Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas

BACKGROUND

Volume of interest (VOI) segmentation is a crucial step for Radiomics analyses and radiotherapy (RT) treatment planning. Because it can be time-consuming and subject to inter-observer variability, we developed and tested a Deep Learning-based automatic segmentation (DLBAS) algorithm to reproducibly predict the primary gross tumor as VOI for Radiomics analyses in extremity soft tissue sarcomas (STS).

METHODS

A DLBAS algorithm was trained on a cohort of 157 patients and externally tested on an independent cohort of 87 patients using contrast-enhanced MRI. Manual tumor delineations by a radiation oncologist served as ground truths (GTs). A benchmark study with 20 cases from the test cohort compared the DLBAS predictions against manual VOI segmentations of two residents (ERs) and clinical delineations of two radiation oncologists (ROs). The ROs rated DLBAS predictions regarding their direct applicability.

RESULTS

The DLBAS achieved a median dice similarity coefficient (DSC) of 0.88 against the GTs in the entire test cohort (interquartile range (IQR): 0.11) and a median DSC of 0.89 (IQR 0.07) and 0.82 (IQR 0.10) in comparison to ERs and ROs, respectively. Radiomics feature stability was high with a median intraclass correlation coefficient of 0.97, 0.95 and 0.94 for GTs, ERs, and ROs, respectively. DLBAS predictions were deemed clinically suitable by the two ROs in 35% and 20% of cases, respectively.

CONCLUSION

The results demonstrate that the DLBAS algorithm provides reproducible VOI predictions for radiomics feature extraction. Variability remains regarding direct clinical applicability of predictions for RT treatment planning.

Chondrosarcoma evaluation using hematein-based x-ray staining and high-resolution 3D micro-CT: a feasibility study

BACKGROUND

Chondrosarcomas are rare malignant bone tumors diagnosed by analyzing radiological images and histology of tissue biopsies and evaluating features such as matrix calcification, cortical destruction, trabecular penetration, and tumor cell entrapment.

METHODS

We retrospectively analyzed 16 cartilaginous tumor tissue samples from three patients (51-, 54-, and 70-year-old) diagnosed with a dedifferentiated chondrosarcoma at the femur, a moderately differentiated chondrosarcoma in the pelvis, and a predominantly moderately differentiated chondrosarcoma at the scapula, respectively. We combined a hematein-based x-ray staining with high-resolution three-dimensional (3D) microscopic x-ray computed tomography (micro-CT) for nondestructive 3D tumor assessment and tumor margin evaluation.

RESULTS

We detected trabecular entrapment on 3D micro-CT images and followed bone destruction throughout the volume. In addition to staining cell nuclei, hematein-based staining also improved the visualization of the tumor matrix, allowing for the distinction between the tumor and the bone marrow cavity. The hematein-based staining did not interfere with further conventional histology. There was a 5.97 ± 7.17% difference between the relative tumor area measured using micro-CT and histopathology (p = 0.806) (Pearson correlation coefficient r = 0.92, p = 0.009). Signal intensity in the tumor matrix (4.85 ± 2.94) was significantly higher in the stained samples compared to the unstained counterparts (1.92 ± 0.11, p = 0.002).

CONCLUSIONS

Using nondestructive 3D micro-CT, the simultaneous visualization of radiological and histopathological features is feasible.

RELEVANCE STATEMENT

3D micro-CT data supports modern radiological and histopathological investigations of human bone tumor specimens. It has the potential for being an integrative part of clinical preoperative diagnostics.

KEY POINTS

• Matrix calcifications are a relevant diagnostic feature of bone tumors. • Micro-CT detects all clinically diagnostic relevant features of x-ray-stained chondrosarcoma. • Micro-CT has the potential to be an integrative part of clinical diagnostics.

Proteomic Characterization of Undifferentiated Small Round Cell Sarcomas with EWSR1- and CIC::DUX4-Translocations Reveals Diverging Tumor Biology and Distinct Diagnostic Markers

Undifferentiated small round cell sarcomas of bone and soft tissue (USRS) are a group of tumors with heterogenic genomic alterations sharing similar morphology. In the present study, we performed a comparative large-scale proteomic analysis of USRS (n=42) with diverse genomic translocations including classic Ewing sarcomas with EWSR1::FLI1 fusions (n=24) or EWSR1::ERG - fusions (n=4), sarcomas with an EWSR1 - rearrangement (n=2), CIC::DUX4 fusion (n=8), as well as tumors classified as USRS with no genetic data available (n=4). Proteins extracted from formalin-fixed, paraffin-embedded (FFPE) pretherapeutic biopsies were analyzed qualitatively and quantitatively using shot gun mass spectrometry (MS). More than 8000 protein groups could be quantified using data-independent acquisition. Unsupervised hierarchical cluster analysis based on proteomic data allowed stratification of the 42 cases into distinct groups reflecting the different molecular genotypes. Protein signatures that significantly correlated with the respective genomic translocations were identified and used to generate a heatmap of all 42 sarcomas with assignment of cases with unknown molecular genetic data to either the EWSR1- or CIC-rearranged groups. MS-based prediction of sarcoma subtypes was molecularly confirmed in two cases where next-generation sequencing was technically feasible. MS also detected proteins routinely used in the immunohistochemical approach for the differential diagnosis of USRS. BCL11B highly expressed in Ewing sarcomas and Bach2 as well as ETS-1 highly expressed in CIC::DUX4-associated sarcomas, were among proteins identified by the present proteomic study and were chosen for immunohistochemical confirmation of MS data in our study cohort. Differential expression of these 3 markers in the two genetic groups were further validated in an independent cohort of n= 34 USRS. Finally, our proteomic results point towards diverging signaling pathways in the different USRS subgroups.

What Is the Impact of Multimodal Treatment in Patients with Leiomyosarcoma of Bone? A Multicenter Study of 35 Patients with an Ultra-Rare Tumor Entity

Primary leiomyosarcoma of bone (LMSoB) is extremely rare, comprising only <0.7% of primary malignant bone tumors, and is therefore considered an ultra-rare tumor entity. There is currently no consensus as to whether therapeutic strategies should be based on the biological characteristics of soft tissue leiomyosarcoma or on primary tumor localization in the bone. The use of perioperative chemotherapy and its effectiveness in this rare tumor entity remains unclear. We aimed to evaluate the impact of different treatment approaches in a multicenter setting with a total of 35 patients included. The 5-year overall survival (OS) was 74%. Patients with localized disease undergoing surgery had a significantly higher 5-year OS compared to patients who did not undergo surgical treatment (82% vs. 0%, p = 0.0015). Axial tumor localization was associated with worse event-free survival (EFS) probability (p < 0.001) and OS (p = 0.0082). A high proportion of our patients developed secondary metastases. Furthermore, the perioperative chemotherapy protocols applied to our patients were not associated with an improved EFS or OS. Therefore, the benefit of perioperative chemotherapy in LMSoB needs to be further investigated, and the choice of agents still needs to be clarified.

Diagnostic Delay in Patients with Osteoid Osteoma

PURPOSE

 To assess diagnostic delay in patients with osteoid osteoma and to analyze influencing factors.

MATERIALS AND METHODS

 All patients treated for osteoid osteoma at our tertiary referral center between December 1997 and February 2021 were retrospectively identified (n = 302). The diagnosis was verified by an expert panel of radiologists and orthopedic surgeons. The exclusion criteria were post-interventional recurrence, missing data on symptom onset, and lack of pretherapeutic CT images. Clinical parameters were retrieved from the local clinical information system. CT and MR images were assessed by a senior specialist in musculoskeletal radiology.

RESULTS

 After all exclusions, we studied 162 patients (mean age: 24 ± 11 years, 115 men). The average diagnostic delay was 419 ± 485 days (median: 275 days; range: 21-4503 days). Gender, patient age, presence of nocturnal pain, positive aspirin test, extent of bone sclerosis, and location of the tumor within bone and relative to joints did not influence diagnostic delay (p > 0.05). It was, however, positively correlated with nidus size (r = 0.26; p < 0.001) and was shorter with affection of long tubular bones compared to all other sites (p = 0.04). If osteoid osteoma was included in the initial differential diagnoses, the diagnostic delay was also shorter (p = 0.007).

CONCLUSION

 The diagnostic delay in patients with osteoid osteoma is independent of demographics, clinical parameters, and most imaging parameters. A long average delay of more than one year suggests low awareness of the disease among physicians. Patients with unclear imaging findings should thus be referred to a specialized musculoskeletal center or an expert in the field should be consulted in a timely manner.

KEY POINTS

  · In this retrospective study of 162 patients treated for osteoid osteoma, the median diagnostic delay was 275 days (range: 21-4503 days).. · Gender, age, presence of nocturnal pain, positive aspirin test, extent of bone sclerosis, and location of the tumor did not influence the diagnostic delay (p > 0.05).. · Diagnostic delay was positively correlated with nidus size (r = 0.26; p < 0.001) and was shorter with affection of long tubular bones compared to all other sites (376 ± 485 vs. 560 ± 462 days; p = 0.04)..

Deep Learning-Based Detection of Bone Tumors around the Knee in X-rays of Children

Even though tumors in children are rare, they cause the second most deaths under the age of 18 years. More often than in other age groups, underage patients suffer from malignancies of the bones, and these mostly occur in the area around the knee. One problem in the treatment is the early detection of bone tumors, especially on X-rays. The rarity and non-specific clinical symptoms further prolong the time to diagnosis. Nevertheless, an early diagnosis is crucial and can facilitate the treatment and therefore improve the prognosis of affected children. A new approach to evaluating X-ray images using artificial intelligence may facilitate the detection of suspicious lesions and, hence, accelerate the referral to a specialized center. We implemented a Vision Transformer model for image classification of healthy and pathological X-rays. To tackle the limited amount of data, we used a pretrained model and implemented extensive data augmentation. Discrete parameters were described by incidence and percentage ratio and continuous parameters by median, standard deviation and variance. For the evaluation of the model accuracy, sensitivity and specificity were computed. The two-entity classification of the healthy control group and the pathological group resulted in a cross-validated accuracy of 89.1%, a sensitivity of 82.2% and a specificity of 93.2% for test groups. Grad-CAMs were created to ensure the plausibility of the predictions. The proposed approach, using state-of-the-art deep learning methodology to detect bone tumors on knee X-rays of children has achieved very good results. With further improvement of the algorithm, enlargement of the dataset and removal of potential biases, this could become a useful additional tool, especially to support general practitioners for early, accurate and specific diagnosis of bone lesions in young patients.

Development and Evaluation of MR-Based Radiogenomic Models to Differentiate Atypical Lipomatous Tumors from Lipomas

Background: The aim of this study was to develop and validate radiogenomic models to predict the MDM2 gene amplification status and differentiate between ALTs and lipomas on preoperative MR images. Methods: MR images were obtained in 257 patients diagnosed with ALTs (n = 65) or lipomas (n = 192) using histology and the MDM2 gene analysis as a reference standard. The protocols included T2-, T1-, and fat-suppressed contrast-enhanced T1-weighted sequences. Additionally, 50 patients were obtained from a different hospital for external testing. Radiomic features were selected using mRMR. Using repeated nested cross-validation, the machine-learning models were trained on radiomic features and demographic information. For comparison, the external test set was evaluated by three radiology residents and one attending radiologist. Results: A LASSO classifier trained on radiomic features from all sequences performed best, with an AUC of 0.88, 70% sensitivity, 81% specificity, and 76% accuracy. In comparison, the radiology residents achieved 60–70% accuracy, 55–80% sensitivity, and 63–77% specificity, while the attending radiologist achieved 90% accuracy, 96% sensitivity, and 87% specificity. Conclusion: A radiogenomic model combining features from multiple MR sequences showed the best performance in predicting the MDM2 gene amplification status. The model showed a higher accuracy compared to the radiology residents, though lower compared to the attending radiologist.

Outcome of patients with soft tissue sarcomas of the extremities and trunk treated by (neo)adjuvant intensity modulated radiation therapy with curative intent

BACKGROUND

Soft tissue sarcomas (STS) are a relatively rare group of malignant tumors. Currently, there is very little published clinical data, especially in the context of curative multimodal therapy with image-guided, conformal, intensity-modulated radiotherapy.

METHODS

Patients who received preoperative or postoperative intensity-modulated radiotherapy for STS of the extremities or trunk with curative intent were included in this single centre retrospective analysis. A Kaplan-Meier analysis was performed to evaluate survival endpoints. Multivariable proportional hazard models were used to investigate the association between survival endpoints and tumour-, patient-, and treatment-specific characteristics.

RESULTS

86 patients were included in the analysis. The most common histological subtypes were undifferentiated pleomorphic high-grade sarcoma (UPS) (27) and liposarcoma (22). More than two third of the patients received preoperative radiation therapy (72%). During the follow-up period, 39 patients (45%) suffered from some type of relapse, mainly remote (31%). The two-years overall survival rate was 88%. The median DFS was 48 months and the median DMFS was 51 months. Female gender (HR 0.460 (0.217; 0.973)) and histology of liposarcomas compared to UPS proved to be significantly more favorable in terms of DFS (HR 0.327 (0.126; 0.852)).

CONCLUSION

Conformal, intensity-modulated radiotherapy is an effective treatment modality in the preoperative or postoperative management of STS. Especially for the prevention of distant metastases, the establishment of modern systemic therapies or multimodal therapy approaches is necessary.

Differentiating Enchondromas and Atypical Cartilaginous Tumors in Long Bones with Computed Tomography and Magnetic Resonance Imaging

The differentiation between the atypical cartilaginous tumor (ACT) and the enchondromas is crucial as ACTs require a curettage and clinical as well as imaging follow-ups, whereas in the majority of cases enchondromas require neither a treatment nor follow-ups. Differentiating enchondromas from ACTs radiologically remains challenging. Therefore, this study evaluated imaging criteria in a combination of computed tomography (CT) and magnetic resonance (MR) imaging for the differentiation between enchondromas and ACTs in long bones. A total of 82 patients who presented consecutively at our institution with either an ACT (23, age 52.7 ±18.8 years; 14 women) or an enchondroma (59, age 46.0 ± 11.1 years; 37 women) over a period of 10 years, who had undergone preoperative MR and CT imaging and subsequent biopsy or/and surgical removal, were included in this study. A histopathological diagnosis was available in all cases. Two experienced radiologists evaluated several imaging criteria on CT and MR images. Likelihood of an ACT was significantly increased if either edema within the bone (p = 0.049), within the adjacent soft tissue (p = 0.006) or continuous growth pattern (p = 0.077) were present or if the fat entrapment (p = 0.027) was absent on MR images. Analyzing imaging features on CT, the likelihood of the diagnosis of an ACT was significantly increased if endosteal scalloping >2/3 (p < 0.001), cortical penetration (p < 0.001) and expansion of bone (p = 0.002) were present and if matrix calcifications were observed in less than 1/3 of the tumor (p = 0.013). All other imaging criteria evaluated showed no significant influence on likelihood of ACT or enchondroma (p > 0.05). In conclusion, both CT and MR imaging show suggestive signs which can help to adequately differentiate enchondromas from ACTs in long bones and therefore can improve diagnostics and consequently patient management. Nevertheless, these features are rare and a combination of CT and MR imaging features did not improve the diagnostic performance substantially.

Neoadjuvant Radiation in High-Grade Soft-Tissue Sarcomas: Histopathologic Features and Response Evaluation

In this study, we sought to determine the prognostic value of both the European Organization for Research and Treatment of Cancer-Soft Tissue and Bone Sarcoma Group (EORTC-STBSG) score and the histologic parameters viable tumor, coagulative necrosis, hyalinization/fibrosis, and infarction in patients (n=64) with localized, nonmetastatic high-grade soft-tissue sarcomas after preoperative radiomonotherapy. A standardized macroscopic workup for pretreated surgical specimen including evaluation of a whole section of high-grade soft tissue sarcomas in the largest diameter, was used. Association with overall survival and disease-free survival was assessed. Limb salvage could be accomplished in 98.4% of patients. Overall, 90.6% tumors had negative resection margins. The median postoperative tumor diameter was 9 cm. Undifferentiated pleomorphic sarcoma (42.2%) and myxofibrosarcoma (17.2%) were the most common diagnoses. In all, 9.4% of patients had local recurrence despite clear resection margins, and 50% had distant metastases. Morphologic mapping suggests an overall heterogenous intratumoral response to radiotherapy, with significant differences among histologic subtypes. Complete regression (0% vital tumor cells) was not seen. Categorizing the results according to the proposed EORTC-STBSG 5-tier response score, <1% viable tumor cells were seen in 3.1%, ≥1% to <10% viable tumor cells in 20.4%, ≥10% to <50% viable tumor cells in 35.9% and ≥50% viable tumor cells in 40.6% of cases. Mean values for viable tumor cells were 40% (range: 1% to 100%), coagulative necrosis 5% (0% to 60%), hyalinization/fibrosis 25% (0% to 90%) and infarction 15% (0% to 79%). Hyalinization/fibrosis was a significant independent prognostic factor for overall survival (hazard ratio=4.4; P =0.047), while the other histologic parameters including the EORTC-STBSG score were not prognostic.

Diagnosis of joint invasion in patients with malignant bone tumors: value and reproducibility of direct and indirect signs on MR imaging

OBJECTIVES

To evaluate the performance and reproducibility of MR imaging features in the diagnosis of joint invasion (JI) by malignant bone tumors.

METHODS

MR images of patients with and without JI (n = 24 each), who underwent surgical resection at our institution, were read by three radiologists. Direct (intrasynovial tumor tissue (ITT), intraarticular destruction of cartilage/bone, invasion of capsular/ligamentous insertions) and indirect (tumor size, signal alterations of epiphyseal/transarticular bone (bone marrow replacement/edema-like), synovial contrast enhancement, joint effusion) signs of JI were assessed. Odds ratios, sensitivity, specificity, PPV, NPV, and reproducibilities (Cohen's and Fleiss' κ) were calculated for each feature. Moreover, the diagnostic performance of combinations of direct features was assessed.

RESULTS

Forty-eight patients (28.7 ± 21.4 years, 26 men) were evaluated. All readers reliably assessed the presence of JI (sensitivity = 92-100 %; specificity = 88-100%, respectively). Best predictors for JI were direct visualization of ITT (OR = 186-229, p < 0.001) and destruction of intraarticular bone (69-324, p < 0.001). Direct visualization of ITT was also highly reliable in assessing JI (sensitivity, specificity, PPV, NPV = 92-100 %), with excellent reproducibility (κ = 0.83). Epiphyseal bone marrow replacement and synovial contrast enhancement were the most sensitive indirect signs, but lacked specificity (29-54%). By combining direct signs with high specificity, sensitivity was increased (96 %) and specificity (100 %) was maintained.

CONCLUSION

JI by malignant bone tumors can reliably be assessed on preoperative MR images with high sensitivity, specificity, and reproducibility. Particularly direct visualization of ITT, destruction of intraarticular bone, and a combination of highly specific direct signs were valuable, while indirect signs were less predictive and specific.

KEY POINTS

• Direct visualization of intrasynovial tumor was the single most sensitive and specific (92-100%) MR imaging sign of joint invasion. • Indirect signs of joint invasion, such as joint effusion or synovial enhancement, were less sensitive and specific compared to direct signs. • A combination of the most specific direct signs of joint invasion showed best results with perfect specificity and PPV (both 100%) and excellent sensitivity and NPV (both 96 %).

Development and evaluation of machine learning models based on X-ray radiomics for the classification and differentiation of malignant and benign bone tumors

OBJECTIVES

To develop and validate machine learning models to distinguish between benign and malignant bone lesions and compare the performance to radiologists.

METHODS

In 880 patients (age 33.1 ± 19.4 years, 395 women) diagnosed with malignant (n = 213, 24.2%) or benign (n = 667, 75.8%) primary bone tumors, preoperative radiographs were obtained, and the diagnosis was established using histopathology. Data was split 70%/15%/15% for training, validation, and internal testing. Additionally, 96 patients from another institution were obtained for external testing. Machine learning models were developed and validated using radiomic features and demographic information. The performance of each model was evaluated on the test sets for accuracy, area under the curve (AUC) from receiver operating characteristics, sensitivity, and specificity. For comparison, the external test set was evaluated by two radiology residents and two radiologists who specialized in musculoskeletal tumor imaging.

RESULTS

The best machine learning model was based on an artificial neural network (ANN) combining both radiomic and demographic information achieving 80% and 75% accuracy at 75% and 90% sensitivity with 0.79 and 0.90 AUC on the internal and external test set, respectively. In comparison, the radiology residents achieved 71% and 65% accuracy at 61% and 35% sensitivity while the radiologists specialized in musculoskeletal tumor imaging achieved an 84% and 83% accuracy at 90% and 81% sensitivity, respectively.

CONCLUSIONS

An ANN combining radiomic features and demographic information showed the best performance in distinguishing between benign and malignant bone lesions. The model showed lower accuracy compared to specialized radiologists, while accuracy was higher or similar compared to residents.

KEY POINTS

• The developed machine learning model could differentiate benign from malignant bone tumors using radiography with an AUC of 0.90 on the external test set. • Machine learning models that used radiomic features or demographic information alone performed worse than those that used both radiomic features and demographic information as input, highlighting the importance of building comprehensive machine learning models. • An artificial neural network that combined both radiomic and demographic information achieved the best performance and its performance was compared to radiology readers on an external test set.

MRI-based delta-radiomics predicts pathologic complete response in high-grade soft-tissue sarcoma patients treated with neoadjuvant therapy

PURPOSE

In high-grade soft-tissue sarcomas (STS) the standard of care encompasses multimodal therapy regimens. While there is a growing body of evidence for prognostic pretreatment radiomic models, we hypothesized that temporal changes in radiomic features following neoadjuvant treatment ("delta-radiomics") may be able to predict the pathological complete response (pCR).

METHODS

MRI scans (T1-weighted with fat-saturation and contrast-enhancement (T1FSGd) and T2-weighted with fat-saturation (T2FS)) of patients with STS of the extremities and trunk treated with neoadjuvant therapy were gathered from two independent institutions (training: 103, external testing: 53 patients). pCR was defined as <5% viable cells. After segmentation and preprocessing, 105 radiomic features were extracted. Delta-radiomic features were calculated by subtraction of features derived from MRI scans obtained before and after neoadjuvant therapy. After feature reduction, machine learning modeling was performed in 100 iterations of 3-fold nested cross-validation. Delta-radiomic models were compared with single timepoint models in the testing cohort.

RESULTS

The combined delta-radiomic models achieved the best area under the receiver operating characteristic curve (AUC) of 0.75. Pre-therapeutic tumor volume was the best conventional predictor (AUC 0.70). The T2FS-based delta-radiomic model had the most balanced classification performance with a balanced accuracy of 0.69. Delta-radiomic models achieved better reproducibility than single timepoint radiomic models, RECIST or the peri-therapeutic volume change. Delta-radiomic models were significantly associated with survival in multivariate Cox regression.

CONCLUSION

This exploratory analysis demonstrated that MRI-based delta-radiomics improves prediction of pCR over tumor volume and RECIST. Delta-radiomics may one day function as a biomarker for personalized treatment adaptations.

Multitask Deep Learning for Segmentation and Classification of Primary Bone Tumors on Radiographs

Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and classification of primary bone tumors on radiographs. Materials and Methods This retrospective study analyzed bone tumors on radiographs acquired prior to treatment and obtained from patient data from January 2000 to June 2020. Benign or malignant bone tumors were diagnosed in all patients by using the histopathologic findings as the reference standard. By using split-sample validation, 70% of the patients were assigned to the training set, 15% were assigned to the validation set, and 15% were assigned to the test set. The final performance was evaluated on an external test set by using geographic validation, with accuracy, sensitivity, specificity, and 95% CIs being used for classification, the intersection over union (IoU) being used for bounding box placements, and the Dice score being used for segmentations. Results Radiographs from 934 patients (mean age, 33 years ± 19 [standard deviation]; 419 women) were evaluated in the internal data set, which included 667 benign bone tumors and 267 malignant bone tumors. Six hundred fifty-four patients were in the training set, 140 were in the validation set, and 140 were in the test set. One hundred eleven patients were in the external test set. The multitask DL model achieved 80.2% (89 of 111; 95% CI: 72.8, 87.6) accuracy, 62.9% (22 of 35; 95% CI: 47, 79) sensitivity, and 88.2% (67 of 76; CI: 81, 96) specificity in the classification of bone tumors as malignant or benign. The model achieved an IoU of 0.52 ± 0.34 for bounding box placements and a mean Dice score of 0.60 ± 0.37 for segmentations. The model accuracy was higher than that of two radiologic residents (71.2% and 64.9%; P = .002 and P < .001, respectively) and was comparable with that of two musculoskeletal fellowship-trained radiologists (83.8% and 82.9%; P = .13 and P = .25, respectively) in classifying a tumor as malignant or benign. Conclusion The developed multitask deep learning model allowed for accurate and simultaneous bounding box placement, segmentation, and classification of primary bone tumors on radiographs. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Carrino in this issue.

Development and External Validation of Deep-Learning-Based Tumor Grading Models in Soft-Tissue Sarcoma Patients Using MR Imaging

BACKGROUND

In patients with soft-tissue sarcomas, tumor grading constitutes a decisive factor to determine the best treatment decision. Tumor grading is obtained by pathological work-up after focal biopsies. Deep learning (DL)-based imaging analysis may pose an alternative way to characterize STS tissue. In this work, we sought to non-invasively differentiate tumor grading into low-grade (G1) and high-grade (G2/G3) STS using DL techniques based on MR-imaging.

METHODS

Contrast-enhanced T1-weighted fat-saturated (T1FSGd) MRI sequences and fat-saturated T2-weighted (T2FS) sequences were collected from two independent retrospective cohorts (training: 148 patients, testing: 158 patients). Tumor grading was determined following the French Federation of Cancer Centers Sarcoma Group in pre-therapeutic biopsies. DL models were developed using transfer learning based on the DenseNet 161 architecture.

RESULTS

The T1FSGd and T2FS-based DL models achieved area under the receiver operator characteristic curve (AUC) values of 0.75 and 0.76 on the test cohort, respectively. T1FSGd achieved the best F1-score of all models (0.90). The T2FS-based DL model was able to significantly risk-stratify for overall survival. Attention maps revealed relevant features within the tumor volume and in border regions.

CONCLUSIONS

MRI-based DL models are capable of predicting tumor grading with good reproducibility in external validation.

Prognostic Assessment in High-Grade Soft-Tissue Sarcoma Patients: A Comparison of Semantic Image Analysis and Radiomics

BACKGROUND

In patients with soft-tissue sarcomas of the extremities, the treatment decision is currently regularly based on tumor grading and size. The imaging-based analysis may pose an alternative way to stratify patients' risk. In this work, we compared the value of MRI-based radiomics with expert-derived semantic imaging features for the prediction of overall survival (OS).

METHODS

Fat-saturated T2-weighted sequences (T2FS) and contrast-enhanced T1-weighted fat-saturated (T1FSGd) sequences were collected from two independent retrospective cohorts (training: 108 patients; testing: 71 patients). After preprocessing, 105 radiomic features were extracted. Semantic imaging features were determined by three independent radiologists. Three machine learning techniques (elastic net regression (ENR), least absolute shrinkage and selection operator, and random survival forest) were compared to predict OS.

RESULTS

ENR models achieved the best predictive performance. Histologies and clinical staging differed significantly between both cohorts. The semantic prognostic model achieved a predictive performance with a C-index of 0.58 within the test set. This was worse compared to a clinical staging system (C-index: 0.61) and the radiomic models (C-indices: T1FSGd: 0.64, T2FS: 0.63). Both radiomic models achieved significant patient stratification.

CONCLUSIONS

T2FS and T1FSGd-based radiomic models outperformed semantic imaging features for prognostic assessment.

Oncological Outcome and Prognostic Factors of Surgery for Soft Tissue Sarcoma After Neoadjuvant or Adjuvant Radiation Therapy: A Retrospective Analysis over 15 Years

BACKGROUND/AIM

Surgical resection for soft tissue sarcomas (STSs) is the gold standard for a curative oncologic therapy in combination with neoadjuvant or adjuvant radiation therapy (NRT/ART). The aim of this study was to determine prognostic factors influencing the survival of patients with STS undergoing NRT or ART considering various parameters in a retrospective, single-centre analysis over 15 years.

PATIENTS AND METHODS

We included 119 patients (male 59) and the median follow-up period was 69 months (4-197). The patients received NRT (n=64) or ART (n=55). We recorded the histopathologic subtype of STS, tumour grade, localization, tumour margins, complications, survival, local recurrence, and metastases. Survival analysis was performed using the Kaplan-Meier method.

RESULTS

The overall survival rate was 68.9% at 5 years. The localization (epifascial/subfascial), resection margin and type of radiation therapy (NRT/ART) had no significant impact on survival. Tumour grade, tumour size, local recurrence and metastases were significantly correlated with patient survival (p<0.05). Local recurrence was significantly higher in patients with ART (p=0.044).

CONCLUSION

Tumour grade and tumour size were independently associated with disease-specific survival, and patients with local recurrence and metastases had lower survival rates.

Soft tissue masses: distribution of entities and rate of malignancy in small lesions

BACKGROUND

Small soft tissue masses are often falsely assumed to be benign and resected with failure to achieve tumor-free margins. Therefore, this study retrospectively investigated the distribution of histopathologic diagnosis to be encountered in small soft tissue tumors (≤ 5 cm) in a large series of a tertiary referral center.

METHODS

Patients with a soft tissue mass (STM) with a maximum diameter of 5 cm presenting at our institution over a period of 10 years, who had undergone preoperative Magnetic resonance imaging and consequent biopsy or/and surgical resection, were included in this study. A final histopathological diagnosis was available in all cases. The maximum tumor diameter was determined on MR images by one radiologist. Moreover, tumor localization (head/neck, trunk, upper extremity, lower extremity, hand, foot) and depth (superficial / deep to fascia) were assessed.

RESULTS

In total, histopathologic results and MR images of 1753 patients were reviewed. Eight hundred seventy patients (49.63%) showed a STM ≤ 5 cm and were therefore included in this study (46.79 +/- 18.08 years, 464 women). Mean maximum diameter of the assessed STMs was 2.88 cm. Of 870 analyzed lesions ≤ 5 cm, 170 (19.54%) were classified as superficial and 700 (80.46%) as deep. The malignancy rate of all lesions ≤ 5 cm was at 22.41% (superficial: 23.53% / deep: 22.14%). The malignancy rate dropped to 16.49% (20.79% / 15.32%) when assessing lesions ≤ 3 cm (p = 0.007) and to 15.0% (18.18% / 13.79%) when assessing lesions ≤ 2 cm (p = 0.006). Overall, lipoma was the most common benign lesion of superficial STMs (29.41%) and tenosynovial giant cell tumor was the most common benign lesion of deep STMs (23.29%). Undifferentiated pleomorphic sarcoma was the most common malignant diagnosis among both, superficial (5.29%) and deep (3.57%) STMs.

CONCLUSIONS

The rate of malignancy decreased significantly with tumor size in both, superficial and deep STMs. The distribution of entities was different between superficial and deep STMs, yet there was no significant difference found in the malignancy rate.

Preoperative Evaluation of Myxofibrosarcoma: Prognostic Value and Reproducibility of Different Features on MRI

BACKGROUND/AIM

Myxofibrosarcoma (MFS) is characterized by an infiltrative growth pattern. This study aimed to determine the correlation between overall survival (OS) and morphological features of MFS as well as examine the reproducibility of these findings on preoperative magnetic resonance imaging (MRI).

PATIENTS AND METHODS

Fifty-eight MFS patients underwent preoperative MR imaging with the following features analysed: i) tumour size, ii) localization, iii) margins, iv) morphology, v) signal characteristics, vi) contrast enhancement, vii) presence and extent of perilesional oedema, and viii) presence of the tail sign.

RESULTS

Only circumscribed perilesional oedema was associated with a significantly better survival compared to diffuse oedema (p=0.010), which was found in the majority of cases. The tail sign was found in less than 50% of the cases. Cohen's kappa coefficients confirmed a relatively high interrater variability.

CONCLUSION

Perilesional diffuse oedema on MR imaging of MFS is significantly correlated with a poor overall survival. The interrater variability in interpretation of MR examinations varies from slight to substantial agreement. Preoperative MR imaging with detailed planning of the resection seem to be a logical approach to achieve negative resection margins and recurrence-free survival.

Diffusion tensor imaging and tractography for preoperative assessment of benign peripheral nerve sheath tumors

PURPOSE

To evaluate the diagnostic value of fiber tractography and diffusivity analysis generated from 3D diffusion-weighted (DW) sequences for preoperative assessment of benign peripheral nerve sheath tumors.

METHOD

MR imaging at 3 T was performed in 22 patients (mean age 41.9 ± 17.1y, 13 women) with histologically confirmed schwannomas (N = 18) and histologically confirmed neurofibromas (N = 11), including a 3D DW turbo spin echo sequence with fat suppression. Diffusion tensor parameters were computed and fiber tracks were determined. Evaluation was performed by two radiologists and one orthopedic surgeon blinded for final diagnosis. Mean diffusivity was computed to allow further assessment of tumor microstructure. Preoperative fascicle visualization was graded, fascicles were categorized regarding anatomical location and amount of fascicles surrounding the tumor. The agreement of imaging findings with intraoperative findings was assessed.

RESULTS

On 78.3 % of the DTI images, the fascicle visualization was rated as good or very good. Tractography differences were observed in schwannomas and neurofibromas, showing schwannomas to be significantly more often located eccentrically to the nerve (94.8 %) than neurofibromas (0 %, P < 0.01). Fascicles were significantly more often continuous (87.5 %) in schwannomas, while in neurofibromas, none of the tracks was graded to be continuous (0 %, P = 0.014). A substantial agreement between fiber tracking and surgical anatomy was found regarding the fascicle courses surrounding the tumor (κ = 0.78). Mean diffusivity of schwannomas (1.5 ± 0.2 × 10^-3 mm²/s) was significantly lower than in neurofibromas (1.8 ± 0.2 × 10^-3 mm²/s; P < 0.001). The Youden index showed an optimal cutoff at 1.7 × 10^-3 mm²/s (sensitivity, 0.91; specificity, 0.78; J = 0.69).

CONCLUSIONS

Preoperative diffusion tensor imaging allowed to accurately differentiate between schwannomas and neurofibromas and to describe their location in relation to the nerve fascicles for preoperative planning.

Peri-Prosthetic Joint Infection of the Knee Causes High Levels of Psychosocial Distress: A Prospective Cohort Study

Background: Peri-prosthetic joint infection (PJI) is a major complication of knee arthroplasty that can cause long-term disability. In addition to its physical impact, there is a clear psychological burden that has not been measured yet. We hypothesized that the psychosocial burden of PJI can be assessed quantitatively using standardized questionnaires and may be correlated with treatment stage. Methods: Thirty-one patients were enrolled in this longitudinal prospective cohort study from August 2015 to November 2016. Participants had clinically established knee PJI after primary total knee replacement in osteoarthritis according to the Musculoskeletal Infection Society criteria and underwent a standardized two-stage protocol. After explantation of the prosthesis and implantation of a polymethylmethacrylate knee spacer, patients were treated with organism-specific intravenous antibiotics for two weeks, followed by oral antibiotics for four weeks; and then reimplantation was performed in all cases. Psychometrically validated standardized questionnaires were used to measure psychosocial stress via self-assessment at four time points: (1) Before explantation of the prosthesis; (2) after explantation; (3) after the antibiotic treatment before reimplantation; and (4) three months after reimplantation (follow-up). The Patient Health Questionnaire (PHQ)-4, Short Form (SF)-12 (including PSK and KSK), Questions about Life Satisfaction (FLZ^M) and Fear of Progression (PA-F-KF) (titles and abbreviations in German) scores were interpreted according to cut-off values for depression, fear of progression, anxiety, and quality of life. Results: Eighteen patients (58.1%) showed a PHQ-4 score above the cut-off value for depression at least once, with the highest score before reimplantation (time point 3). On the SF-12, the mean subtest mental scale (PSK) score was 42.6 (± 14.5), and the mean subtest physical scale (KSK) score was 26.9 (± 7.5) over the four time points, which was significantly lower than that of the general German population (PSK 53.1, KSK 44.0; p < 0.05). The SF-12 scores did not change significantly over time. On the FLZ, health was least satisfactory, followed by recreational activities and work. On the PA-F-KF, patients had the greatest fear of being dependent on outside help, drastic medical interventions, and infection progression. The mean PA-F-KF value was 31.24 (± 9.60; values ≥34 are regarded as critical). Conclusion: Peri-prosthetic joint infection is a measurable, relevant psychosocial stressor for patients. Their quality of life and fear of the disease progressing are comparable to those of oncology patients. Routine screening should be conducted to identify affected patients early for appropriate treatment, improving long-term outcomes. Orthopaedic surgeons who treat patients with PJI should initiate by psychologists as well in order to maintain the patient's long-term quality of life.

[Amputations around the knee]

An amputation around, through or below the knee joint constitutes a "huge" change in a patient's life. In Orthopaedics, amputations are most frequently performed in cases with musculoskeletal tumours or failed total knee arthroplasty. A multidisciplinary team approach (surgeon, anaesthetist, pain specialists, orthotist, psychologist etc.) and patient-specific treatment regime from the outset as well as a meticulous surgical technique are of the outmost importance. Nowadays, prosthetic legs can be fitted for nearly any amputation level. The functional outcome of amputations below the knee is usually superior to amputations above or through the knee joint. Postoperative stump conditioning is paramount and the final prosthetic leg should not be fitted earlier than 4-6 months postoperatively. Problems with wound healing, muscle contractures and phantom limb pain represent common complications which might adversely affect patient outcomes.

Chondrosarcoma of the Chest Wall: A Review of 53 Cases from Two Institutions

BACKGROUND/AIM

Chondrosarcomas (CS) of the chest wall are rare, but present an aggressive biological behavior compared to CS of the extremities. The aims of the present study were to determine factors associated with oncological outcomes as well as complications.

PATIENTS AND METHODS

We retrospectively analyzed 53 patients (42 primary, 11 recurrent tumors). In total, 39 central CS, 10 peripheral CS, 3 dedifferentiated CS and 1 mesenchymal CS were included. The ribs were most commonly affected (68%). Overall survival and disease-free survival were estimated with Kaplan-Meier analyses and compared with log-rank test.

RESULTS

Mean follow-up was 7 years. Negative margins were achieved in 87% of patients. Thirty patients (57%) remained continuously disease-free (NED), three (5%) NED after treatment of relapse, seven (13%) were alive with disease, twelve (23%) were dead with disease and one of other cause. The 10-year survival rate was 81% and 45% in primary and recurrent tumors, respectively. Survival was significantly affected by tumor stage (p<0.001), local recurrence (p=0.025) and metastases (p=0.002). Six complications (16%) were observed.

CONCLUSION

The outcome is rather poor, especially in patients with local recurrence. Presumably due to a high biological aggressiveness, a stricter definition of surgical margins should be considered for this location.

[Parosteal low-grade osteosarcoma with focal differentiation]

This case study deals with the case of a 16-year-old male patient with a low-grade parosteal osteosarcoma of the distal femur with focal differentiation. Case history, disease course, and surgery as well as the pathological workup with final diagnosis are presented. Relevant radiologic and pathologic differential diagnoses und diagnostic pitfalls are explained in detail and discussed. Additionally, postoperative treatment options are illustrated.

Tumor grading of soft tissue sarcomas using MRI-based radiomics

Background

Treatment decisions for multimodal therapy in soft tissue sarcoma (STS) patients greatly depend on the differentiation between low-grade and high-grade tumors. We developed MRI-based radiomics grading models for the differentiation between low-grade (G1) and high-grade (G2/G3) STS.

Methods

The study was registered at ClinicalTrials.gov (number NCT03798795). Contrast-enhanced T1-weighted fat saturated (T1FSGd), fat-saturated T2-weighted (T2FS) MRI sequences, and tumor grading following the French Federation of Cancer Centers Sarcoma Group obtained from pre-therapeutic biopsies were gathered from two independent retrospective patient cohorts. Volumes of interest were manually segmented. After preprocessing, 1394 radiomics features were extracted from each sequence. Features unstable in 21 independent multiple-segmentations were excluded. Least absolute shrinkage and selection operator models were developed using nested cross-validation on a training patient cohort (122 patients). The influence of ComBatHarmonization was assessed for correction of batch effects.

Findings

Three radiomic models based on T2FS, T1FSGd and a combined model achieved predictive performances with an area under the receiver operator characteristic curve (AUC) of 0.78, 0.69, and 0.76 on the independent validation set (103 patients), respectively. The T2FS-based model showed the best reproducibility. The radiomics model involving T1FSGd-based features achieved significant patient stratification. Combining the T2FS radiomic model into a nomogram with clinical staging improved prognostic performance and the clinical net benefit above clinical staging alone.

Interpretation

MRI-based radiomics tumor grading models effectively classify low-grade and high-grade soft tissue sarcomas.

Fund

The authors received support by the medical faculty of the Technical University of Munich and the German Cancer Consortium.

Psychosocial Distress in Follow-up Care - Results of a Tablet-based Routine Screening in 202 Patients With Sarcoma

BACKGROUND

Patients with sarcoma are particularly vulnerable to psychosocial distress. The aim of this study was to collect preliminary data on the prevalence of psychosocial distress in such patients during follow-up care and identify risk factors associated with higher psycho-oncological stress levels.

PATIENTS AND METHODS

The study retrospectively enrolled 202 patients with bone or soft-tissue sarcomas who underwent routine psychosocial distress screening during their follow-up care. All patients were screened using an electronic cancer-specific questionnaire.

RESULTS

Females and patients who underwent radiotherapy were more distressed. Psychosocial distress levels were markedly higher in the early postoperative phase, but approximately one-third of patients showed high psychosocial distress levels even more than 2 years postoperatively.

CONCLUSION

The results underscore the importance of routine psychosocial distress screenings in patients with sarcoma, which should be performed throughout the follow-up period.

[Total endoprosthetic replacement of femur, humerus and tibia]

Improvements in diagnostics and effectiveness of chemotherapy have resulted in most patients with primary malignant bone tumours being candidates for limb salvage surgery. Herewith, the use of modern modular tumour endoprostheses allows for the replacement of all big joints and even entire long bones such as the femur, humerus and tibia. In this article, we focus on individual prerequisites for and challenges with performing a total endoprosthetic reconstruction of the above-mentioned anatomic structures. Additionally, data from the literature with regards to functional outcome, problems and complications are presented.

Differentiating atypical lipomatous tumors from lipomas with magnetic resonance imaging: a comparison with MDM2 gene amplification status

Background

To evaluate the diagnostic value of MR imaging for the differentiation of lipomas and atypical lipomatous tumors (ALT) in comparison with histology and MDM2 amplification status.

Methods

Patients with well-differentiated lipomatous tumors (n = 113), of which 66 were diagnosed as lipoma (mean age 53 years (range, 13–82); 47% women) and 47 as atypical lipomatous tumor (ALT; mean age 60 years (range, 28–88); 64% women), were included into this study using histology and MDM2 amplification status by fluorescence in situ hybridization (FISH) as standard of reference. Preoperative MR images were retrospectively assessed by two radiologists for the following imaging features: maximum tumor diameter (mm) as well as the affected compartment (intramuscular, intermuscular or subcutaneous), septa (absent, thin (< 2 mm) or thick septa (> 2 mm) with nodular components); contrast enhancing areas within the lipomatous tumor (< 1/3 of the tumor volume, > 1/3 of the tumor volume);

Results

Of the 47 patients with ALT, 40 (85.1%) presented thick septa (> 2 mm) and this finding significantly increased the likelihood of ALT (OR 6.24, 95% CI 3.36–11.59; P < 0.001). The likelihood of ALT was increased if the tumor exceeded a maximum diameter of 130.0 mm (OR 2.74, 95% CI 1.82–4.11, P < 0.001). The presence of contrast enhancement in lipomatous tumors significantly increased the likelihood of ALT (Odds ratio (OR) 2.95, 95% confidence interval (CI) 2.01–4.31; P < 0.001). Of the lipomas, 21.1% were located subcutaneously, 63.6% intramuscularly and 15.2% intermuscularly. On the other hand, none of the ALTs were located subcutaneously, the majority was located intermuscularly (87.3%) and a small number of ALTs was located intramuscularly (12.7%).

Conclusions

Our results suggest that using specific morphological MR imaging characteristics (maximum tumor diameter, thick septa and contrast enhancement) and the information on the localization of the lipomatous tumor, a high sensitivity and substantial specificity can be achieved for the diagnosis of lipomas and ALTs.

Neoadjuvant image-guided helical intensity modulated radiotherapy of extremity sarcomas - a single center experience

Background

Advanced radiotherapy (RT) techniques allow normal tissue to be spared in patients with extremity soft tissue sarcoma (STS). This work aims to evaluate toxicity and outcome after neoadjuvant image-guided radiotherapy (IGRT) as helical intensity modulated radiotherapy (IMRT) with reduced margins based on MRI-based target definition in patients with STS.

Methods

Between 2010 to 2014, 41 patients with extremity STS were treated with IGRT delivered as helical IMRT on a tomotherapy machine. The tumor site was in the upper extremity in 6 patients (15%) and lower extremity in 35 patients (85%). Reduced margins of 2.5 cm in longitudinal direction and 1.0 cm in axial direction were used to expand the MRI-defined gross tumor volume, including peritumoral edema, to the clinical target volume. An additional margin of 5 mm was added to receive the planning target volume. The full total dose of 50 Gy in 2 Gy fractions was sucessfully applied in 40 patients. Two patients received chemotherapy instead of surgery due to systemic progression. All patients were included into a strict follow-up program and were seen interdisciplinarily by the Departments of Orthopaedic Surgery and Radiation Oncology.

Results

Thirty eight patients that received total RT total dose and subsequent resection were analyzed for outcome. After a median follow-up of 38.5 months cumulative OS, local PFS and systemic PFS at 2 years were determined at 78.2, 85.2 and 54.5%, respectively. Two of 6 local recurrences were proximal marginal misses. Negative resection margins were achieved in 84% of patients. The rate of major wound complications was comparable to previous IMRT studies with 36.8%. RT was overall tolerable with low toxicity rates.

Conclusions

IMRT-IGRT offers neoadjuvant treatment for extremity STS with reduced safety margins and thus low toxicity rates. Wound complication rates were comparable to previously reported frequencies. Two reported marginal misses suggest a word of caution for reduction of longitudinal safety margins.

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1207-2) contains supplementary material, which is available to authorized users.

[Megaimplants of the Proximal Femur: Current Concepts]

In addition to their outstanding significance in the field of tumor orthopaedics, megaprostheses are becoming increasingly important for revision arthroplasty. Despite their wide application, the reported complication and failure rates remain high. The analysis of failure mechanisms roughly allows a breakdown into mechanical and non-mechanical causes; soft-tissue failure, loosening and periprosthetic infection play outstanding roles. Each type of failure can be associated to a specific prosthetic component: To avoid soft tissue failure, muscular connection to the prosthesis is essential; to avoid loosening, the anchoring technique on the stem is crucial; to prevent infection, the surface condition or possibly the coating of the prosthesis seem to play major roles. Some fully-fledged proximal femoral replacement systems have become established on the market and have similar clinical outcomes. However, there are significant differences in anchoring techniques, modularity or module connections and soft tissue connection. In any case, the high failure rates show that there is great potential for future developments. Innovative suggestions for each component are certainly possible through cross-linking to already functioning systems. Together with new findings from basic research, future systems should be able to significantly reduce the rate of prosthetic failures.

Standardized Screening and Psycho-oncological Treatment of Orthopedic Cancer Patients

BACKGROUND/AIM

Psycho-oncological distress is a relevant clinical problem. The aim of this study was to administer a standardized psycho-oncological distress screening for early identification and indication-based treatment of highly distressed orthopedic cancer patients as well as the evaluation of distress patterns.

PATIENTS AND METHODS

In total, 35 patients with cancer were psycho-oncologically screened using a cancer-specific expert rating scale (Basic Documentation for Psycho-Oncology Short Form) at three different time points (day of admission, day before discharge, 3 months postoperatively). Psycho-oncological support was offered to all patients whose distress exceeded a defined cut-off value.

RESULTS

Levels of distress in approximately 51% of patients exceeded the cut-off value at the time of admission and these patients received psycho-oncological support. The high distress levels decreased significantly over time. Patients whose distress did not exceed the cut-off value at the first assessment showed low distress levels at all time points.

CONCLUSION

A relevant number of orthopedic tumor patients suffer from psychosocial distress. Standardized screening might help to identify and adequately treat those patients.

Prospective Analysis of a Sterile, Semi-automated Tissue Biopsy Homogenization Method in the Diagnosis of Prosthetic Joint Infections

BACKGROUND/AIM

Prosthetic joint infection (PJI) remains a serious complication of total joint arthroplasty. To effectively treat PJI, it is essential to identify the microorganism causing it and be able to combine correct surgical and anti-infective treatments. This cannot always be achieved with the currently employed diagnostic methods. The aim of this study was to evaluate a semi-automated tissue biopsy bead milling method (Ultra-TurrAX, Axonlab AG; Reichenbach, Germany) based on the hypothesis that the results are more sensitive for microbe detection and less prone to contamination.

MATERIALS AND METHODS

We included 35 consecutive patients undergoing 38 hip or knee arthroplasty revisions in this study. In addition to manually processed biopsies, we processed tissue specimens harvested intraoperatively using a semi-automated method. The sensitivity and specificity of both methods were calculated using MSIS criteria and sonication results as gold standards.

RESULTS

For total hip arthroplasty samples were evaluated separately based on MSIS criteria as the reference standard, Ultra-TurrAX processing yielded 81% (62-100%) sensitivity and 100% specificity. Using sonication as the gold standard, a sensitivity of 80% (60-100%) and specificity of 80% (45-100%) were calculated. In total knee arthroplasty, Ultra-TurrAX processing yielded 27% (1-54%) sensitivity and 57% (20-94%) specificity when using MSIS criteria as the gold standard. Using sonication as the gold standard, a sensitivity of 60% (17-100%) and specificity of 77% (54-100%) were calculated.

CONCLUSION

This is the first study to analyze bead mill processing in total hip and knee arthroplasty revisions in a consecutive patient series. The method's sensitivity was comparable to and its specificity superior to regular sample processing results reported in the literature with respect to hip arthroplasties and to both hip and knee arthroplasties collectively. With respect to total knee arthroplasties, the method fared worse in our collective, most likely due to the small number of patients in the sample. Integrating the method into the clinical workflow allowed for speedier and more efficient sample handling and processing. The theoretical advantage of a lower risk of contamination because of fewer manual processing steps is, in our opinion, valid.

Transcriptome based individualized therapy of refractory pediatric sarcomas: feasibility, tolerability and efficacy

Survival rates of pediatric sarcoma patients stagnated during the last two decades, especially in adolescents and young adults (AYAs). Targeted therapies offer new options in refractory cases. Gene expression profiling provides a robust method to characterize the transcriptome of each patient’s tumor and guide the choice of therapy.

Twenty patients with refractory pediatric sarcomas (age 8-35 years) were assessed with array profiling: ten had Ewing sarcoma, five osteosarcoma, and five soft tissue sarcoma. Overexpressed genes and deregulated pathways were identified as actionable targets and an individualized combination of targeted therapies was recommended. Disease status, survival, adverse events (AEs), and quality of life (QOL) were assessed in patients receiving targeted therapy (TT) and compared to patients without targeted therapy (non TT).

Actionable targets were identified in all analyzed biopsies. Targeted therapy was administered in nine patients, while eleven received no targeted therapy. No significant difference in risk factors between these two groups was detected. Overall survival (OS) and progression free survival (PFS) were significantly higher in the TT group (OS: P=0.0014, PFS: P=0.0011). Median OS was 8.83 versus 4.93 months and median PFS was 6.17 versus 1.6 months in TT versus non TT group, respectively. QOL did not differ at baseline as well as at four week intervals between the two groups. TT patients had less grade 1 AEs (P=0.009). The frequency of grade 2-4 AEs did not differ.

Overall, expression based targeted therapy is a feasible and likely beneficial approach in patients with refractory pediatric sarcomas that warrants further study.

[Spindle-cell osteosclerotic bone lesion with MDM2 amplification]

This case report presents an osteosclerotic bone lesion in a 49-year-old man with MDM2 amplification. The final diagnosis shows metastasis to the bones from stomach cancer. In primary bone tumours, the MDM2 amplifications observed have been described for many other tumour entities as well, and therefore do not exclude bone metastasis from a carcinoma.

IT-based Psychosocial Distress Screening in Patients with Sarcoma and Parental Caregivers via Disease-specific Online Social Media Communities

BACKGROUND

Psychosocial distress can be frequently observed in patients with sarcoma, depicting a relevant clinical problem. However, prospective data collection on psychosocial distress in patients with rare tumors is often time-consuming. In this context, social media such as Facebook can serve as a potential platform to expand research. The aim of this study was to assess the feasibility of psychosocial distress screening in patients with osteosarcoma and Ewing's sarcoma via social media.

MATERIALS AND METHODS

For this study an online questionnaire including general information and self-assessment distress measurement tools for patients and parents was created. The link to the questionnaire was then posted on the main page of the two largest disease-specific Facebook communities on osteosarcoma and Ewing's sarcoma.

RESULTS

Within 2 months, 28 patients and 58 parents of patients were enrolled. All patients with osteosarcoma and Ewing's sarcoma, as well as the majority of parental caregivers of such patients, showed relevant psychosocial distress levels.

CONCLUSION

Crowdsourcing via disease-specific patient communities on Facebook is feasible and provides great potential for acquisition of medical data of rare diseases.

Procalcitonin ratio indicates successful surgical treatment of abdominal sepsis

BACKGROUND

On-demand relaparotomy has been associated with a slightly decreased mortality compared to planned relaparotomy in the surgical treatment of secondary peritonitis. On-demand relaparotomy must be performed without delay to detect progressing sepsis early, before the onset of multiorgan failure. The aim of the study was to evaluate procalcitonin (PCT) as a parameter for early detection of progressing sepsis after operative treatment of the infective source.

METHODS

In 104 consecutive patients with secondary peritonitis, PCT serum levels were monitored on postoperative days 1 and 2 after initial operative elimination of the septic focus. The PCT ratio between postoperative days 1 and 2 was calculated and correlated to the success of the initial intervention. The latter was considered inadequate if relaparotomies were necessary to eliminate the intraabdominal infection.

RESULTS

Using classification and regression tree analysis, a cutoff could be calculated at 1.03 for the PCT ratio of postoperative day 1 to day 2. Lesser values indicated unsuccessful elimination of the septic source, whereas values above 1.03 represented successful operative treatment of the septic focus. Unsuccessful treatment of the septic process could be detected with a specificity of 63% and a sensitivity of 95%.

CONCLUSION

The PCT ratio appears to be a valuable aid in deciding if further relaparotomies are necessary after initial operative treatment of an intraabdominal septic focus.

Seronegative Herpes simplex Associated Esophagogastric Ulcer after Liver Transplantation

Herpes simplex infection is characterized by acute or subacute infection, often followed by a chronic carrier state. Consecutive recurrences may flare up if immunocompromise occurs. Herpes simplex associated esophagitis or duodenal ulcer have been reported in immunocompromised patients due to neoplasm, HIV/AIDS or therapeutically induced immune deficiency. Here we report the case of an HSV-DNA seronegative patient who developed grade III dysphagia 13 days after allogeneic liver transplantation. Endoscopy revealed an esophageal-gastric ulcer, and biopsy histopathology showed a distinct fibroplastic and capillary ulcer pattern highly suspicious for viral infection. Immunohistochemistry staining revealed a distinct nuclear positive anti-HSV reaction. Antiviral therapy with acyclovir and high-dose PPI led to a complete revision of clinical symptoms within 48 h. Repeat control endoscopy after 7 days showed complete healing of the former ulcer site at the gastroesophageal junction. Although the incidence of post-transplantation Herpes simplex induced gastroesophageal disease is low, the viral HSV ulcer may be included into a differential diagnosis if dysphagia occurs after transplantation even if HSV-DNA PCR is negative.

[Rare occurrence of fulminant acid burn of the esophagus]

Peptic ulcer due to Zollinger-Ellison syndrome is a rare entity. In this case report a 55-year-old man had a medical history of esophageal reflux, vomiting, and diarrhea for 10 years. Despite continuous medication with a proton pump inhibitor, no complete recovery from symptoms was achieved. A diagnosis of gastrinoma was at first not considered. After discontinuation of the proton pump inhibitor for only a few days, the strong stimulation of the gastrinoma led to fulminant hydrochloric acid burn of the distal esophagus with iatrogenic or spontaneous perforation at the esophagogastral junction. We describe the operative treatment as a two-stage reconstruction with colon interposition and resection of the primary tumor in the duodenum.

[Volumetry of the human tongue by MRI]

AIM

The purpose of this study was to determine the volume of the tongue using MRI. The correlation of the individual volume of the tongue and the size of the oral cavity was to be investigated.

MATERIAL AND METHODS

To analyze the tongue volume we combined coronal and sagittal data acquisition, which divided the tongue virtually into two lateral and one medial part. This procedure helped to decrease artefacts by partial volume effect. In 20 probands (m/f 7/13, average age of 36.3 years) the volume of the tongue was determined. Imaging protocol: Magnetom 63 SP (Siemens, Erlangen), T1-weighted sequences (TR/TE 500 ms/10 ms), slice thickness 5 mm, matrix 256 x 256, FOV 250 mm.

RESULTS

There was a significant linear regression between the tongue volume and height of the mouth cavity. This correlation can be used to calculate the normal volume of a patient's tongue.

DISCUSSION

Volumetry of the tongue can be carried out by means of MRI without application of injurious X-rays. It can be employed before as well as after tongue reduction surgeries for therapy control. The individual ideal tongue volume can be determined easily by determination of the height of the oral cavity.