INTRODUCTION: Takayasu’s aortoarteritis (TA) is a chronic inflammatory systemic vasculitis affecting large vessels, primarily the aorta and its branches. The disease is more common in young women and leads to progressive stenosis, occlusion, aneurysms, and severe systemic complications.

Diagnosis of Takayasu’s disease is based on a comprehensive assessment of the clinical picture, laboratory data, and imaging techniques such as magnetic resonance angiography, computed tomography angiography, ultrasound, positron emission tomography, and digital subtraction X-ray angiography. Accurate diagnosis is critical for timely initiation of therapy and prevention of complications.

OBJECTIVE: To highlight the key aspects of the etiopathogenesis and clinical presentation of the disease. To analyze and systematize current diagnostic imaging capabilities for Takayasu’s disease, based on the ACR/EULAR-2022 consensus of professional societies. To demonstrate typical radiographic patterns of the disease. To highlight the capabilities and prospects of new diagnostic techniques, including spectral (dual-energy) computed tomography.

MATERIALS AND METHODS: A search was conducted in the scientific databases PubMed/MEDLINE, Web of Science, eLibrary using keywords: «nonspecific Takayasu’s aortoarteritis», «Takayasu’s disease», in combination with «radiation diagnostics», «ultrasound», «MRI», «spectral CT», «PET-CT». Inclusion criteria: professional society guidelines (EULAR, ACR/VF), systematic reviews/meta-analyses, and original studies on the imaging of Takayasu’s disease. Duplicates and irrelevant publications were excluded. Data on the etiopathogenesis of the disease, the objectives of diagnostic methods, diagnostic criteria, the accuracy of the methods, limitations, and dose load were extracted.

RESULTS: A total of 173 scientific publications were analyzed, 36 of which were used to compile this review. This review presents data on the key aspects of the etiopathogenesis of Takayasu’s disease and its clinical diagnostic criteria. It also highlights issues of multimodal imaging diagnostics, indicating the sensitivity and specificity of diagnostic techniques. It also examines the capabilities and prospects of spectral (dual-energy) computed tomography and other new imaging techniques.

CONCLUSION: Modern diagnostic imaging methods play a key role in the diagnosis and treatment monitoring of Takayasu’s disease. Their use, in accordance with the clinical task being addressed, significantly contributes to the comprehensive diagnosis of the disease, enabling the development of optimal treatment strategies aimed at reducing the risk of complications and improving patients’ quality of life.

INRODUCTION: Proton magnetic resonance spectroscopy (MR spectroscopy, MRS) allows determining tissue metabolite concentrations in the region of interest. Clinically used MR spectroscopy pulse sequences solve two main problems: voxel localization and water signal suppression. The spectra obtained in this way are a superposition of all signals from the region of interest, so the most reliable information can be obtained only about a small number of metabolites with the highest concentrations. The remaining metabolites have low concentrations and/or have complex peak splitting, and are overlapped by more intense signals. Spectral editing is a method for identifying these metabolites in clinically available systems (<3T). This review briefly presents spectral editing methods, discusses post-processing methods for such spectra, and discusses the main results of studies using spectral editing. Spectral editing methods have shown that the concentrations of γ-aminobutyric acid, lactate, aspartate, N-acetylaspartate and N-acetylaspartylglutamate, 2-hydroxyglutarate, glutathione, and glutamate change in various diseases. The methods and research results considered in this review will allow clinicians to suggest and test new approaches to diagnosing diseases of the central nervous system. 

OBJECTIVE: To describe methods for editing the ¹H MRS spectrum in human studies and to present some of the main results of the application of these measurements.

CONCLUSION: Using the most effective editing methods to optimize information in human brain proton spectra is a highly complex technical process. However, the application of the editing techniques discussed in this lecture allows us to obtain unique and invaluable information on the intracellular concentrations of several key metabolites, which undoubtedly enhances our understanding of brain metabolism in health and disease.

INTRODUCTION: A large amount of information, including a growing population and the number of studies significantly increases the workload of a doctor of any specialty, including a radiologist. Digitalization of research makes it possible to facilitate diagnostic processes, because competent software helps a specialist to quickly detect a pathological process, and therefore — to start muchneeded treatment faster. One of the most developing and important software models for these purposes is neural networks. 

OBJECTIVE: To determine the capabilities of neural networks in vertebrology at the current stage of their development in the field of such a neural network function as classification.

MATERIALS AND METHODS: Using the PRISMA protocol, a search was performed in the Pubmed database for the period from January 2017 to December 31, 2023 using keywords. 

RESULTS: For the systematic review, 34 articles were selected that described such a neural network function as classification. 

DISCUSSION: Based on the analysis of literature sources, conclusions were drawn about the usefulness of using artificial intelligence at the current stage of development in vertebrology in such a function as classification. 

CONCLUSION: The classification function of neural networks for pathological changes in the spine is not so clear-cut. Good results in detecting degenerative changes are primarily limited to central spinal stenosis, while the results for detecting lateral recess and foraminal stenosis are inconclusive. For spinal fractures, GoogleNet has emerged as the clear leader. Two networks follow GoogleNet: a proprietary DCNN (Germann C. et al.) and a combination of a multilayer perceptron and 3D radiomics techniques (Chiari-Correia N. S. et al.). Only one network, ResNet 50, excels in the classification of spinal tumors, while the results of other architectures lag significantly behind and require further refinement.

INTRODUCTION: The nasal cavity is a complex anatomical structure. The nasal septum (NS), consisting of cartilage, bone elements and mucous membrane, divides the cavity into two symmetrical parts, its average thickness is about 2 mm. From 75 to 80% of the world’s population suffer from various forms of deformity of the NS. Surgical interventions on this anatomical structure are one of the most frequently performed otorhinolaryngological operations, while undesirable surgical outcomes vary from 10 to 27%. The most common complications are septal perforation, septal flotation, secondary anterior deformity, and external nasal deformity. 

OBJECTIVE: Improving the diagnosis of pathological conditions of the nasal septum.

MATERIALS AND METHODS: A total of 128 patients (72 women and 56 men aged 18 to 69 years) were subjected to ultrasound of the NS. The control group included 30 subjects without NS pathology. The first group included 52 patients with NS perforation. The second group consisted of 46 patients with NS curvatures. The studies were carried out on expert-level ultrasound devices (i-800, Canon; Resona 7, Mindray) linear sensors with a frequency range of 3 to 20 MHz. Multicomponent (multiparameter) ultrasound included: B-mode, color duplex scanning mode (CDS), ultrasonic shear wave elastography (SWE). In the gray-scale B-mode, the structure, contours, and echogenicity of the NS were studied. The arterial vessels of the NS were studied using the CDS mode, the parameters of blood flow were determined: the maximum linear velocity of blood flow in cm/sec — V_max, the minimum linear velocity of blood flow in cm/sec — V_min, the index of vascular resistance — Ri in units. Dominant arteries (DA) in the vascular plexus of the NS on both sides were determined, the parameters of blood flow in which were maximum in comparison with the rest of the arteries. To determine the elasticity of the NS (in kPa), the SWE mode was used. 

Statistics: analysis was carried out in the SPSS software package version 21.0. The normality of the sample distribution was assessed using the Kolmogorov-Smirnov criterion.

RESULTS: The cartilaginous part of the NS is normally visualized as a homogeneous isoechogenic structure, with clear contours. Perforated openings of the NS, different in size, are visualized as anechoic areas with clear contours. The mean V_max values in DA were 26,000 (14,000–38,000) cm/sec; (p<0.001 on both sides). The median Ri in DA was 0.5650 (0.3500–0.6900) units; (p<0.001 on both sides of the NS). The results of the hemodynamic parameters of the DA of the first group (NS perforation) showed that the blood flow in 4 subjects differed significantly from the parameters of the control group. The parameters of blood flow in the DA of the second group (NS curvature) did not differ from the parameters of the control group. The study of the elasticity of the cartilaginous part of the NS reliably shows an increase in its stiffness with age. The stiffness values increase with perforation of the NS (43.05±3.44 kPa; p<0.001), which is explained by impaired vascularization of the NS in this pathology. 

DISCUSSION: In the grayscale B-mode, it is possible to clearly visualize the cartilaginous part of the NS and determine those ultrasound criteria that are characteristic of the norm and for pathological conditions. Ultrasound allows you to clearly determine the size, contours and localization of the perforated opening. For normal survival rate of the relocated endonasal flap during plastic surgery on NS, the parametrs of the vessels that nourish this flap is important. Parameters of DA allow to predict the survival rate of the relocated endonasal flaps. The study of the elasticity of the cartilaginous part of the NS reliably shows an increase in its stiffness with age. The stiffness values increase with NS perforation (43.05±3.44 kPa; p<0.001), which is explained by impaired vascularization of the NS in this pathology.

CONCLUSION: Multicomponent ultrasound of the NS allows you to reliably obtain results about the state of its cartilaginous region, to identify deformities and defects of the septum, to study the parameters of the vessels involved in the blood supply of the NS, the elasticity of the NS in normal and pathological conditions.

INTRODUCTION: Liver cirrhosis represents the end stage of chronic liver diseases and is associated with the development of portal hypertension, leading to alterations in quantitative magnetic resonance (MR) parameters of the liver and spleen. Noninvasive techniques, including native T1 mapping and extracellular volume fraction (ECV) calculation, are considered promising tools for disease severity stratification; however, their comparative diagnostic performance in classifying patients according to the Child-Pugh grading system remains insufficiently investigated.

OBJECTIVE: To evaluate and compare the diagnostic performance of native T1 mapping and liver and splenic extracellular volume fraction for stratifying liver cirrhosis according to Child-Pugh classes.

MATERIALS AND METHODS: This retrospective study included 50 patients with confirmed liver cirrhosis who underwent multiparametric magnetic resonance imaging (MRI) with native T1 mapping (MOLLI 4(1)3(1)2 and 5(3)3 protocols) and calculation of liver and spleen extracellular volume fraction (ECV). Patients were stratified according to Child-Pugh classes: A (n=31), B (n=13), and C (n=6).

Statistics: Intergroup analysis was performed using the Kruskal-Wallis and Mann-Whitney tests with Benjamini-Hochberg correction (FDR), along with Spearman correlation analysis and ROC analysis with calculation of the area under the curve (AUROC) and pairwise comparison of ROC curves using the DeLong test.

RESULTS: Statistically significant intergroup differences were observed for all quantitative MRI parameters (p≤0.002; FDR <0.05). Liver extracellular volume fraction (ECV) demonstrated the highest discriminative performance (AUROC 1.000 for A vs C; 0.985 and 0.954 for A vs B; 0.986 for B vs C). Native liver T1 mapping showed moderate diagnostic efficiency (AUROC 0.728–0.893). Native spleen T1 mapping yielded lower and more variable AUROC values (0.436–0.857). Spleen ECV was inferior to liver ECV in diagnostic performance (AUROC 0.812–0.971). The strongest correlation with the total Child-Pugh score was observed for liver ECV (r 0.879–0.892; p<0.001).

DISCUSSION: The findings indicate higher specificity of liver ECV compared with integral native T1 mapping parameters in reflecting the functional severity of cirrhosis according to the Child-Pugh classification. Spleen ECV primarily reflects hemodynamic manifestations of portal hypertension and is less closely associated with progression of hepatocellular insufficiency. 

CONCLUSION: Liver ECV is the most accurate and informative quantitative MR parameter for stratifying cirrhosis according to Child-Pugh classes, outperforming native liver T1 mapping, spleen ECV, and spleen T1 mapping in diagnostic value.

INTRODUCTION: The increase in the incidence of benign breast tumors, as well as the improvement and active introduction of new high-tech surgical techniques into medical practice, has led to an increase in the number of resections performed using vacuum aspiration biopsy (VAB) technology. The capabilities of VAB are constantly expanding: large and multiple tumors can now be successfully and safely resected, thanks in part to the improvement of ultrasound (US) methodology at various stages of the procedure, which is an integral part of the procedure.

OBJECTIVE: is to examine the ultrasound semiotics of breast changes at different time intervals after vacuum aspiration resection of benign neoplasms.

MATERIALS AND METHODS: For the period 2017–2024 inclusive in the day hospital of NCC No. 2 of the Russian National Research Center named after Academician B. V. Petrovsky (formerly the Central Design Bureau of the Russian Academy of Sciences) performed ultrasound-controlled VAB in 986 patients. A total of 1,433 neoplasms were removed. The number of simultaneously removed neoplasms in one patient ranged from 1 to 7. The size of the removed formations reached a maximum of 54 mm. In addition to intraoperative ultrasound, the patients underwent dynamic studies after surgery: on the 1st day (all patients), as well as in the long-term period (1 follow-up ultrasound — 273 patients; 2 or more follow-up ultrasounds — 47 patients).

Statistics: data analysis was performed using Excel 2019 (Microsoft, USA) and JMP Pro 17 (SAS, USA) software.

RESULTS: Ultrasound was performed in the early postoperative period in all 986 patients, who had a total of 1433 breast neoplasms removed. The number of hemorrhagic complications, represented by hematomas ranging from 1.5 to 3 cm in size, was 2.63% (26 patients). After the 1st dynamic ultrasound, residual tissue of the removed neoplasm was initially suspected in 83 of the 319 women who attended the examination (83 residual fragments out of 490 removed neoplasms, which accounted for 16.93%). Subsequently, during dynamic ultrasounds, this percentage decreased to 14.28% (70 cases) — in 13 patients, residual tissue was excluded during later examinations. Performing ultrasound scans in patients with suspected residual tissue up to 6 months after surgery allowed for the exclusion of solid tumors in 29% of cases in the second group of patients.

DISCUSSION: The main objective of ultrasound in the early postoperative period was to control hemorrhagic complications, while the differentiation of the possible residual tumor tissue against the background of edema is difficult and should be performed at a later time. A characteristic pattern of changes in the breast tissue during the first months after the intervention is the presence of hypoechoic «immature» scar tissue in the bed, often having a star-shaped appearance and making it difficult to differentiate the possible residual tumor tissue. Over the following months, the tissues in the bed area become more compact in size and contour, their echogenicity increases, and their structure becomes more consistent with connective tissue. By the 6th month, various outcomes of the reparative processes in the surgical area can be observed, with significant variability: from almost intact tissue corresponding to the unchanged gland (which is observed in most cases after VAB), to the formation of scars with different shapes and structures. At this time, it is possible to convincingly differentiate the likely residual tissue of the neoplasm against the background of good visualization. The most difficult in terms of differential diagnosis in ultrasound are structural changes in the tumor bed, which are a hypoechoic formation of an irregular stellate shape, mimicking a malignant neoplasm. 

CONCLUSION: The ultrasound semiotics of structural changes in the mammary glands at various stages of breast-conserving surgery have specific features related both to the intervention technology and to the course of healing of the bed of the removed neoplasm. Knowledge of the variability of the ultrasound picture at different times after performing breast-conserving surgery and performing ultrasound in dynamics helps to avoid diagnostic errors in terms of differentiation of residual tissue or recurrence of the neoplasm.

INTRODUCTION: Breast cancer (BC) is one of the most complex and significant problems in modern clinical oncology. This malignancy demands a multidisciplinary approach to improve survival, in which early detection plays a key role. Currently, mammography remains the only screening modality with relatively high sensitivity, but its specificity is only moderate. It is particularly difficult to differentiate BI-RADS 3 findings, for which the probability of malignancy does not exceed 2%. Asymmetric density represents one such finding, observed in 1–2% of all mammograms. In this context, magnetic resonance imaging (MRI) which does not use ionizing radiation and allows tissue characterization based on both intrinsic MR signal and contrast uptake and wash‑out kinetics — is of particular interest.

OBJECTIVE: To evaluate the diagnostic performance of dynamic contrast‑enhanced breast MRI in differentiating mammographically detected asymmetric densities.

MATERIALS AND METHODS: We included 57 women (mean age 43.13±6.57 years) who had an asymmetric density on mammography. For all women, we obtained the clinical history and performed a physical breast examination. We also reviewed the findings of other breast imaging modalities. Breast MRI was performed using a Siemens Amira 1.5 T scanner (Siemens, Germany). For contrast enhancement, we administered gadobutrol (7.5 mL, 1 mmol; infusion rate 3–5 mL/s). Lesion verification was achieved by histopathological examination or a minimum 3‑year follow-up.

Statistics: normally distributed continuous variables were compared using the Student t-test; non-normally distributed variables were analyzed with the Wilcoxon signed-rank test or the χ² test, as appropriate. Statistical significance was set at р< 0.05. Sensitivity, specificity, and positive predictive value were calculated from 2×2 contingency tables.

RESULTS: True asymmetric densities without a focal lesion comprised physiological asymmetries caused by uneven distribution of glandular or fibrous tissue, as well as asymmetric breast edema. The former was observed in the majority of cases (50.86%). These cases demonstrated typical asymmetric islands of glandular and fibrous tissue, the summation of which could produce the mammographic finding. Asymmetric breast edema could be caused by inflammatory breast cancer or various benign conditions and was found relatively infrequently (3.51% of all cases). Malignant edema was characterized by signs of regional lymph node metastasis or by parenchymal areas with suspicious enhancement kinetics. True asymmetric densities caused by focal lesions were attributable to breast cancer (12.28%) or benign masses (22.81%).

Contrast enhancement in the area of asymmetry was observed in 49.12% of patients. Type I (persistent) enhancement was seen in 50.0% of cases without malignancy, yielding a positive predictive value for benign asymmetry of 100%. Type II (plateau) enhancement was found in 25.0% of cases; its sensitivity and specificity for breast cancer were 60.0% and 82.61%, respectively. Type III (washout) enhancement was observed in 25.0% of patients, with sensitivity and specificity for breast cancer of 40.0% (p<0.001) and 78.26% (р=0.053), respectively.

DISCUSSION: Technical asymmetric densities resulting from differences in exposure, compression, or breast positioning during mammography are usually easy to recognize and require technically adequate images for interpretation. Iatrogenic asymmetries (postsurgical scars) were common (14.04% of our series) but are readily identified on clinical examination.

CONCLUSION: The sensitivity of dynamic contrast-enhanced MRI for detecting invasive breast cancer in areas of mammographic asymmetry was 100%, but its specificity was only moderate (69.57%).

INTRODUCTION: According to the literature, the diagnostic accuracy of mammographic AI services in determining the BIRADS category can vary quite widely. However, there are no studies that evaluate agreement between AI systems and radiologists in determining the BI-RADS category.

OBJECTIVE: Evaluation of the diagnostic accuracy and agreement of three AI systems with each other and with an expert reader in mammographic examinations through BI-RADS.

MATERIALS AND METHODS: A mixed study was performed, which included retrospective diagnostic and analytical components. The analysis included 99 anonymized mammographic studies. The studies were evaluated by an expert reader with the definition of BI-RADS 1–5 categories separately for the right and left breast; the scores obtained were used as a reference standard. The data set was processed by three commercial AI services, which also identified BI-RADS 1–5 categories.

Statistics: Statistical analysis was performed at the level of individual breasts (n=198). ROC AUC, sensitivity, specificity, and accuracy were evaluated with 95% confidence intervals for two binary BI-RADS scales: BI-RADS 1–3 vs. 4–5 and BI-RADS 12 vs. 3–5. Agreement was calculated using the Pearson and Cohen intraclass correlation method for similar scales and the full BI-RADS scale. The McNemar test was used to compare diagnostic parameters, and a bootstrap analysis with 5,000 repetitions was used to assess consistency differences.

RESULTS: Diagnostic accuracy estimates are presented as ranges of values obtained for individual AI services, and consistency estimates include values obtained for individual pairs of AI services or pairs of «AI service + reader». Diagnostic accuracy of AI services on the BI-RADS binary scale No. 1: ROC AUC — 0.644–0.876, accuracy — 0.788–0.909, specificity — 0.816–0.977, sensitivity — 0.333–0.883. According to the BI-RADS No. 2 binary scale: ROC AUC — 0.795–0.915, accuracy — 0.808–0.939, specificity — 0.818–0.961, sensitivity — 0.739–0.870. Agreement between pairs of AI services on the BI-RADS binary scale No. 1 ranged from 0.232 to 0.504, on the BI-RADS binary scale No. 2 — from 0.416 to 0.663, on the full BI-RADS scale — from 0.387 to 0.564. Agreement between AI services and an expert reader on the binary scale BI-RADS No. 1 ranged from 0.288 to 0.641, on the binary scale BI-RADS No. 2 — from 0.518 to 0.832, on the full BI-RADS scale — from 0.570 to 0.701. 

DISCUSSION: The diagnostic accuracy of AI services on the BI-RADS No. 1 binary scale and BI-RADS No. 2 binary scale corresponded to the ranges in similar studies. Compared to the results of our previous study, the agreement on the BI-RADS No. 1 binary scale, BI-RADS No. 2 binary scale, and the full scale was in the vast majority of cases was lower than the agreement between radiologists.

CONCLUSION: In most cases, there were no statistically significant differences between the diagnostic accuracy parameters of the AI services calculated for the BI-RADS binary scale No. 1 and No. 2. There were also no statistically significant differences in the agreement between pairs of AI services and between AI services and an expert doctor, depending on the type of BI-RADS scale. Considering the various BI-RADS scales, the agreement between AI services and an expert reader was in the vast majority of cases lower than the agreement between radiologists that we evaluated in a previous study.

INTRODUCTION: Radiomics provides quantitative image-derived descriptors that may reduce subjectivity in MRI assessment of supraspinatus muscle degeneration. In rotator cuff pathology, the major challenge is reliable stratification of intermediate grades of fatty infiltration and atrophy, where visual grading is prone to inter-reader variability. Proton-density fat-suppressed sequences are routinely acquired in shoulder MRI and may serve as a practical source for radiomics-based modeling. 

OBJECTIVE: To identify the most informative radiomic, predominantly texture-based, features on proton-density fat-suppressed MRI of the supraspinatus muscle and, based on these features, to develop and internally validate a Random Forest machinelearning model for objective multiclass stratification of degenerative changes.

MATERIALS AND METHODS: A retrospective dataset of 41 shoulder MRI examinations acquired on 1.5 T scanners in multiple clinical sites was analyzed. PD-weighted turbo/fast spin-echo fat-suppressed series were selected and processed using a unified pre-processing and standardization workflow. The supraspinatus muscle was manually segmented slice-by-slice to create a three-dimensional region of interest. Radiomic features were extracted using SlicerRadiomics, followed by stepwise dimensionality reduction and a combined feature-selection strategy to form the final predictor set. A Random Forest classifier with class balancing and hyperparameter tuning was used as the main model. Performance was assessed with 5-fold stratified cross-validation using accuracy, macro F1-score, Cohen’s kappa, per-class sensitivity, and one-vs-rest ROC AUC.

Statistics: statistical data processing and the construction of machine learning models were carried out using IBM SPSS Statistics software (IBM Corp., Armonk, USA) and the R statistical computing environment (R Core Team, 2025), as well as using the Python programming language (scikit-learn, pandas, matplotlib, shap libraries).

RESULTS: Expert grading yielded an imbalanced class distribution (grade 0: 11 cases; grade 1: 5; grade 2: 20; grade 3: 5). The final modeling set comprised 43 radiomic predictors. Cross-validated performance of the Random Forest model reached an overall accuracy of 63.4%, macro F1-score of 45.7%, and Cohen’s kappa of 0.42. One-vs-rest ROC analysis showed high AUC values (0.94–1.0), while class-wise sensitivity indicated pronounced heterogeneity, with better recognition of the most prevalent category and reduced performance for intermediate/rare grades. Wavelet-based texture features and intensity-related descriptors contributed most to model decisions.

CONCLUSIONS: The study demonstrates the feasibility of radiomics-assisted multiclass classification of supraspinatus muscle degeneration on PD fat-suppressed MRI in a real-world clinical dataset. Texture features, particularly wavelet-derived metrics, were among the most informative; however, discrimination of adjacent and underrepresented grades remains a limitation and requires further protocol harmonization and larger datasets.

INTRODUCTION: Osteoporosis manifestations in the context of malabsorption syndrome result from impaired intestinal micronutrient absorption, representing a significant challenge in pediatric practice. While various modalities exist, dual-energy X-ray absorptiometry offers distinct advantages over ultrasound densitometry or quantitative computed tomography. Interpreting osteoporosis and osteoporotic fracture risk in children is particularly complex due to the often oligosymptomatic presentation and the limited availability of robust pediatric diagnostic criteria. Low-energy fractures, a major complication, significantly diminish quality of life and contribute to premature disability. Early identification of risk factors, coupled with timely prophylactic and therapeutic interventions, is crucial for improving long-term outcomes in this growing population.

OBJECTIVE: To refine the interpretive algorithm for dual-energy X-ray absorptiometry (DXA) reports in a pediatric cohort. 

MATERIALS AND METHODS: Bone mineral density (BMD) and bone mineral content (BMC) serve as the principal surrogate markers for assessing bone health. Clinical screening for osteoporosis fundamentally relies on quantifying these parameters. For this analysis, we selected DXA scan protocols for total body less head (TBLH) and the lumbar spine (L_II–L_IV). The study cohort comprised 98 pediatric patients with gastroenterological conditions. Indications for DXA evaluation included: chronic oral corticosteroid therapy (>3 months duration, >5 mg/day), delayed puberty, a history of two or more long bone fractures by age 10, prior administration of zoledronic acid, and conditions associated with intestinal malabsorption. Assessment of bone metabolism included the Z‑score and individual quantitative BMD (g/cm²).

RESULTS: When employing a rigorous, standardized acquisition protocol coupled with patient-specific interpretation of ageand sex-appropriate reference data, DXA provides clinicians with enhanced diagnostic capability. This approach facilitates accurate baseline assessment of bone mineral status and enables sensitive monitoring of longitudinal changes, thereby guiding therapeutic management in this vulnerable population.

DISCUSSION: It is important to emphasize that the examination protocol has been methodically validated in children aged 5–17 years. Nevertheless, the procedural specifics and interpretation of results in patients younger than 5 years warrant further investigation and methodological refinement to improve the accuracy of data analysis.

CONCLUSION: Adopting a personalized analytical approach minimizes the risk of overdiagnosis and allows for precise identification of the baseline value for longitudinal monitoring of bone mineral density (BMD) accumulation, including quantitative follow‑up assessments. Standardization of the analytical framework in densitometric studies not only facilitates BMD evaluation but also enables assessment of bone metabolism quality and prevention of potential complications.

Decidualized endometriomas in pregnancy are a rare finding and pose a significant diagnostic challenge as they mimic malignant ovarian neoplasms. We describe a clinical case of a 27-year-old patient at 15 weeks of gestation with a solid-cystic mass of the left ovary detected on ultrasound. MRI of the pelvis with intravenous contrast enhancement with gadobutrol (Gadovist) and DWI was performed for differential diagnosis. MRI revealed a mass consistent with an endometrioma with an intraluminal solid nodule (height <11 mm) that showed moderate heterogeneous contrast enhancement. A critically important feature was the absence of significant diffusion restriction: the ADC value of the node was 1.5–1.8×10^–3 mm²/s. There were no signs of invasive growth, lymphadenopathy, or carcinomatosis.

CONCLUSION: Comprehensive MRI evaluation, including analysis of morphology (nodule height), contrast enhancement kinetics, and especially quantitative ADC values, is a highly informative method for the differential diagnosis of decidualized endometrioma and malignant ovarian tumors in pregnant patients, justifying the choice of conservative tactics and avoiding unjustified surgical intervention.

Hypophosphatasia is a rare metabolic disorder characterized by mutations in the ALPL gene and reduced activity of tissue-nonspecific alkaline phosphatase, leading to impaired mineralization of bone tissue and teeth. Clinical manifestations depend on the age at onset and the severity of the disease. In the severe perinatal and infantile forms, the following features are observed: marked skeletal hypomineralization, chest wall deformities, respiratory insufficiency, pyridoxine-dependent seizures, hypercalcemia, nephrocalcinosis, craniosynostosis, and a high risk of mortality. This article describes the characteristic radiographic features of various forms of the disease and provides a differential diagnosis with rickets. Clinical observations of two patients — one with the perinatal form and one with the childhood form of hypophosphatasia — are presented; both were diagnosed using laboratory, molecular genetic, and radiographic methods. It is noted that accurate interpretation of radiographic signs in different forms of hypophosphatasia can be crucial for timely diagnosis, initiation of therapy, and subsequent monitoring of treatment efficacy.