Accurate tissue delineation is essential in radiotherapy; however, conventional segmentation metrics mainly quantify geometric overlap and lack clinical interpretability. We proposed an automated Python-based evaluation pipeline using a bidirectional local distance-based metric that pairs test and reference contour points after center-of-mass correction and computes a similarity score from averaged Euclidean distances. The framework supports multislice images, multiple masks per slice, and concave mask separation, with open-source code provided. The method was demonstrated on fibroid and prostate MRI datasets, using 233 training cases and 12 test cases. In test examples, overlap scores exceeded 0.90, while Medical Similarity Index scores decreased to approximately 0.40.

Objectives:To identify characteristic vascular features of focal nodular hyperplasia (FNH) on microvascular flow imaging (MVFI) and assess the utility of MVFI in FNH diagnosis. Methods:This retrospective study included B-mode ultrasound (US) and MVFI scans of 41 FNHs, 21 hepatocellular carcinomas (HCCs), 20 metastases (METs), 10 hepatocellular adenomas (HCAs), and eight hemangiomas (HEMs) from 80 patients. Diagnoses were confirmed by contrast-enhanced imaging or histology. Two independent observers evaluated vascular patterns on MVFI. Interobserver agreement was calculated, and logistic regression models using either B-mode or MVFI features were developed to differentiate FNH from other focal liver lesions (FLLs). Results:Interobserver agreement for MVFI patterns was substantial (κ = 0.641, p < 0.001). The spoke-wheel pattern (OR = 51.53 and 35.28) and central artery (OR = 4.96 and 1.95) were strongly associated with FNH. However, the spoke-wheel pattern also appeared in subsets of HCAs (20%-30%), HCCs (14%-19%), and METs (5%-15%). Rim vascularity was common but nonspecific. The MVFI-based model (AUC = 0.891, p < 0.001) outperformed the B-mode model (AUC = 0.814) in distinguishing FNH. For lesions ≥3 cm, MVFI accuracy was even higher (AUC = 0.944, p < 0.001). Conclusion:MVFI enhances the diagnostic confidence of US for FNH, particularly in asymptomatic patients at low risk for malignancy. However, given the potential overlap with certain malignant FLLs, MVFI findings should be interpreted with caution.

Background: we evaluated regression models based on quantitative ultrasound (QUS) parameters and compared them with a vendor-provided method for calculating the ultrasound fat fraction (USFF) in metabolic dysfunction-associated steatotic liver disease (MASLD). Methods: We measured the attenuation coefficient (AC) and the backscatter-distribution coefficient (BSC-D) and determined the USFF during a liver ultrasound and calculated the magnetic resonance imaging proton-density fat fraction (MRI-PDFF) and steatosis grade (S0–S4) in a combined retrospective–prospective cohort. We trained multiple models using single or various QUS parameters as independent variables to forecast MRI-PDFF. Linear and nonlinear models were trained during five-time repeated three-fold cross-validation in a retrospectively collected dataset of 60 MASLD cases. We calculated the models’ Pearson correlation (r) and the intraclass correlation coefficient (ICC) in a prospectively collected test set of 57 MASLD cases. Results: The linear multivariable model (r = 0.602, ICC = 0.529) and USFF (r = 0.576, ICC = 0.54) were more reliable in S0- and S1-grade steatosis than the nonlinear multivariable model (r = 0.492, ICC = 0.461). In S2 and S3 grades, the nonlinear multivariable (r = 0.377, ICC = 0.32) and AC-only (r = 0.375, ICC = 0.313) models’ approximated correlation and agreement surpassed that of the multivariable linear model (r = 0.394, ICC = 0.265). We searched a QUS parameter grid to find the optimal thresholds (AC ≥ 0.84 dB/cm/MHz, BSC-D ≥ 105), above which switching from a linear (r = 0.752, ICC = 0.715) to a nonlinear multivariable (r = 0.719, ICC = 0.641) model could improve the overall fit (r = 0.775, ICC = 0.718). Conclusions: The USFF and linear multivariable models are robust in diagnosing low-grade steatosis. Switching to a nonlinear model could enhance the fit to MRI-PDFF in advanced steatosis.

INTRODUCTION:Mechanical thrombectomy is an established therapeutic method for acute ischemic stroke and first pass effect (FPE) constitutes the ultimate goal of endovascular treatment. Aim. To investigate the relationship between the clot composition in acute ischemic stroke (AIS) in patients with large-vessel occlusion and first pass effect of mechanical thrombectomy (MT). MATERIAL AND METHODS:Clots from AIS patients who underwent MT were examined histologically and the area occupied by red blood cells (RBCs), white blood cells (WBCs) and fibrin was quantified. The clinical outcome of the procedure was evaluated using modified Rankin Scale (mRS). RESULTS:Seventy consecutive patients were included in this prospective study. Demographics, occlusion site, procedural details and clinical outcomes were evaluated. Full recanalization was observed in 54 patients (77.1%) and from this group FPE was achieved in 28 patients. Statistical analysis did not show significant correlation between clot composition and FPE but low RBC clot area was close to significance (P=0.08). CONCLUSIONS:Despite the lack of statistically significant correlation between clot composition and first pass effect in patients with acute ischemic stroke, we observed that red blood cell rich clots were associated with increased number of thrombectomy passes which supports the notion that clot histology influences recanalization outcomes and shows the need for further studies on this topic.

PURPOSE:Digital variance angiography (DVA), a recently developed image processing technology, provides a higher contrast-to-noise ratio (CNR) and better image quality during lower limb interventions than digital subtraction angiography (DSA). Our aim was to investigate whether the quality reserve of DVA can also be observed in uterine fibroid embolization (UFE). METHODS:In this retrospective observational study, the CNR and image quality of DSA and DVA images from 56 patients (mean ± standard deviation age: 44.2 ± 5.3 years) who underwent UFE at our institution were assessed. For the visual evaluation of the same image pairs, the visibility of large vessels, small vessels, tissue blush, and background noise was compared by three experienced readers using a four-grade Likert scale. Data were analyzed using the Wilcoxon signed-rank test or the one-sample Wilcoxon test. RESULTS:DVA provided significantly higher CNR than DSA (the median CNRDVA/CNRDSA was 1.96). In the visual comparison of DVA and DSA images, Likert scores did not significantly differ from zero (equal quality level) in any evaluated categories. The median (interquartile range) values were 0.00 (1.00) for large vessels, -0.33 (1.33) for small vessels, 0.00 (0.67) for tissue blush, and 0.00 (0.75) for background noise. CONCLUSION:Although the visual image quality of DSA and DVA was identical, DVA provided a twofold CNR in UFE, indicating a significant quality advantage for this technology. CLINICAL SIGNIFICANCE:The observed quality reserve may allow for dose management (reduction of applied radiation dose and/or contrast media), enhancing the safety of UFE for both patients and personnel.

Background: In the field of radiology and radiotherapy, accurate delineation of tissues and organs plays a crucial role in both diagnostics and therapeutics. While the gold standard remains expert-driven manual segmentation, many automatic segmentation methods are emerging. The evaluation of these methods primarily relies on traditional metrics that only incorporate geometrical properties and fail to adapt to various applications. Aims: This study aims to develop and implement a clinically relevant segmentation metric that can be adapted for use in various medical imaging applications. Methods: Bidirectional local distance was defined, and the points of the test contour were paired with points of the reference contour. After correcting for the distance between the test and reference center of mass, Euclidean distance was calculated between the paired points, and a score was given to each test point. The overall medical similarity index was calculated as the average score across all the test points. For demonstration, we used myoma and prostate datasets; nnUNet neural networks were trained for segmentation. Results: An easy-to-use, sustainable image processing pipeline was created using Python. The code is available in a public GitHub repository along with Google Colaboratory notebooks. The algorithm can handle multislice images with multiple masks per slice. Mask splitting algorithm is also provided that can separate the concave masks. We demonstrate the adaptability with prostate segmentation evaluation. Conclusions: A novel segmentation evaluation metric was implemented, and an open-access image processing pipeline was also provided, which can be easily used for automatic measurement of clinical relevance of medical image segmentation.}

The ellipsoidal formula is the most common method used to determine the volume of fibroids on MR images. Labor-intensive manual segmentation provides the opportunity to measure the volume of a given lesion on a voxel basis. The aim of this study is to compare the volume of the uterine fibroid calculated using voxel-based segmentation and the ellipsoid formula. In this study, pretreatment MRI scans of patients who underwent uterine artery embolization due to symptomatic fibroids were retrospectively collected between 2016 and 2022. The volume data of the largest fibroids was determined by segmentation (group S) as the reference standard. In addition, the largest diameters of the fibroids in three planes (D1/D2/D3) were also measured and the volumes were also estimated by using the ellipsoidal formula (D1*D2*D3*0.5233) (group E). The interobserver reproducibility of the diameter measurements was tested. The volume values (median, IQR) were compared; in addition, the differences between the segmented and ellipsoidal volumes were recorded. Statistical analysis was performed using the Kruskal-Wallis test, Wilcoxon's two-sided signed rank test, intraclass correlation (ICC) analysis, and Bland-Altman plots. Pretreatment MRI scans of 113 patients were identified. Fibroids where the interobserver difference of diameter-based ellipsoidal volumes reached 30% were excluded resulting in 99 patients in the final dataset. The volumes of group S and group E showed no significant differences with 134.1 (257.3) cm3 and 133.5 (269.1) cm3, respectively, with an average difference of 3.47 cm3 (0.25%; p = 0.377). The agreement between the two methods was excellent (ICC = 0.979), without difference across fibroid locations. In 46 cases (46.5%), group S values were larger, and in 53 fibroids (53.5%), group E volume values were larger. However, volume difference was outside the ± 20% range in 21 cases (21.2%) and outside the ± 30% range in 10 cases (10.1%); the largest difference was approximately 56.5% (156.5 cm3). The ellipsoid formula-based and the voxel-based volume calculation showed no significant difference for the group as a whole. However, there was a difference of > 20% in 21.2% of cases and > 30% in 10.1% of cases. In the era of personalized medicine, it is not only the average difference between the two methods that need to be considered but also cases where there is a 20% or 30% difference in results should be highlighted, as these may change the treatment plan in individual cases. This methodology should also be tested for other tumor-type volume calculations.

Abstract Background Uterine artery embolisation is a recommended method of adenomyosis treatment with good clinical results. Changes in uterine volume and maximal junctional zone thickness (JZmax) after embolisation are thoroughly analyzed in the literature. In contrast changes in other suggested morphological diagnostic markers of adenomyosis (junctional zone differential / JZdiff—and junctional zone ratio / JZratio) are rarely evaluated. This single-centre retrospective study aimed to analyse the changes in morphological parameters used for the MR imaging diagnosis of adenomyosis (including JZdiff and JZratio) after UAE. Clinical effectiveness and safety were also analysed. Materials and methods Patients who underwent UAE for pure adenomyosis from Jan 2008 to Dec 2021 were evaluated. Adenomyosis was diagnosed based on JZmax, JZdiff, and JZratio measured on MR imaging. To assess clinical efficacy, the numerical-analog-quality-of-life (QoL) score was routinely obtained from patients at our centre. MRI morphological data were analysed. Statistical analysis was conducted using Wilcoxon signed-rank test, uni- and multivariate regression models, Pearson product-moment correlation, and Kruskal–Wallis tests. Results From our database of 801 patients who underwent UAE between Jan 2008 to Dec 2021, preprocedural MR images were available in 577 cases and, 15 patients had pure adenomyosis (15/577, 2.6%). Uterine volume, JZmax, and JZdiff decreased significantly after UAE; QoL score increased significantly. A significant correlation was found between QoL change vs. JZmax and JZdiff change. Permanent amenorrhoea and elective hysterectomy 5 years after UAE were both 7.1%. Conclusion Change of JZdiff after UAE in adenomyosis is a potential marker of clinical success. UAE is a clinically safe and effective treatment for adenomyosis. Graphical Abstract

The aim of this article is to present our experience with minimally-invasive treatment for nulliparous patients with pelvic venous congestion syndrome (PVCS) with special attention to anatomical considerations, procedural and clinical outcome. In this retrospective, monocentric study, 21 patients with PVCS treated from January 2014 to June 2023 were included. The preprocedural imaging evaluation of PVCS was based on color Doppler ultrasound, contrast-enhanced CT and/or MRI. In all cases insufficient ovarian veins and/or internal iliac branches were occluded with coils and sclerosant. Procedural and clinical outcomes were measured 30 and 90 days after the procedure. Average duration of pelvic pain was 44.8 ± 54.2 months (from 6 to 200) with the mean VAS-recorded pain intensity of 8.5 ± 1.1 (range from 7 to 10 where 0 was “no pain” and 10 “worst pain possible”). Most common symptoms included dysmenorrhea, dyspareunia and dysuria. Complete embolization was observed in in all cases. Targeted vessels included left ovarian vein (13/21, 62

(1) Background: Open-source software tools are available to estimate proton density fat fraction (PDFF). (2) Methods: We compared four algorithms: complex-based with graph cut (GC), magnitude-based (MAG), magnitude-only estimation with Rician noise modeling (MAG-R), and multi-scale quadratic pseudo-Boolean optimization with graph cut (QPBO). The accuracy and reliability of the methods were evaluated in phantoms with known fat/water ratios and a patient cohort with various grades (S0–S3) of steatosis. Image acquisitions were performed at 1.5 Tesla (T). (3) Results: The PDFF estimates showed a nearly perfect correlation (Pearson r = 0.999, p < 0.001) and inter-rater agreement (ICC = from 0.995 to 0.999, p < 0.001) with true fat fractions. The absolute bias was low with all methods (0.001–1%), and an ANCOVA detected no significant difference between the algorithms in vitro. The agreement across the methods was very good in the patient cohort (ICC = 0.891, p < 0.001). However, MAG estimates (−2.30% ± 6.11%, p = 0.005) were lower than MAG-R. The field inhomogeneity artifacts were most frequent in MAG-R (70%) and GC (39%) and absent in QPBO images. (4) Conclusions: The tested algorithms all accurately estimate PDFF in vitro. Meanwhile, QPBO is the least affected by field inhomogeneity artifacts in vivo.

Uterine fibroids are the most common pelvic benign tumours occurring in women of reproductive age. Current treatment options include surgical procedures, pharmacological therapies, and minimally invasive procedures. The most commonly applied and accepted minimally invasive procedure used in the treatment of symptomatic uterine fibroid is uterine artery embolisation (UAE). Uterine artery embolisation is a minimally invasive procedure that can be used either as an auxiliary method or the main treatment method of symptomatic uterine fibroids. We would like to present the application of pre-operative UAE before hysterectomy in anaemic women with giant uterine fibroid (21.9 × 14.9 × 10.4 cm) and HIV-associated nephropathy. Among the possible treatment options for uterine fibroids in cases like the one presented in our manuscript, hysterectomy is the treatment of choice. However, surgical treatment in a patient with severe comorbid conditions and giant uterine fibroid carries serious risk of perioperative complications. Pre-operative UAE decreases such risk by reducing blood loss during hysterectomy and shortening operation/anaesthesia time. Although the benefits of pre-operative UAE before planned myomectomy or hysterectomy in high surgical risk patients with large fibroids has yet to be confirmed in a well-designed clinical trial, this procedure seems to be a promising tool to reduce the risk of perioperative complications in such patients.

We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (UEFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. We measured and retrospectively collected the ultrasound attenuation coefficient (AC), backscatter-distribution coefficient (BSC-D), and liver stiffness (LS) using shear wave elastography (SWE) in 90 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD), and 51 patients with clinically suspected metabolic-associated fatty liver disease (MAFLD). The MRI-PDFF was also measured in all patients within a month of the ultrasound scan. In the linear regression analysis, only AC and BSC-D showed a significant association with MRI-PDFF. Therefore, we developed prediction models using non-linear least squares analysis to estimate MRI-PDFF based on the AC and BSC-D parameters. We fitted the models on the NAFLD dataset and evaluated their performance in three-fold cross-validation repeated five times. We decided to use the model based on both parameters to calculate UEFF. The correlation between UEFF and MRI-PDFF was strong in NAFLD and very strong in MAFLD. According to a receiver operating characteristics (ROC) analysis, UEFF could differentiate between <5% vs. ≥5% and <10% vs. ≥10% MRI-PDFF steatosis with excellent, 0.97 and 0.91 area under the curve (AUC), accuracy in the NAFLD and with AUCs of 0.99 and 0.96 in the MAFLD groups. In conclusion, UEFF calculated from QUS parameters is an accurate method to quantify liver fat fraction and to diagnose ≥5% and ≥10% steatosis in both NAFLD and MAFLD. Therefore, UEFF can be an ideal non-invasive screening tool for patients with NAFLD and MAFLD risk factors.

The staff of the Radiation Protection Service of a European clinical center measured the radiation dose by type-tested thermoluminescent dosemeter systems to which the medical staff was exposed, to assess the effectiveness of current procedures and equipment for optimalisation prompted by the requirements EU Basic Safety Standard 2013. There were three participating sites, the Site 1 was an external hospital, whereas Sites 2 and 3 are part of the same clinical center, who provided data regarding their personnel, from technologists, nurses and medical doctors. In this preliminary study, only a low number of cases were available and used to establish a new, more realistic yearly dose constraint, namely 6 (from two) mSv for whole-body effective dose, 15 (from two) mSv for eye lens dose and 300 (from 50) mSv for extremity dose. Furthermore, the state of safety culture and protection equipment was assessed. Collection of the sufficient amount of data for statistical evaluation is ongoing.

Background and Objectives: This study aims to evaluate artificial intelligence-calculated hepatorenal index (AI-HRI) as a diagnostic method for hepatic steatosis. Materials and Methods: We prospectively enrolled 102 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD). All patients had a quantitative ultrasound (QUS), including AI-HRI, ultrasound attenuation coefficient (AC,) and ultrasound backscatter-distribution coefficient (SC) measurements. The ultrasonographic fatty liver indicator (US-FLI) score was also calculated. The magnetic resonance imaging fat fraction (MRI-PDFF) was the reference to classify patients into four grades of steatosis: none < 5%, mild 5–10%, moderate 10–20%, and severe ≥ 20%. We compared AI-HRI between steatosis grades and calculated Spearman’s correlation (rs) between the methods. We determined the agreement between AI-HRI by two examiners using the intraclass correlation coefficient (ICC) of 68 cases. We performed a receiver operating characteristics (ROC) analysis to estimate the area under the curve (AUC) for AI-HRI. Results: The mean AI-HRI was 2.27 (standard deviation, ±0.96) in the patient cohort. The AI-HRI was significantly different between groups without (1.480 ± 0.607, p < 0.003) and with mild steatosis (2.155 ± 0.776), as well as between mild and moderate steatosis (2.777 ± 0.923, p < 0.018). AI-HRI showed moderate correlation with AC (rs = 0.597), SC (rs = 0.473), US-FLI (rs = 0.5), and MRI-PDFF (rs = 0.528). The agreement in AI-HRI was good between the two examiners (ICC = 0.635, 95% confidence interval (CI) = 0.411–0.774, p < 0.001). The AI-HRI could detect mild steatosis (AUC = 0.758, 95% CI = 0.621–0.894) with fair and moderate/severe steatosis (AUC = 0.803, 95% CI = 0.721–0.885) with good accuracy. However, the performance of AI-HRI was not significantly different (p < 0.578) between the two diagnostic tasks. Conclusions: AI-HRI is an easy-to-use, reproducible, and accurate QUS method for diagnosing mild and moderate hepatic steatosis.

Splenic hamartoma is a rare benign vascular lesion of the spleen. A splenic mass was incidentally detected in an asymptomatic 65-year-old male during an abdominal ultrasound scan. The workup of the splenic lesion included an abdominal CT angiography (CTA), contrast-enhanced ultrasound (CEUS), and microvascular flow imaging Doppler sonography. The CT scan confirmed that the splenic mass had benign characteristics, and its contrast enhancement was similar to the spleen. The CEUS was able to rule out the possibility of hemangioma. Meanwhile, chronic compression of the celiac trunk and the filling of the splenic artery from collaterals were also detected on CTA. The imaging studies suggested a splenic hamartoma, and the diagnosis was confirmed by the result of a fine needle aspiration biopsy.

The area of Artificial Intelligence is developing at a high rate. In the medical field, an extreme amount of data is created every day. As the images and the reports are quantifiable, the field of radiology aspires to deliver better, more efficient clinical care. Artificial intelligence (AI) means the simulation of human intelligence by a system or machine. It has been developed to enable machines to "think" , which means to be able to learn, reason, predict, categorize, and solve problems concerning high amounts of data and make decisions in a more effective manner than before. Different AI methods can help radiologists with pre-screening images and identifying features. In this review, we summarize the basic concepts which are needed to understand AI. As the AI methods are expected to exceed the threshold for clinical usefulness soon, in the near future it will be inevitable to use AI in medicine.

Liver tumors constitute a major part of the global disease burden, often making regular imaging follow-up necessary. Recently, deep learning (DL) has increasingly been applied in this research area. How these methods could facilitate report writing is still a question, which our study aims to address by assessing multiple DL methods using the Medical Open Network for Artificial Intelligence (MONAI) framework, which may provide clinicians with preliminary information about a given liver lesion. For this purpose, we collected 2274 three-dimensional images of lesions, which we cropped from gadoxetate disodium enhanced T1w, native T1w, and T2w magnetic resonance imaging (MRI) scans. After we performed training and validation using 202 and 65 lesions, we selected the best performing model to predict features of lesions from our in-house test dataset containing 112 lesions. The model (EfficientNetB0) predicted 10 features in the test set with an average area under the receiver operating characteristic curve (standard deviation), sensitivity, specificity, negative predictive value, positive predictive value of 0.84 (0.1), 0.78 (0.14), 0.86 (0.08), 0.89 (0.08) and 0.71 (0.17), respectively. These results suggest that AI methods may assist less experienced residents or radiologists in liver MRI reporting of focal liver lesions.

It has been proven in a few early studies that radiomic analysis offers a promising opportunity to detect or differentiate between organ lesions based on their unique texture parameters. Recently, the utilization of CT texture analysis (CTTA) has been receiving significant attention, especially for response evaluation and prognostication of different oncological diagnoses. In this review article, we discuss the unique ability of radiomics and its subfield CTTA to diagnose lesions in the pancreas and kidney. We review studies in which CTTA was used for the classification of histology grades in pancreas and kidney tumors. We also review the role of radiogenomics in the prediction of the molecular and genetic subtypes of pancreatic tumors. Furthermore, we provide a short report on recent advancements of radiomic analysis in predicting prognosis and survival of patients with pancreatic and renal cancers.

OBJECTIVES:To present preliminary results of minimally invasive endovascular embolization as a treatment of symptomatic adenomyosis or adenomyosis with fibroids and to assess the long-term clinical outcome.MATERIAL AND METHODS:Between 2015 and 2020 twelve patients with symptomatic adenomyosis or adenomyosis with fibroids underwent uterine artery embolization (UAE). All patients were evaluated in terms of patient's overall satisfaction, relief of clinical symptoms, reintervention and hysterectomy as well as menopause rates.RESULTS:Mean age on admission was 48 years. Reported symptoms included: dysmenorrhea with the mean VAS score of 7.8, menorrhagia and problems with urination. Successful embolization was achieved in all patients (100%). A reduction in pelvic pain intensity assessed using VAS was observed in 11/12 (92%) of the patients - pain decreased by 6.2 points on average (from 7.8 to 1.6 pts). In one patient (8%) the recurrence of pain was observed. All patients reported decrease of menstrual bleeding and consequently improvement of everyday life quality. Avoidance of hysterectomy was achieved in 83% of the women. Five patients experience absence of menstrual periods for at least 12 months after the embolization resulting in menopause rate of 42%. Ten patients (83%) reported to be very or fairly satisfied with the results and would recommend this treatment to a friend.CONCLUSIONS:Uterine artery embolization might be safe and effective method of treatment for patients with symptomatic adenomyosis with or without fibroids with very high rate of satisfied patients.

INTRODUCTION:Caesarean scar pregnancy (CSP) is a relatively rare yet life-threatening condition in which the embryo is implanted in the scar after caesarean section. Recent studies have reported that uterine artery chemoembolisation (UAC) can be safe and effective method in treating CSP.AIM:To present the clinical outcome of UAC with a mixture of methotrexate and gelatine sponge for the treatment of CSP and analysis of procedural failure.MATERIAL AND METHODS:Forty-one patients diagnosed with CSP were treated with selective endovascular chemoembolisation of uterine arteries. Short- and long-term results, reasons for procedural failure, and clinical outcome were analysed.RESULTS:Primary procedure failed in 7 out of 41 (17%) cases. In 4 cases additional blood supply to the CSP was disclosed; 3 out of 4 from an ovarian artery and one from a superior vesical artery. In other 3 patients, reperfusion of uterine arteries was observed. All these 7 patients underwent successful secondary embolisation. The majority of the followed-up patients reported regular menses after the intervention. Four women suffered from amenorrhoea and 2 from hypomenorrhoea that continued after 90 days. Twelve patients expressed the desire for subsequent pregnancy. From this group, 5 conceived within a year of the procedure. The rest did not achieve a pregnancy.CONCLUSIONS:UAC proved to be a safe and effective method and should be considered as an option for CSP treatment, especially for women hoping to preserve their fertility. However, the presence of collateral blood supply should always be considered.