Can DNA Methylation Profiling Classify Histologic Subtypes and Grades in Soft Tissue Sarcoma?

BACKGROUND: A clear classification of the subtype and grade of soft tissue sarcoma is important for predicting prognosis and establishing treatment strategies. However, the rarity and heterogeneity of these tumors often make diagnosis difficult. In addition, it remains challenging to predict the response to chemotherapy and prognosis. Thus, we need a new method to help diagnose soft tissue sarcomas and determine treatment strategies in conjunction with traditional methods. Genetic alterations can be found in some subtypes of soft tissue sarcoma, but many other types show dysregulated gene expression attributed to epigenetic changes, such as DNA methylation status. However, research on DNA methylation profiles in soft tissue sarcoma is still insufficient to provide information to assist in diagnosis and therapeutic decisions. QUESTIONS/PURPOSES: (1) Do DNA methylation profiles differ between normal tissue and soft tissue sarcoma? (2) Do DNA methylation profiles vary between different histologic subtypes of soft tissue sarcoma? (3) Do DNA methylation profiles differ based on tumor grade? METHODS: Between January 2019 and December 2022, we treated 85 patients for soft tissue sarcomas. We considered patients whose specimens were approved for pilot research by the Human Biobank of St. Vincent's Hospital, The Catholic University of Korea, as potentially eligible. Based on this, 41% (35 patients) were eligible; 1% (one patient) was excluded because of gender mismatch between clinical and genetic data after controlling for data quality. Finally, 39 specimens (34 soft tissue sarcomas and five normal samples) were included from 34 patients who had clinical data. All tissue samples were collected intraoperatively. The five normal tissue samples were from muscle tissues. There were 20 female patients and 14 male patients, with a median age of 58 years (range 19 to 82 years). Genomic DNA was extracted from frozen tissue, and DNA methylation profiles were obtained. Genomic annotation of DNA methylation sites and hierarchical cluster analysis were performed to interpret results from DNA methylation profiling. A t-test was used to analyze different methylation probes. Benjamini-Hochberg-adjusted p value calculations were used to account for bias resulting from evaluating thousands of methylation sites. RESULTS: The most common histologic subtypes were liposarcoma (n = 10) and leiomyosarcoma (n = 9). The tumor grade was Fédération Nationale des Centres de Lutte Contre Le Cancer Grades 1, 2, and 3 in 3, 15, and 16 patients, respectively. DNA methylation profiling demonstrated differences between soft tissue sarcoma and normal tissue as 21,188 cytosine-phosphate-guanine sites. Despite the small number of samples, 72 of these sites showed an adjusted p value of < 0.000001, suggesting a low probability of statistical errors. Among the 72 sites, 70 exhibited a hypermethylation pattern in soft tissue sarcoma, with only two sites showing a hypomethylation pattern. Thirty of 34 soft tissue sarcomas were distinguished from normal samples using hierarchical cluster analysis. There was a different methylation pattern between leiomyosarcoma and liposarcoma at 7445 sites. Using the data, hierarchical clustering analysis showed that liposarcoma was distinguished from leiomyosarcoma. When we used the same approach and included other subtypes with three or more samples, only leiomyosarcoma and myxofibrosarcoma were separated from the other subtypes, while liposarcoma and alveolar soft-part sarcoma were mixed with the others. When comparing DNA methylation profiles between low-grade (Grade 1) and high-grade (Grades 2 and 3) soft tissue sarcomas, a difference in methylation pattern was observed at 144 cytosine-phosphate-guanine sites. Among these, 132 cytosine-phosphate-guanine sites exhibited hypermethylation in the high-grade group compared with the low-grade group. Hierarchical clustering analysis showed a division into two groups, with most high-grade sarcomas (28 of 31) separated from the low-grade group and few (3 out of 31) clustered together with the low-grade group. However, three high-grade soft tissue sarcomas were grouped with the Grade 1 cluster, and all of these sarcomas were Grade 2. When comparing Grades 1 and 2 to Grade 3, Grade 3 tumors were separated from Grades 1 and 2. CONCLUSION: We observed a different DNA methylation pattern between soft tissue sarcomas and normal tissues. Liposarcoma was distinguished from leiomyosarcoma using methylation profiling. High-grade soft tissue sarcoma samples showed a hypermethylation pattern compared with low-grade ones. Our findings indicate the need for research using methylation profiling to better understand the diverse biological characteristics of soft tissue sarcoma. Such research should include studies with sufficient samples and a variety of subtypes, as well as analyses of the expression and function of related genes. Additionally, efforts to link this research with clinical data related to treatment and prognosis are necessary. LEVEL OF EVIDENCE: Level III, diagnostic study.

Feasibility of a Novel In-situ Local Tumor Ablation and Recycling Machine Based on Radiofrequency Dielectric Heating: In-depth Review on Research Background and Preliminary Report of an Experimental Study.

Background: In bone sarcomas, chemotherapy has improved the prognosis with advances in diagnostic and surgical technologies, which has led to attempts to save limbs. As early detection and multidisciplinary treatment have improved the survival rate, curative surgery is considered for selected patients with metastatic bone carcinomas. Limb salvage procedures may vary in relation to the reconstruction method, which is accompanied by different complications. To overcome them, we devised a novel concept, in-situ local tumor ablation and recycling machine based on radiofrequency (RF)-induced heating and intended experiments to demonstrate its feasibility. Methods: The fresh femurs of 6-month-old pigs were used after removing the epiphyses; the distal parts were placed in a heating chamber. Fiber-optic temperature sensors were inserted in the metaphysis, meta-diaphysis, and diaphysis. Temperatures were measured six times each during heating at 27.12 MHz at various powers. Additionally, the compressive and bending stiffnesses were measured six times each for the unprocessed, RF-treated, and pasteurized bones, and the results were compared. Results: Under 200 W power output, the temperatures at all measurement sites reached 70 ℃ or higher in 6 minutes, and the temperatures were maintained. The median compressive stiffness of RF-heated bones was 79.2% higher than that of pasteurized bones, but the difference was statistically insignificant. The median bending stiffness of RF-heated bones was approximately 66.3% of that of unprocessed bones, which was 20% higher than that of pasteurized bones. Conclusions: The feasibility to rapidly attain and maintain temperatures for tumor ablation is shown, which favorably preserves bone stiffness through the in-situ local tumor ablation and recycling based on RF heating. The problem of nonuniform temperature distribution might be solved by an optimal design determined from simulation research and additional experiments.

Current Treatment Concepts for Extra-Abdominal Desmoid-Type Fibromatosis: A Narrative Review.

Extra-abdominal desmoid-type fibromatosis (EADTF) is a rare neoplastic condition of monoclonal fibroblastic proliferation characterized by local aggressiveness with a distinct tendency to recur. Although EADTF is a benign disease entity, these tumors have a tendency to infiltrate surrounding normal tissues, making it difficult to completely eliminate them without adjacent healthy tissue injury. Surgical excision of these locally aggressive tumors without clear resection margins often leads to local recurrence. The aim of this thorough review was to assess the current treatment concepts for these rare tumors. A comprehensive search of articles published in the Cochrane Library, MEDLINE (PubMed), and EMBASE databases between January 2008 and February 2023 was conducted. Surgical intervention is no longer the first-line approach for most cases; instead, strategies like active surveillance or systemic therapies are used as initial treatment options. With the exception of EADTFs situated near vital structures, a minimum of 6-12 months of active surveillance is currently advocated for, during which some disease progression may be considered acceptable. Non-surgical interventions such as radiation or cryoablation may be employed in certain patients to achieve local control. The currently preferred systemic treatment options include tyrosine kinase inhibitors, low-dose chemotherapy, and gamma-secretase inhibitors, while hormone therapy is not advised. Nonsteroidal anti-inflammatory drugs are utilized primarily for pain management.

Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.

Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application of the DeepLab v3+ -based deep learning model for the automatic segmentation of fragments of the fractured tibia and fibula from CT images and the results of the evaluation of the performance of the automatic segmentation. The deep learning model, which was trained using over 11 million images, showed good performance with a global accuracy of 98.92%, a weighted intersection over the union of 0.9841, and a mean boundary F1 score of 0.8921. Moreover, deep learning performed 5-8 times faster than the experts' recognition performed manually, which is comparatively inefficient, with almost the same significance. This study will play an important role in preoperative surgical planning for trauma surgery with convenience and speed.

Diagnostic conundrums of schwannomas: two cases highlighting morphological extremes and diagnostic challenges in biopsy specimens of soft tissue tumors.

Schwannomas are benign, slow-growing peripheral nerve sheath tumors commonly occurring in the head, neck, and flexor regions of the extremities. Although most schwannomas are easily diagnosable, their variable morphology can occasionally create difficulty in diagnosis. Reporting pathologists should be aware that schwannomas can exhibit a broad spectrum of morphological patterns. Clinical and radiological examinations can show correlation and should be performed, in conjunction with ancillary tests, when appropriate. Furthermore, deferring a definitive diagnosis until excision may be necessary for small biopsy specimens and frozen sections. This report underscores these challenges through examination of two unique schwannoma cases, one predominantly cellular and the other myxoid, both of which posed significant challenges in histological interpretation.

Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.

BACKGROUND: Improvement in survival in patients with advanced cancer is accompanied by an increased probability of bone metastasis and related pathologic fractures (especially in the proximal femur). The few systems proposed and used to diagnose impending fractures owing to metastasis and to ultimately prevent future fractures have practical limitations; thus, novel screening tools are essential. A CT scan of the abdomen and pelvis is a standard modality for staging and follow-up in patients with cancer, and radiologic assessments of the proximal femur are possible with CT-based digitally reconstructed radiographs. Deep-learning models, such as convolutional neural networks (CNNs), may be able to predict pathologic fractures from digitally reconstructed radiographs, but to our knowledge, they have not been tested for this application. QUESTIONS/PURPOSES: (1) How accurate is a CNN model for predicting a pathologic fracture in a proximal femur with metastasis using digitally reconstructed radiographs of the abdomen and pelvis CT images in patients with advanced cancer? (2) Do CNN models perform better than clinicians with varying backgrounds and experience levels in predicting a pathologic fracture on abdomen and pelvis CT images without any knowledge of the patients' histories, except for metastasis in the proximal femur? METHODS: A total of 392 patients received radiation treatment of the proximal femur at three hospitals from January 2011 to December 2021. The patients had 2945 CT scans of the abdomen and pelvis for systemic evaluation and follow-up in relation to their primary cancer. In 33% of the CT scans (974), it was impossible to identify whether a pathologic fracture developed within 3 months after each CT image was acquired, and these were excluded. Finally, 1971 cases with a mean age of 59 ± 12 years were included in this study. Pathologic fractures developed within 3 months after CT in 3% (60 of 1971) of cases. A total of 47% (936 of 1971) were women. Sixty cases had an established pathologic fracture within 3 months after each CT scan, and another group of 1911 cases had no established pathologic fracture within 3 months after CT scan. The mean age of the cases in the former and latter groups was 64 ± 11 years and 59 ± 12 years, respectively, and 32% (19 of 60) and 53% (1016 of 1911) of cases, respectively, were female. Digitally reconstructed radiographs were generated with perspective projections of three-dimensional CT volumes onto two-dimensional planes. Then, 1557 images from one hospital were used for a training set. To verify that the deep-learning models could consistently operate even in hospitals with a different medical environment, 414 images from other hospitals were used for external validation. The number of images in the groups with and without a pathologic fracture within 3 months after each CT scan increased from 1911 to 22,932 and from 60 to 720, respectively, using data augmentation methods that are known to be an effective way to boost the performance of deep-learning models. Three CNNs (VGG16, ResNet50, and DenseNet121) were fine-tuned using digitally reconstructed radiographs. For performance measures, the area under the receiver operating characteristic curve, accuracy, sensitivity, specificity, precision, and F1 score were determined. The area under the receiver operating characteristic curve was used to evaluate three CNN models mainly, and the optimal accuracy, sensitivity, and specificity were calculated using the Youden J statistic. Accuracy refers to the proportion of fractures in the groups with and without a pathologic fracture within 3 months after each CT scan that were accurately predicted by the CNN model. Sensitivity and specificity represent the proportion of accurately predicted fractures among those with and without a pathologic fracture within 3 months after each CT scan, respectively. Precision is a measure of how few false-positives the model produces. The F1 score is a harmonic mean of sensitivity and precision, which have a tradeoff relationship. Gradient-weighted class activation mapping images were created to check whether the CNN model correctly focused on potential pathologic fracture regions. The CNN model with the best performance was compared with the performance of clinicians. RESULTS: DenseNet121 showed the best performance in identifying pathologic fractures; the area under the receiver operating characteristic curve for DenseNet121 was larger than those for VGG16 (0.77 ± 0.07 [95% CI 0.75 to 0.79] versus 0.71 ± 0.08 [95% CI 0.69 to 0.73]; p = 0.001) and ResNet50 (0.77 ± 0.07 [95% CI 0.75 to 0.79] versus 0.72 ± 0.09 [95% CI 0.69 to 0.74]; p = 0.001). Specifically, DenseNet121 scored the highest in sensitivity (0.22 ± 0.07 [95% CI 0.20 to 0.24]), precision (0.72 ± 0.19 [95% CI 0.67 to 0.77]), and F1 score (0.34 ± 0.10 [95% CI 0.31 to 0.37]), and it focused accurately on the region with the expected pathologic fracture. Further, DenseNet121 was less likely than clinicians to mispredict cases in which there was no pathologic fracture than cases in which there was a fracture; the performance of DenseNet121 was better than clinician performance in terms of specificity (0.98 ± 0.01 [95% CI 0.98 to 0.99] versus 0.86 ± 0.09 [95% CI 0.81 to 0.91]; p = 0.01), precision (0.72 ± 0.19 [95% CI 0.67 to 0.77] versus 0.11 ± 0.10 [95% CI 0.05 to 0.17]; p = 0.0001), and F1 score (0.34 ± 0.10 [95% CI 0.31 to 0.37] versus 0.17 ± 0.15 [95% CI 0.08 to 0.26]; p = 0.0001). CONCLUSION: CNN models may be able to accurately predict impending pathologic fractures from digitally reconstructed radiographs of the abdomen and pelvis CT images that clinicians may not anticipate; this can assist medical, radiation, and orthopaedic oncologists clinically. To achieve better performance, ensemble-learning models using knowledge of the patients' histories should be developed and validated. The code for our model is publicly available online at https://github.com/taehoonko/CNN_path_fx_prediction . LEVEL OF EVIDENCE: Level III, diagnostic study.

Mesencephalic astrocyte-derived neurotrophic factor promotes axonal regeneration and the motor function recovery after sciatic nerve injury.

Peripheral nerve injuries have common clinical problems that are often accompanied by sensory and motor dysfunction and failure of axonal regeneration. Although various therapeutic approaches have been attempted, full functional recovery and axonal regeneration are rarely achieved in patients. In this study, we investigated the effects of recombinant adeno-associated virus (AAV) of mesencephalic astrocyte-derived neurotrophic factor (AAV-MANF) or placental growth factor (AAV-PlGF) transduced into mesenchymal stem cells (hMSC-MANF and hMSC-PlGF), which were then transplanted using human decellularized nerves (HDN) into sciatic nerve injury model. Our results showed that both AAV-MANF and AAV-PlGF were expressed in MSCs transplanted into the injury site. Behavioral measurements performed 2, 4, 6, 8, and 12 weeks after injury indicated that MANF facilitated the rapid and improved recovery of sensory and motor functions than PlGF. In addition, immunohistochemical analysis was used to quantitatively analyze the myelination of neurofilaments, Schwann cells, and regrowth axons. Both hMSC-MANF and hMSC-PlGF increased axon numbers and immunoreactive areas of axons and Schwann cells compared with the hMSC-GFP group. However, hMSC-MANF significantly improved the thickness of axons and Schwann cells compared with hMSC-PlGF. G-ratio analysis also showed a marked increase in axon myelination in axons thicker than 2.0 µm treated with MANF than that treated with PlGF. Our study suggests that transplantation of hMSC transduced with AAV-MANF has a potential to provide a novel and efficient strategy for promoting functional recovery and axonal regeneration in peripheral nerve injury.

Diagnosis of Local Recurrence of Malignant Soft Tissue Tumors after Reconstructive Surgery on MRI.

PURPOSE: Magnetic resonance imaging (MRI) is useful in the diagnosis of local recurrence, but few studies have explored recurrence in MRI in patients after reconstructive surgery. The purpose of this study was to analyze MRI findings of locoregional recurrence following reconstructive surgery after malignant soft tissue tumor resection. METHOD: Fifty-three postoperative MRIs from 37 patients who underwent reconstructive surgery after malignant soft tissue tumor resection were retrospectively reviewed. A total of 76 enhancing lesions, including 40 locoregional recurrences and 36 postoperative changes, were analyzed regarding morphology (location on the transplanted tissue, border, and shape) and the signals on T1- and T2-weighted imaging (T1WI, T2WI), fat-suppressed (FS) T2WI, and contrast-enhanced FS T1WI. Diffusion-weighted imaging with an apparent diffusion coefficient was assessed. A chi-squared test and Fisher's exact test were used for statistical analysis. RESULTS: The most common site of recurrent tumors and postoperative changes was the peripheral margin on transplanted tissue (63% and 61%, respectively p = 0.907). Recurrent tumors commonly appeared with well-defined borders (75%) as well as nodular appearance (98%), hyperintensity on T2WI (85%) and FS-T2WI (95%), isointensity on T1WI (65%), impeded water diffusion (55%), and intense (50%) or moderate (45%) enhancement. Postoperative changes showed ill-defined borders (75%), nodular appearance (56%), facilitated water diffusion (69%), and moderate (86%) enhancement, which were significantly different from those of recurrent tumors (p ≤ 0.020). CONCLUSIONS: Common and partitioning MRI features of locoregional recurrence were well-defined borders, nodular shape, impeded water diffusion, and intense enhancement. Peripheral margins on transplanted tissue were common sites in both recurrent tumors and postoperative changes.

Structural analysis of customized 3D printed plate for pelvic bone by comparison with conventional plate based on bending process.

Pelvic bone fracture is highly complex, and its anatomical reduction is difficult. Therefore, patient-specific customized plates have been developed using three-dimensional (3D) printing technology and are being increasingly used. In this study, the reduction status in five representative pelvic fracture models was compared between two groups: the 3D printing plate (3DP) group using a patient-specific 3D printed plate after virtual reduction and the conventional plate (CP) group using a conventional plate by manual bending. The 3DP and CP groups included 10 and 5 cases, respectively. The fractured models were reduced virtually and their non-locking metal plates were customized using 3D printing. The process of contouring the conventional plates to fit the contact surface of the bone with the bending tool was conducted by an experienced pelvic bone trauma surgeon. The reduction and fixation achieved using the two different plate groups was compared, and the significance of differences in the results was analyzed using paired t-tests, after verifying the normality of data distribution. The vertex distances between the surface of the bone and the contact surface of the plate were significantly lower in the 3DP group than in the CP group (0.407 ± 0.342 and 2.195 ± 1.643, respectively, P = 0.008). Length and angular variations, which are measurements of the reduction state, were also lower in the 3DP group than in the CP group (length variation: 3.211 ± 2.497 and 5.493 ± 3.609, respectively, P = 0.051; angular variation: 2.958 ± 1.977 and 4.352 ± 1.947, respectively, P = 0.037). The customized 3D printed plate in the virtual reduction model provided a highly accurate reduction of pelvic bone fractures, suggesting that the customized 3D printed plate may help ensure easy and accurate reduction.

Ensemble learning-based radiomics with multi-sequence magnetic resonance imaging for benign and malignant soft tissue tumor differentiation.

Many previous studies focused on differentiating between benign and malignant soft tissue tumors using radiomics model based on various magnetic resonance imaging (MRI) sequences, but it is still unclear how to set up the input radiomic features from multiple MRI sequences. Here, we evaluated two types of radiomics models generated using different feature incorporation strategies. In order to differentiate between benign and malignant soft tissue tumors (STTs), we compared the diagnostic performance of an ensemble of random forest (R) models with single-sequence MRI inputs to R models with pooled multi-sequence MRI inputs. One-hundred twenty-five STT patients with preoperative MRI were retrospectively included and consisted of training (n = 100) and test (n = 25) sets. MRI included T1-weighted (T1-WI), T2-weighted (T2-WI), contrast-enhanced (CE)-T1-WI, diffusion-weighted images (DWIs, b = 800 sec/mm2) and apparent diffusion coefficient (ADC) maps. After tumor segmentation on each sequence, 100 original radiomic features were extracted from each sequence image and divided into three-feature sets: T features from T1- and T2-WI, CE features from CE-T1-WI, and D features from DWI and ADC maps. Four radiomics models were built using Lasso and R with four combinations of three-feature sets as inputs: T features (R-T), T+CE features (R-C), T+D features (R-D), and T+CE+D features (R-A) (Type-1 model). An ensemble model was built by soft voting of five, single-sequence-based R models (Type-2 model). AUC, sensitivity, specificity, and accuracy of each model was calculated with five-fold cross validation. In Type-1 model, AUC, sensitivity, specificity, and accuracy were 0.752, 71.8%, 61.1%, and 67.2% in R-T; 0.756, 76.1%, 70.4%, and 73.6% in R-C; 0.750, 77.5%, 63.0%, and 71.2% in R-D; and 0.749, 74.6%, 61.1%, and 68.8% R-A models, respectively. AUC, sensitivity, specificity, and accuracy of Type-2 model were 0.774, 76.1%, 68.5%, and 72.8%. In conclusion, an ensemble method is beneficial to incorporate features from multi-sequence MRI and showed diagnostic robustness for differentiating malignant STTs.

Minimally Invasive Carpal Tunnel Release Using a Hook Knife through a Small Transverse Carpal Incision: Technique and Outcome.

Background: Compared to the classic open technique, limited exposure techniques have the advantages of less scar pain, more grip and pinch strength, and earlier return to daily life. We evaluated the effectiveness and safety of our novel method of minimally invasive carpal tunnel release using a hook knife through a small transverse carpal incision. Methods: This study included 111 carpal tunnel decompressions in 78 patients who underwent carpal tunnel release from January 2017 to December 2018. We performed carpal tunnel release using a hook knife through a small transverse incision just proximal to the wrist crease under local infiltration of lidocaine with tourniquet inflation in the upper arm. All patients were tolerable during the procedure and discharged following the procedure on the same day. Results: At an average of 29.4 months of follow-up (range, 12-51 months), all but one patient (99%) revealed complete or near complete symptomatic recovery. The average of the symptom severity score on the Boston questionnaire was 1.31 ± 0.30 and the average of the functional status score was 1.19 ± 0.26. The final mean Quick Disabilities of the Arm, Shoulder, and Hand questionnaire (QuickDASH) score was 8.66 (range, 2-39). There was no superficial palmar arch injury or nerve injury of the palmar cutaneous branch, recurrent motor branch, or median nerve itself as a complication of the procedure. No patient showed any wound infection or wound dehiscence. Conclusions: Our carpal tunnel release using a hook knife through a small transverse carpal incision performed by an experienced surgeon is a safe and reliable method that is expected to have the benefits of simplicity and minimal invasiveness.

Simple curettage and allogeneic cancellous bone chip impaction grafting in solitary enchondroma of the short tubular bones of the hand.

Enchondroma is the most common bone tumor in the hand. While standard surgical procedure is intra-lesional excision and bone grafting, there is a dispute between allogeneic bone, autogenous bone, and synthetic bone substitute grafting. Diverse adjuvant treatments have been introduced to reduce recurrence, but results are mixed with controversies. Meanwhile, whether existing descriptive classification could predict treatment outcome remains unclear. Thus, we reviewed patients with solitary enchondroma of the hand who underwent simple curettage followed by allogeneic cancellous bone chip impaction grafting. Eighty-eight patients with more than 5 years of follow-up were enrolled. Demographic data, local recurrence, and complications were reviewed. Duration of consolidation and the difference according to Takigawa classification were assessed. Range of motion (ROM), and functional scores were also evaluated. There were 51 women and 37 men, with a mean age of 37.9 years. Mean follow-up was 10.2 years. Recurrence occurred only in one patient. There was no complication. Mean postoperative total active motions of fingers and thumb were 239° and 132.9°. Mean modified Disabilities of the Arm, Shoulder, Hand score, and Musculoskeletal Tumor Society Score were 1.63, and 99.2 at the last follow-up. Consolidation, ROM, and functional scores according to Takigawa classification showed no significant differences. This study suggests that simple curettage with impaction grafting of allogeneic cancellous bone chip is a feasible method for treating solitary enchondromas involving short tubular bone of the hand with good long-term outcomes. Postoperative recurrence and complication rates were very low. Radiographic and clinical results were good regardless of the previous radiological classification.

Diagnosis of Marginal Infiltration in Soft Tissue Sarcoma by Radiomics Approach Using T2-Weighted Dixon Sequence.

BACKGROUND: Determination of preoperative soft tissue sarcoma (STS) margin is crucial for patient prognosis. PURPOSE: To evaluate diagnostic performance of radiomics model using T2-weighted Dixon sequence for infiltration degree of STS margin. STUDY TYPE: Retrospective. POPULATION: Seventy-two STS patients consisted of training (n = 58) and test (n = 14) sets. FIELD STRENGTH/SEQUENCE: A 3.0 T; T2-weighted Dixon images. ASSESSMENT: Pathologic result of marginal infiltration in STS (circumscribed margin; n = 27, group 1, focally infiltrative margin; n = 31, group 2-A, diffusely infiltrative margin; n = 14, group 2-B) was the reference standard. Radiomic volume and shape (VS) and other (T2) features were extracted from entire tumor volume and margin, respectively. Twelve radiomics models were generated using four combinations of classifier algorithms (R, SR, LR, LSR) and three different inputs (VS, T2, VS + T2 [VST2] features) to differentiate the three groups. Three radiologists (reader 1, 2, 3) analyzed the marginal infiltration with 6-scale confidence score. STATISTICAL TESTS: Area under the receiver operating characteristic curve (AUC) and concordance rate. RESULTS: Averaged AUCs of R, SR, LR, LSR models were 0.438, 0.466, 0.438, 0.466 using VS features, 0.596, 0.584, 0.814, 0.815 using T2 features, and 0.581, 0.587, 0.821, 0.821 using VST2 features, respectively. The LR and LSR models constructed with T2 or VST2 features showed higher AUC and concordance rate compared to radiologists' analysis (AUC; 0.730, 0.675, 0.706, concordance rate; 0.46, 0.43, 0.47 in reader 1, 2, 3). DATA CONCLUSION: Radiomics model constructed with features from tumor margin on T2-weighted Dixon sequence is a promising method for differentiating infiltration degree of STS margin. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Deep Learning Model Based on You Only Look Once Algorithm for Detection and Visualization of Fracture Areas in Three-Dimensional Skeletal Images.

Utilizing "You only look once" (YOLO) v4 AI offers valuable support in fracture detection and diagnostic decision-making. The purpose of this study was to help doctors to detect and diagnose fractures more accurately and intuitively, with fewer errors. The data accepted into the backbone are diversified through CSPDarkNet-53. Feature maps are extracted using Spatial Pyramid Pooling and a Path Aggregation Network in the neck part. The head part aggregates and generates the final output. All bounding boxes by the YOLO v4 are mapped onto the 3D reconstructed bone images after being resized to match the same region as shown in the 2D CT images. The YOLO v4-based AI model was evaluated through precision-recall (PR) curves and the intersection over union (IoU). Our proposed system facilitated an intuitive display of the fractured area through a distinctive red mask overlaid on the 3D reconstructed bone images. The high average precision values (>0.60) were reported as 0.71 and 0.81 from the PR curves of the tibia and elbow, respectively. The IoU values were calculated as 0.6327 (tibia) and 0.6638 (elbow). When utilized by orthopedic surgeons in real clinical scenarios, this AI-powered 3D diagnosis support system could enable a quick and accurate trauma diagnosis.

[Tumor Margin Infiltration in Soft Tissue Sarcomas: Prediction Using 3T MRI Texture Analysis]. / 연조직 ìœ¡ì¢ ì˜ ì¢ ì–‘ 가장자리 침윤: 3T ìžê¸°ê³µëª ì˜ìƒ í ìŠ¤ì²˜ 분석을 통한 예측.

Purpose: To determine the value of 3 Tesla (T) MRI texture analysis for predicting tumor margin infiltration in soft tissue sarcomas. Materials and Methods: Thirty-one patients who underwent 3T MRI and had a pathologically confirmed diagnosis of soft tissue sarcoma were included in this study. Margin infiltration on pathology was used as the gold standard. Texture analysis of soft tissue sarcomas was performed on axial T1-weighted images (WI) and T2WI, fat-suppressed contrast-enhanced (CE) T1WI, diffusion-weighted images (DWI) with b-value of 800 s/mm2, and apparent diffusion coefficient (ADC) was mapped. Quantitative parameters were compared between sarcomas with infiltrative margins and those with circumscribed margins. Results: Among the 31 patients with soft tissue sarcomas, 23 showed tumor margin infiltration on pathology. There were significant differences in kurtosis with the spatial scaling factor (SSF) of 0 and 6 on T1WI, kurtosis (SSF, 0) on CE-T1WI, skewness (SSF, 0) on DWI, and skewness (SSF, 2, 4) on ADC between sarcomas with infiltrative margins and those with circumscribed margins (p ≤ 0.046). The area under the receiver operating characteristic curve based on MR texture features for identification of infiltrative tumor margins was 0.951 (p < 0.001). Conclusion: MR texture analysis is reliable and accurate for the prediction of infiltrative margins of soft tissue sarcomas.

Intra and extra pelvic multidisciplinary surgical approach of retroperitoneal sarcoma: Case series report.

BACKGROUND: Retroperitoneal sarcoma (RPS) is a rare malignancy arising from mesenchymal cells that most commonly presents as an abdominal mass and is associated with poor prognosis. Although several studies have assessed the survival benefits of wide excision, few have reported detailed methods for achieving wide excision in patients with RPS. AIM: To describe our experience with multidisciplinary surgical resection of RPS using intra- and extra-pelvic approaches. METHODS: Multidisciplinary surgery is an anatomical approach that combines intra- and extra-peritoneal access within the same surgery to achieve complete RPS removal. This retrospective review of the records of patients who underwent multidisciplinary surgery for RPS analyzed surgical and survival outcomes. RESULTS: Eight patients underwent 10 intra- and extra-pelvic surgical resections, and their median mass size was 12.75 cm (range, 6-45.5 cm). Using an intrapelvic approach, laparoscopy-assisted surgery was performed in four cases and laparotomy surgery in six. Using an extrapelvic approach, ilioinguinal and posterior approaches were used in four cases each, and the prone position and midline skin incision were shared in one. All patients' RPS masses were removed completely, and four achieved R0 resection through intra- and extra-pelvic surgery. The median estimated blood loss was 2000 mL (range, 300-20000 mL) and the median hospitalization was 12.6 d (range, 9-69 d). Reoperation was needed in two patients (one for wound necrosis and the other for bowel perforation and wound necrosis). The median overall survival rate and median progression-free survival were 64.6 and 13.7 mo, respectively. CONCLUSION: RPS is therapeutically challenging because of its location and high risk of recurrence. Therefore, intra- and extra-pelvic surgical approaches can improve the macroscopic security of the surgical margin.

Quantitative Assessment of the Restoration of Original Anatomy after 3D Virtual Reduction of Long Bone Fractures.

Background: The purpose of this study was to demonstrate the usefulness of 3D image-based virtual reduction by validating the evaluation criteria according to guidelines suggested by the AO Surgery Reference. Methods: For this experiment, 19 intact radial ORTHObones (ORTHObones radius, 3B Scientific, Germany, Hamburg) without any fractures were prepared. All ORTHObones with six cortical marking holes (three points on the distal part and three points on the proximal part) were scanned using a CT scanner twice (before/after intentional fracture of the ORTHObone). After the virtual reduction of all 19 ORTHObones, accuracy evaluations using the four criteria (length variation, apposition variation, alignment variation, Rotation Variation) suggested in the AO Surgery Reference were performed. Results: The mean (M) length variation was 0.42 mm, with 0.01 mm standard deviation (SD). The M apposition variation was 0.48 mm, with 0.40 mm SD. The M AP angulation variation (for alignment variation) was 3.24°, with 2.95° SD. The M lateral angulation variation (for alignment variation) was 0.09°, with 0.13° SD. The M angle of axial rotation was 1.27° with SD: 1.19°. Conclusions: The method of accuracy evaluation used in this study can be helpful in establishing a reliable plan.

Secondary Malignancy in Giant Cell Tumor: A Single-Center Study.

Giant cell tumor of bone (GCTB) undergoes a sarcomatous transformation. Secondary malignancy in giant cell tumor (MGCT) is associated with radiotherapy and has a dismal prognosis. We reviewed medical records to investigate the clinicopathological characteristics and prognosis of MGCT patients. The enrollment criterion was high-grade spindle-cell sarcoma, which developed at the site of prior GCTB treatment. Twelve patients were analyzed: six females and six males. The median age was 42.5 years. Benign recurrence occurred in five GCTB patients not treated with radiotherapy. No pulmonary implants were observed. The median latency to the malignant transformation was 63 months. Nine patients were AJCC stage IIB, and three were stage IVA. The median follow-up period after malignant transformation was 62.5 months. Five patients developed local recurrence, and six had distant metastasis. Five-year overall recurrence and metastasis-free survival rates were 61.9%, 66.7%, and 58.3%, respectively. Initial metastasis was a predictive factor for overall survival. Benign local recurrence of GCTB was also a negative factor for metastasis-free survival of MGCT patients. Differences in overall survival according to benign recurrence also showed a tendency toward significance. In our series, secondary MGCT did not occur after radiotherapy. The prognosis was better than previous findings. Benign recurrence of GCTB could reflect the prognosis of MGCT.

Sarcomas in Teachers Using Three-Dimensional Printers: A Report of Three Patients and Literature Review.

Background: While low-cost, small-scale, desktop three-dimensional (3D) printers are gaining popularity in the education sector, some studies have reported harmful emissions of particles and volatile organic compounds during the fused deposition modeling (FDM) process, posing a potential health risk. Sarcomas are rare tumors, constituting a group of diverse rare malignant tumors. While some genetic and environmental factors contribute to the development of sarcomas, most cases are idiopathic and sporadic. Methods: We secured the medical records and statements about work environment from teachers diagnosed with sarcomas after frequent use of 3D printers in high schools, reviewed the cases, and described them in narrative format. Furthermore, popularization of FDM 3D printers, worrisome emissions released during the printing process, and related precautions and countermeasures were discussed through literature review. Results: Exceptionally, the cases of sarcomas, such as Ewing's sarcoma, malignant peripheral nerve sheath tumor, and well-differentiated liposarcoma, arose in a common specific condition. All the teachers regularly operated 3D printers in poorly ventilated spaces for at least 2 years. They had no past or family history of relevant diseases. Conclusions: We first reported three cases of sarcoma in teachers who used 3D printers in poorly ventilated conditions. Although a relationship between the use of 3D printers and the development of sarcomas has not been determined yet, it is important to come up with measures to protect teachers and students using 3D printers from the potential hazard.