Indications for nuclear medicine imaging in prostate cancer.

Nuclear medicine imaging for prostate cancer has advanced significantly over the past decade. A survey is presented in this review. PSMA-PET/CT is a new highly accurate method that has been introduced, but bone scans and bone-PET continue to be widely applied. PSMA-PET/CT still lacks sufficient patient outcome data to be recommended for treatment allocation when used for primary staging. However, the literature and clinical guidelines support its use at the stage of biochemical recurrence. In Denmark, the use of nuclear medicine examinations for prostate cancer aligns with clinical guideline recommendations.

Rib myelolipoma: a case report.

BACKGROUND: Myelolipoma is an uncommon benign tumor composed of mature adipose tissue and hematopoietic elements. These tumors generally affect the adrenal glands, with anomalous presentations being rare and with few cases described in the literature. Most myelolipomas are asymptomatic and discovered incidentally, either through imaging tests or at autopsies. However, depending on the location and size of the lesion, myelolipomas can cause symptoms of mass effect. This article aims to report a very rare presentation of a symptomatic primary myelolipoma affecting the ribs. CASE PRESENTATION: A 21-year-old white female patient presented with a complaint of burning chest pain over 3 months, with gradual worsening in intensity, accompanied by a progressively growing bulge in the right thoracic wall. The patient underwent thoracotomy of the fifth and sixth ribs with complete excision of the lesion with a safety margin. Thoracic wall reconstruction was performed using a polypropylene mesh. The patient had a good postoperative course and was discharged on postoperative day 3. Histopathological examination revealed a histological image consistent with myelolipoma. CONCLUSIONS: This report underscores the importance of considering a myelolipoma diagnosis for tumor masses in the ribs.

CT radiomics-based machine learning model for differentiating between enchondroma and low-grade chondrosarcoma.

It may be difficult to distinguish between enchondroma and low-grade malignant cartilage tumors (grade 1) radiologically. This study aimed to construct machine learning models using 3D computed tomography (CT)-based radiomics analysis to differentiate low-grade chondrosarcoma from enchondroma. A total of 30 patients with enchondroma and 26 with chondrosarcoma were included in this retrospective study. Tumor volume segmentation was manually performed by 2 musculoskeletal radiologists. In total, 107 radiomic features were obtained for each patient. The intraclass correlation coefficient was used to assess interobserver reliability and estimate the absolute agreement between the 2 radiologists. Algorithm-based information gain was used as a feature reduction method, and the 5 most important features were detected. For classification, 7 machine learning models were utilized. Classification was carried out using either all features or 5 features. There was good to excellent agreement between the 2 radiologists for the 107 features of each patient. Therefore, a dataset containing 107 features was used for machine learning classification. When assessed based on area under curve (AUC) values, classification using all features revealed that naive Bayes was the best model (AUC = 0.950), while classification using 5 features revealed that random forest was the best model for differentiating chondrosarcoma from enchondroma (AUC = 0.967). In conclusion, machine learning models using CT-based radiomics analysis can be used to differentiate between low-grade chondrosarcoma and enchondroma.

Solitary Osseous Metastasis of Hepatocellular Carcinoma on SPECT/CT.

Hepatocellular carcinoma (HCC), sixth most common cancer world-over, commonly metastasizes to lung, lymph nodes and adrenal glands. Incidence of osseous metastases in HCC has been reported to be 3-20 % which occurs predominantly in the axial skeleton. It only rarely occurs in the appendicular skeleton and that too as the solitary focus of metastatic deposit.3,4 We present a case of HCC with solitary osseous metastases to the proximal tibia.

Quantitative analysis of standardized uptake values (SUV) of metastatic bone lesions in scintigraphy with [99mTc]Tc-EDDA/HYNIC-Tyr3-octreotide in patients with neuroendocrine tumours.

BACKGROUND: Neuroendocrine tumours (NETs) are a group of cancers that can produce hormones and other metabolically active compounds. The majority of NETs have specific tissue characteristics, such as the expression of somatostatin receptors (SSTR). Metabolic testing with [99mTc]Tc-EDDA/HYNIC-Tyr3-octreotide ([99mTc]Tc-EDDA/HYNIC-TOC) can be used in patients with NETs to visualize the presence of receptors in different locations of pathological lesions, including the skeletal system. The study aimed to calculate the body weight maximum standardized uptake value (SUVbwmax) of pathological bone lesions and healthy bone tissues, estimate the size of lesions, and identify a relationship between the SUVbwmax of the bone tissues, age and body mass of the study participants. MATERIAL AND METHODS: The somatostatin receptor scintigraphies (SRS) with [99mTc]Tc-EDDA/HYNIC-TOC were carried out at the Department of Nuclear Medicine, University Clinical Hospital No. 1, Pomeranian Medical University (PMU) in Szczecin from 2019 to 2022. Whole body and single photon emission computed tomography/computed tomography (SPECT/CT) scans were performed four hours after the injection of 700-800 MBq of [99mTc]Tc-EDDA/HYNIC-TOC in 344 patients with neuroendocrine tumours of various primary lesion locations. In 19 patients, who showed foci of increased radiopharmaceutical accumulation in bone location, the SUVbwmax was measured. The SUVbwmax of pathological bone lesions and healthy tissues were determined on SPECT/CT cross-sectional images using Xeleris 4 software. RESULTS: The total number of foci with increased SSTR expression in bone regions seen on scintigraphic images was 89. Among them, 32 bone lesions were visible on the corresponding CT scans. The mean SUVbwmax of these lesions was 31.39 [standard deviation (SD) 34.31]. For the other 57 lesions that were not visible on corresponding CT scans, the mean SUVbwmax was 19.12 (SD 24.24). The smallest bone lesion detected on the scintigram and visible on the corresponding CT location was 5 mm × 5 mm, measured in cross-section, and was located in the Th8 vertebral body; the largest, measuring 20 mm × 22 mm, was detected in the L3 vertebral body. The SUVbwmax of these lesions was 24.70 and 142.40, respectively. CONCLUSIONS: Bone lesions seen on SPECT/CT in [99mTc]Tc-EDDA/HYNIC-TOC scintigraphy can be quantitatively analysed using the SUV index. Even a very small pathological bone lesion can be detected on [99mTc]Tc-EDDA/HYNIC-TOC scintigraphy. It was shown that in cases where bone lesions were visible on CT scans, the SUVbwmax of bone tumour lesions was higher than when lesions were not visible on CT. Body mass does not affect the SUVbwmax of bone lesions. SUVbwmax of healthy bone tissue decreased with age.

Intra-abdominal telangiectatic osteosarcoma: a case report.

BACKGROUND: Telangiectatic osteosarcoma is rare and it rarely affects flat bones, especially the bones of the pelvis. It is uncommon for telangiectatic osteosarcoma to be considered as a differential diagnosis when assessing a large intrabdominal mass. CASE REPORT: We present our case of a 33-year-old African female who presented with a sizeable telangiectatic osteosarcoma of the left iliac bone. She reported a 3-year duration of a painless, slow-growing mass arising from the left flank. At examination, a large bony hard mass extending from the left ilium to the umbilicus was noted, almost mimicking an intra-abdominal pregnancy. All laboratory tests were within normal limits and an unconventional surgical approach was used for a one-stage excision of the tumor without complications. The definitive histopathological diagnosis postexcision was that of a telangiectatic osteosarcoma only on the second review of the histological specimen. CONCLUSIONS: Pelvic telangiectatic osteosarcoma is rare, and the ilium is the commonly affected pelvic bone. These tumors can be sizeable at presentation with intra-abdominal or pelvic extension with a high chance of misdiagnosis. Fortunately surrounding soft tissue involvement seems to be a rare and late finding when present.

Inter-laboratory reproduction and sensitivity study of a finite element model to quantify human femur failure load: Case of metastases.

INTRODUCTION: Metastases increase the risk of fracture when affecting the femur. Consequently, clinicians need to know if the patient's femur can withstand the stress of daily activities. The current tools used in clinics are not sufficiently precise. A new method, the CT-scan-based finite element analysis, gives good predictive results. However, none of the existing models were tested for reproducibility. This is a critical issue to address in order to apply the technique on a large cohort around the world to help evaluate bone metastatic fracture risk in patients. The aim of this study is then to evaluate 1) the reproducibility 2) the transposition of the reproduced model to another dataset and 3) the global sensitivity of one of the most promising models of the literature (original model). METHODS: The model was reproduced based on the paper describing it and discussion with authors to avoid reproduction errors. The reproducibility was evaluated by comparing the results given in the original model by the original first team (Leuven, Belgium) and the reproduced model made by another team (Lyon, France) on the same dataset of CT-scans of ex vivo femurs. The transposition of the model was evaluated by comparing the results of the reproduced model on two different datasets. The global sensitivity analysis was done by using the Morris method and evaluates the influence of the density calibration coefficient, the segmentation, the orientations and the length of the femur. RESULTS: The original and reproduced models are highly correlated (r2 = 0.95), even though the reproduced model gives systematically higher failure loads. When using the reproduced model on another dataset, predictions are less accurate (r2 with the experimental failure load decreases, errors increase). The global sensitivity analysis showed high influence of the density calibration coefficient (mean variation of failure load of 84 %) and non-negligible influence of the segmentation, orientation and length of the femur (mean variation of failure load between 7 and 10 %). CONCLUSION: This study showed that, although being validated, the reproduced model underperformed when using another dataset. The difference in performance depending on the dataset is commonly the cause of overfitting when creating the model. However, the dataset used in the original paper (Sas et al., 2020a) and the Leuven's dataset gave similar performance, which indicates a lesser probability for the overfitting cause. Also, the model is highly sensitive to density parameters and automation of measurement may minimize the uncertainty on failure load. An uncertainty propagation analysis would give the actual precision of such model and improve our understanding of its behavior and is part of future work.

Bone metastasis prediction in non-small-cell lung cancer: primary CT-based radiomics signature and clinical feature.

BACKGROUND: Radiomics provided opportunities to quantify the tumor phenotype non-invasively. This study extracted contrast-enhanced computed tomography (CECT) radiomic signatures and evaluated clinical features of bone metastasis in non-small-cell lung cancer (NSCLC). With the combination of the revealed radiomics and clinical features, the predictive modeling on bone metastasis in NSCLC was established. METHODS: A total of 318 patients with NSCLC at the Tianjin Medical University Cancer Institute & Hospital was enrolled between January 2009 and December 2019, which included a feature-learning cohort (n = 223) and a validation cohort (n = 95). We trained a radiomics model in 318 CECT images from feature-learning cohort to extract the radiomics features of bone metastasis in NSCLC. The Kruskal-Wallis and the least absolute shrinkage and selection operator regression (LASSO) were used to select bone metastasis-related features and construct the CT radiomics score (Rad-score). Multivariate logistic regression was performed with the combination of the Rad-score and clinical data. A predictive nomogram was subsequently developed. RESULTS: Radiomics models using CECT scans were significant on bone metastasis prediction in NSCLC. Model performance was enhanced with each information into the model. The radiomics nomogram achieved an AUC of 0.745 (95% confidence interval [CI]: 0.68,0.80) on predicting bone metastasis in the training set and an AUC of 0.808(95% confidence interval [CI]: 0.71,0.88) in the validation set. CONCLUSION: The revealed invisible image features were of significance on guiding bone metastasis prediction in NSCLC. Based on the combination of the image features and clinical characteristics, the predictive nomogram was established. Such nomogram can be used for the auxiliary screening of bone metastasis in NSCLC.

Novel MRI scoring system to assess osseous malignancy in soft tissue sarcoma patients following radiotherapy.

PURPOSE: Radiation induced changes in bone such as radiation osteitis are commonly identified on magnetic resonance imaging (MRI) in patients who receive radiotherapy for soft tissue sarcoma (STS) management. This study proposes a novel MRI scoring system to assess osseous lesions and predict potential for malignancy based on MRI score in STS patients who received radiotherapy. METHODS: The MRI score consisted of 3 parameters: morphology, signal intensity, and progression. Interobserver reliability between MRI scores were analyzed with Cohen's kappa coefficient. Receiver operating curve (ROC) analysis was performed to determine a predictive MRI score for malignancy. RESULTS: 156 MRI's from 30 STS patients who received radiotherapy were retrospectively reviewed. Two (6.7 %) patients developed regional osseous metastasis identified on MRI. The kappa coefficient of the scoring system was 0.785 demonstrating substantial interobserver agreement (p < 0.001). ROC analysis demonstrated that the optimal cut-off value for malignant lesion on MRI was 5.5 (area under the curve 0.998; p < 0.001). CONCLUSIONS: This novel MRI scoring system recommends lesions with a score of six and above to be biopsied to distinguish if malignancy is present. We believe this scoring system can be utilized by multidisciplinary care teams to guide clinical recommendations for patients with STS and MRI findings concerning for malignancy versus radiation induced changes.

Design and in vitro evaluation of 223Ra/99mTc-loaded spherical nano-hydroxyapatite in bone tumor therapy.

Aim: Nano-hydroxyapatite (nHA) is a good nanocarrier to load 223Ra, but the low specific activity (sp.act.) of 223Ra@nHA limits its application in medicine. Methods: We proposed a method for preparing nHA using PEG as a template, which significantly increases the sp.act of 223Ra@nHA and a new method to loaded 99mTc for in vivo tracking. Results: The nHA synthesized using PEG as a template was associated with higher sp.act for 223Ra in comparison to nHA with identical particle size and without PEG. The nHA load 99mTc-MDP was associated with higher labeling rate and stability in comparison to 99mTc. Conclusion: All these findings suggest that using PEG as a template and 99mTc-MDP could be the most effective of synthetic 223Ra/99mTc@nHA.

[Box: see text].

Machine Learning-Assisted Decision Making in Orthopaedic Oncology.

¼ Artificial intelligence is an umbrella term for computational calculations that are designed to mimic human intelligence and problem-solving capabilities, although in the future, this may become an incomplete definition. Machine learning (ML) encompasses the development of algorithms or predictive models that generate outputs without explicit instructions, assisting in clinical predictions based on large data sets. Deep learning is a subset of ML that utilizes layers of networks that use various inter-relational connections to define and generalize data.¼ ML algorithms can enhance radiomics techniques for improved image evaluation and diagnosis. While ML shows promise with the advent of radiomics, there are still obstacles to overcome.¼ Several calculators leveraging ML algorithms have been developed to predict survival in primary sarcomas and metastatic bone disease utilizing patient-specific data. While these models often report exceptionally accurate performance, it is crucial to evaluate their robustness using standardized guidelines.¼ While increased computing power suggests continuous improvement of ML algorithms, these advancements must be balanced against challenges such as diversifying data, addressing ethical concerns, and enhancing model interpretability.

Successful complete thoracoscopic resection of costal osteochondroma: A case report.

Osteochondroma rarely occurs in the ribs; therefore, the treatment is not standardized. There are few studies of resection via complete thoracoscopic surgery (CTS), although video-assisted thoracoscopic surgery with mini-thoracotomy has been reported. Herein, we report a case of costal osteochondroma managed with CTS. A 23-year-old woman presented to our hospital due to left chest pain. Chest computed tomography revealed a bone-like structure protruding into the thoracic cavity from the left fourth rib. Thus, surgery was performed to obtain a definitive diagnosis and provide appropriate treatment. The tumor was resected from the base at the border of the normal bone via CTS using three 5.5-mm ports. A pathological diagnosis of costal osteochondroma was made. The patient had an uneventful clinical course and did not present with a recurrence 1 year after surgery. Therefore, CTS can be a good approach for cases with slim and stalked costal osteochondroma.

Hyperostosis Frontalis Simulating Metastatic Deposits: Unmasked on SPECT-CT.

Skeletal scintigraphy has a pivotal role in detecting a number of bone pathologies, but it has its own limitations because of 2D image acquisition. Hybrid imaging acts as a savior in these cases where it is difficult to distinguish between benign and malignant lesions just on the basis of planar images. We present one such case of known breast carcinoma with abnormal increased radiotracer uptake in the skull which was difficult to characterize as benign lesion such as hyperostosis frontalis or metastatic osseous lesion. The importance of describing this case is to have a thorough understanding of hyperostosis patterns and to not confuse it with metastatic deposits in patients with known malignancies.

Preoperative prediction of histopathological grading in patients with chondrosarcoma using MRI-based radiomics with semantic features.

BACKGROUND: Distinguishing high-grade from low-grade chondrosarcoma is extremely vital not only for guiding the development of personalized surgical treatment but also for predicting the prognosis of patients. We aimed to establish and validate a magnetic resonance imaging (MRI)-based nomogram for predicting preoperative grading in patients with chondrosarcoma. METHODS: Approximately 114 patients (60 and 54 cases with high-grade and low-grade chondrosarcoma, respectively) were recruited for this retrospective study. All patients were treated via surgery and histopathologically proven, and they were randomly divided into training (n = 80) and validation (n = 34) sets at a ratio of 7:3. Next, radiomics features were extracted from two sequences using the least absolute shrinkage and selection operator (LASSO) algorithms. The rad-scores were calculated and then subjected to logistic regression to develop a radiomics model. A nomogram combining independent predictive semantic features with radiomic by using multivariate logistic regression was established. The performance of each model was assessed by the receiver operating characteristic (ROC) curve analysis and the area under the curve, while clinical efficacy was evaluated via decision curve analysis (DCA). RESULTS: Ultimately, six optimal radiomics signatures were extracted from T1-weighted imaging (T1WI) and T2-weighted imaging with fat suppression (T2WI-FS) sequences to develop the radiomics model. Tumour cartilage abundance, which emerged as an independent predictor, was significantly related to chondrosarcoma grading (p < 0.05). The AUC values of the radiomics model were 0.85 (95% CI, 0.76 to 0.95) in the training sets, and the corresponding AUC values in the validation sets were 0.82 (95% CI, 0.65 to 0.98), which were far superior to the clinical model AUC values of 0.68 (95% CI, 0.58 to 0.79) in the training sets and 0.72 (95% CI, 0.57 to 0.87) in the validation sets. The nomogram demonstrated good performance in the preoperative distinction of chondrosarcoma. The DCA analysis revealed that the nomogram model had a markedly higher clinical usefulness in predicting chondrosarcoma grading preoperatively than either the rad-score or clinical model alone. CONCLUSION: The nomogram based on MRI radiomics combined with optimal independent factors had better performance for the preoperative differentiation between low-grade and high-grade chondrosarcoma and has potential as a noninvasive preoperative tool for personalizing clinical plans.

Intramuscular mesenchymal chondrosarcoma surrounded by a split fat sign mimicking a benign lesion.

Mesenchymal chondrosarcoma (MCS) is an aggressive malignant mesenchymal tumour of uncertain differentiation. This is rare, accounting for 2%-4% of chondrosarcomas. Its peak incidence is in the second and third decades, though it can occur at any age. These tumours show a widespread distribution, mainly in bone, but with approximately 40% affecting somatic soft tissue. We present a case of MCS arising within the soleus muscle. The lesion was surrounded by a split-fat sign/fatty rind which is a typical feature of peripheral nerve sheath tumours or other benign intramuscular tumours. However, percutaneous biopsy showed MCS. We highlight how perilesional fat is not exclusive to benign intramuscular lesions and, although much less common, can be associated with malignant lesions. This is, to the best of our knowledge, the first reported case of MCS presenting with a split-fat sign at MRI.

Present and future of whole-body MRI in metastatic disease and myeloma: how and why you will do it.

Metastatic disease and myeloma present unique diagnostic challenges due to their multifocal nature. Accurate detection and staging are critical for determining appropriate treatment. Bone scintigraphy, skeletal radiographs and CT have long been the mainstay for the assessment of these diseases, but have limitations, including reduced sensitivity and radiation exposure. Whole-body MRI has emerged as a highly sensitive and radiation-free alternative imaging modality. Initially developed for skeletal screening, it has extended tumor screening to all organs, providing morphological and physiological information on tumor tissue. Along with PET/CT, whole-body MRI is now accepted for staging and response assessment in many malignancies. It is the first choice in an ever increasing number of cancers (such as myeloma, lobular breast cancer, advanced prostate cancer, myxoid liposarcoma, bone sarcoma, …). It has also been validated as the method of choice for cancer screening in patients with a predisposition to cancer and for staging cancers observed during pregnancy. The current and future challenges for WB-MRI are its availability facing this number of indications, and its acceptance by patients, radiologists and health authorities. Guidelines have been developed to optimize image acquisition and reading, assessment of lesion response to treatment, and to adapt examination designs to specific cancers. The implementation of 3D acquisition, Dixon method, and deep learning-based image optimization further improve the diagnostic performance of the technique and reduce examination durations. Whole-body MRI screening is feasible in less than 30 min. This article reviews validated indications, recent developments, growing acceptance, and future perspectives of whole-body MRI.

Fat Fraction Extracted from Whole-Body Magnetic Resonance (WB-MR) in Bone Metastatic Prostate Cancer: Intra- and Inter-Reader Agreement of Single-Slice and Volumetric Measurements.

BACKGROUND: This study evaluates the repeatability and reproducibility of fat-fraction percentage (FF%) in whole-body magnetic resonance imaging (WB-MRI) of prostate cancer patients with bone metastatic hormone naive disease. METHODS: Patients were selected from the database of a prospective phase-II trial. The treatment response was assessed using the METastasis Reporting and Data System for Prostate (MET-RADS-P). Two operators identified a Small Active Lesion (SAL, <10 mm) and a Large Active Lesion (LAL, ≥10 mm) per patient, performing manual segmentation of lesion volume and the largest cross-sectional area. Measurements were repeated by one operator after two weeks. Intra- and inter-reader agreements were assessed via Interclass Correlation Coefficient (ICC) on first-order radiomics features. RESULTS: Intra-reader ICC showed high repeatability for both SAL and LAL in a single slice (SS) and volumetric (VS) measurements with values ranging from 0.897 to 0.971. Inter-reader ICC ranged from 0.641 to 0.883, indicating moderate to good reproducibility. Spearman's rho analysis confirmed a strong correlation between SS and VS measurements for SAL (0.817) and a moderate correlation for LAL (0.649). Both intra- and inter-rater agreement exceeded 0.75 for multiple first-order features across lesion sizes. CONCLUSION: This study suggests that FF% measurements are reproducible, particularly for larger lesions in both SS and VS assessments.

Lower extremity deformity and its risk factors in patients with solitary osteochondromas.

BACKGROUND: This study aimed to demonstrate the occurrence of lower extremity deformities and their risk factors in patients with solitary osteochondromas. METHODS: We retrospectively reviewed consecutive patients with solitary osteochondromas around the knee. The laterality (left or right), involved bone (femur or tibia), tumor type (pedunculated or sessile), and direction (medial or lateral) were examined. The whole limb length (WLL), mechanical lateral distal femoral angle (mLDFA), and medial proximal tibial angle (MPTA) were measured using teleroentgenogram. Lower limb deformity was defined as a difference of more than 5° in mLDFA or MPTA in both lower extremities or a difference in WLL of more than 1 cm. Patients were divided into two groups, with deformity and without deformity. RESULTS: Lower extremity deformities were observed in 8 of 83 patients. Significant difference in the type of osteochondroma (p = 0.004) between the groups was observed. Differences in sex, age, laterality, involved bone, direction, and distance from the physis to the osteochondroma between groups were not statistically significant. The sessile type of osteochondroma was a risk factor for lower limb deformity with an odds ratio of 24.0 according to Firth's logistic regression analysis. CONCLUSION: In our cohort with solitary osteochondroma, lower limb deformities were observed in 8 (9.6%) out of the 83 patients and these were significantly associated with sessile-type tumors. Therefore, patients with sessile-type solitary osteochondroma around the knee require careful surveillance of lower limb alignment with whole leg teleroentgenogram.

Conventional vs. endoscopic-assisted curettage of benign bone tumours. An experimental study.

BACKGROUND: This experimental study aimed at directly comparing conventional and endoscopic-assisted curettage towards (1) amount of residual tumour tissue (RTT) and (2) differences between techniques regarding surgical time and surgeons' experience level. METHODS: Three orthopaedic surgeons (trainee, consultant, senior consultant) performed both conventional (4x each) and endoscopic-assisted curettages (4x each) on specifically prepared cortical-soft cancellous femur and tibia sawbone models. "Tumours" consisted of radio-opaque polyurethane-based foam injected into prepared holes. Pre- and postinterventional CT-scans were carried out and RTT assessed on CT-scans. For statistical analyses, percentage of RTT in relation to total lesion's volume was used. T-tests, Wilcoxon rank-sum tests, and Kruskal-Wallis tests were applied to assess differences between surgeons and surgical techniques regarding RTT and timing. RESULTS: Median overall RTT was 1% (IQR 1 - 4%). Endoscopic-assisted curettage was associated with lower amount of RTT (median, 1%, IQR 0 - 5%) compared to conventional curettage (median, 4%, IQR 0 - 15%, p = 0.024). Mean surgical time was prolonged with endoscopic-assisted (9.2 ± 2.9 min) versus conventional curettage (5.9 ± 2.0 min; p = 0.004). No significant difference in RTT amount (p = 0.571) or curetting time (p = 0.251) depending on surgeons' experience level was found. CONCLUSIONS: Endoscopic-assisted curettage appears superior to conventional curettage regarding complete tissue removal, yet at expenses of prolonged curetting time. In clinical practice, this procedure may be reserved for cases at high risk of recurrence (e.g. anatomy, histology).