing DA system has systemic limitations in the objective assessment of the cognitive component of disability, failing to adequately account for the substantial impact of executive dysfunction on activities of daily living and work capacity. Promising directions for the development of care systems for patients with PSCI include the creation of integrative rehabilitation–expert data transfer models, the implementation of standardized neuropsychological diagnostic protocols using validated scales (e.g., MoCA and functionally oriented tests), and the modification of DA criteria in accordance with current concepts of PSCI pathogenesis and clinical manifestations. The implementation of these approaches may optimize the effectiveness of rehabilitation programs and improve the accuracy and efficiency of DA in patients with PSCI.
201-216
The role of artificial intelligence in post-stroke rehabilitation
Abstract
Stroke remains one of the leading causes of disability and mortality worldwide. It results from impaired cerebral blood supply and leads to pronounced neurological deficits that negatively affect patients’ quality of life. Artificial intelligence (AI) technologies, including machine learning, convolutional neural networks, and brain–computer interfaces, enable reproduction of mechanisms underlying natural neural recovery. AI-based rehabilitation systems are capable of analyzing individual patient characteristics and adapting therapeutic strategies in real time, which is analogous to the processes of biological neuroplasticity in the brain. The scientific data search was conducted using international and Russian electronic databases, including PubMed, Google Scholar, and eLibrary.ru. Search queries were formulated using keywords and phrases reflecting the key aspects of post-stroke rehabilitation with AI technologies: искусственный интеллект (artificial intelligence), реабилитация после инсульта (post stroke rehabilitation), инсульт (stroke), машинное обучение (machine learning), нейрореабилитация (neurorehabilitation), artificial intelligence, stroke rehabilitation, stroke, machine learning, neurorehabilitation, and telemedicine. The integration of advanced neuroimaging techniques enhanced by AI algorithms has contributed to the modernization of diagnostic approaches, particularly through the application of deep learning methods for the analysis of computed tomography and magnetic resonance imaging data, as well as for the automated identification of the ischemic penumbra. Prognostic modeling based on machine learning algorithms enables the prediction of functional recovery outcomes, the risk of complications, and the degree of disability. The implementation of AI in post-stroke care raises a number of ethical, legal, and regulatory challenges that must be addressed to ensure its effective use. AI is a tool capable of exerting a positive impact on the rehabilitation of patients after stroke, and its integration into the treatment process offers broad prospects; however, it is associated with a number of challenges that must be addressed to fully realize its potential. Despite such issues as data heterogeneity and the need for interdisciplinary collaboration, advances in artificial intelligence technologies may contribute to improved outcomes of post-stroke rehabilitation.
217-230
Impact of environmental factors in industrial cities on the development, course, and outcomes of cerebrovascular condition in patients with metabolic syndrome: medical and social aspects
Abstract
In the context of global urbanization and the increasing prevalence of metabolic syndrome (MetS), the impact of environmental factors characteristic of industrial cities on the incidence and severity of cerebrovascular diseases (CVD) has become particularly relevant. This narrative review analyzes the interaction between the pathophysiological components of MetS (insulin resistance, hypertension, dyslipidemia, and visceral obesity) and environmental factors specific to industrial cities. The available evidence demonstrates that these factors act synergistically to exacerbate key mechanisms of vascular injury, including systemic inflammation, oxidative stress, and endothelial dysfunction. This interaction contributes to the accelerated development and progression of atherosclerosis and cerebral microangiopathy, as well as to an increased risk of both first-ever and recurrent acute CVD. The review highlights the heightened vulnerability of patients with MetS to the adverse effects of air pollutants, which creates a vicious pathogenic cycle clinically manifested by more severe neurological deficits, poorer functional outcomes, accelerated cognitive decline, and reduced effectiveness of rehabilitation programs. It is also noted that existing prognostic scales (e.g., CHA₂DS₂-VASc) and medical–social disability assessment criteria do not account for exposures to environmental factors, thereby limiting their clinical utility and contributing to suboptimal rehabilitation outcomes in patients with CVD and its sequelae. Based on the analyzed data, there is a clear need to develop comprehensive predictive and preventive strategies that encompass not only individualized correction of metabolic disturbances and the implementation of personalized rehabilitation programs, but also large-scale environmental and urban planning interventions aimed at reducing air and noise pollution. In addition, the development of rehabilitation programs oriented to urban environmental conditions is required to reduce the medical, social, and economic burden on healthcare systems in industrial regions.
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