Treatment effects in pediatric soft tissue and bone tumors: practical considerations for the pathologist

Can conventional magnetic resonance imaging at presentation predict chemoresistance in osteosarcoma?

OBJECTIVES

Histological tumour necrosis is the current indicator for the response of osteosarcoma after neoadjuvant chemotherapy. Chemoresistant tumours require close monitoring and adjustment of treatment. Characteristics of tumours on baseline MRI may be able to predict response to chemotherapy. The aim is to identify which baseline MRI findings can help predict chemoresistant osteosarcoma.

METHODS

Baseline MRI before giving neoadjuvant chemotherapy of 95 patients during 2008-2021 was reviewed by 2 musculoskeletal radiologists. Histological necrosis from surgical specimens was the reference standard. MRIs were reviewed for tumour characteristics (tumour volume, maximum axial diameter, central necrosis, haemorrhage, fluid-fluid level), peritumoural bone and soft tissue oedema, and other parameters including intra-articular extension, epiphyseal involvement, neurovascular involvement, pathologic fracture, and skip metastasis. The cut-off thresholds were generated by receiver operating characteristic curves which then tested for diagnostic accuracy.

RESULTS

Two-third of patients were chemoresistance (histological necrosis <90%). Tumour volume >150 mL, maximum axial diameter >7.0 cm, area of necrosis >50%, presence of intra-articular extension, and peritumoural soft tissue oedema >6.5 cm significantly predicted chemoresistance, particularly when found in combination. Tumour volume >150 mL and maximum axial diameter >7.0 cm could be used as an independent predictor (multivariable analysis, P-value = .025, .045).

CONCLUSIONS

Findings on baseline MRI could help predicting chemoresistant osteosarcoma with tumour size being the strongest predictor.

ADVANCES IN KNOWLEDGE

Osteosarcomas with large size, large cross-sectional diameter, large area of necrosis, presence of intra-articular extension, and extensive peritumoural soft tissue oedema were most likely to have a poor response to neoadjuvant chemotherapy.

Manual and Semi-Automated Measurement and Calculation of Osteosarcoma Treatment Effect Using Whole Slide Image and Qupath

INTRODUCTION

In osteosarcoma, the most significant indicator of prognosis is the histologic changes related to tumor response to preoperative chemotherapy, such as necrosis. We have developed a method to measure the osteosarcoma treatment effect using whole slide image (WSI) with an open-source digital image analytical software Qupath.

MATERIALS AND METHODS

In Qupath, each osteosarcoma case was treated as a project. All H&E slides from the entire representative slice of osteosarcoma were scanned into WSIs and imported into a project in Qupath. The regions of tumor and tumor necrosis were annotated, and their areas were measured in Qupath. In order to measure the osteosarcoma treatment effect, we needed to calculate the percentage of total necrosis area over total tumor area. We developed a tool that can automatically extract all values of tumor and necrosis areas from a Qupath project into an Excel file, sum these values for necrosis and whole tumor respectively, and calculate necrosis/tumor percentage.

CONCLUSION

Our method that combines WSI with Qupath can provide an objective measurement to facilitate pathologist's assessment of osteosarcoma response to treatment. The proposed approach can also be used for other types of tumors that have clinical need for post-treatment response assessment.

Dynamic Changes in Microvascular Density Can Predict Viable and Non-Viable Areas in High-Risk Neuroblastoma

Despite aggressive treatments, the prognosis of high-risk NB remains poor. Surgical oncology needs innovative intraoperative devices to help surgeons discriminate malignant tissue from necrotic and surrounding healthy tissues. Changes within the tumor vasculature could be used intraoperatively as a diagnostic tool to guide surgical resection. Here, we retrospectively analyzed the mean vascular density (MVD) of different NB subtypes at diagnosis and after induction chemotherapy using scanned histological samples. One patient was prospectively enrolled, and an ex vivo photoacoustic imaging (PAI) scan was performed on two representative sections to assess its capacity to discriminate different tumor regions. We found that post-chemotherapy, viable areas of differentiating NBs and ganglioneuroblastomas are associated with higher MVD compared to poorly differentiated NBs. Early necrotic regions showed higher MVD than late necrotic and viable regions. Finally, calcified areas showed significantly lower MVD than any other histological component. The acquired PAI images showed a good high-resolution ex vivo 3D delineation of NB margins. Overall, these results suggest that a high-definition preclinical imaging device such as PAI could potentially be exploited to guide surgical resection by identifying different vasculature signatures.

Radical Resection of Pediatric Fibrosarcoma Is Not Associated With Survival Benefit: A Nationwide Database Analysis

INTRODUCTION

Fibrosarcoma is one of the most common nonrhabdomyosarcoma soft tissue sarcomas in the pediatric population. Surgical resection is the cornerstone of treatment; however, optimal factors regarding the extent of fibrosarcoma resection in localized versus regional disease is poorly understood.

METHODS

The Surveillance, Epidemiology, and End Results database was queried for patients who are 19 y old or younger with a diagnosis of fibrosarcoma from 1975 to 2016. Kaplan-Meier analyses were performed for disease-specific survival on clinical and pathologic variables. Multivariate analysis was performed based on significant predictors of disease-specific survival.

RESULTS

There were 1290 patients (median age 13 [7-17] y) identified with fibrosarcoma. The overall survival rate at 20 y was 93%. Radical resection was performed on 22%, 40%, and 52% of patients with localized, regional, and distant Surveillance, Epidemiology, and End Results disease stage, respectively. Chemotherapy (P < 0.001), radiation (P < 0.001), histology (P < 0.001), and stage (P = 0.004) were significant predictors of increased mortality using univariate Kaplan-Meier analysis. Most patients (86%) with localized or regional stage who underwent radiation had fibrosarcomas of nondermatofibrosarcoma histology (P < 0.001). Dermatofibrosarcoma subtype comprised most radical resections (41%). Excluding distant stage, nondermatofibroma histology (hazard ratio 16.94, 95% confidence interval 3.77-76.01) and regional stage (hazard ratio 8.15, 95% confidence interval 2.93-22.69) were independent prognostic factors of mortality (both P < 0.001). Radical resection was not a significant independent prognostic indicator of survival.

CONCLUSIONS

Nondermatofibrosarcoma subtype is independently associated with increased mortality. Although surgery remains the mainstay of treatment, the extent of resection is not a predictor of survival for patients with the localized and regional stage of disease.

Radiomics of Musculoskeletal Sarcomas: A Narrative Review

Bone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenotype as well as the tumor microenvironment which, combined with other pertinent data such as genomics and proteomics and correlated with outcomes data, can produce accurate, robust, evidence-based, clinical-decision support systems. Our purpose in this narrative review is to offer an overview of radiomics studies dealing with Magnetic Resonance Imaging (MRI)-based radiomics models of bone and soft-tissue sarcomas that could help distinguish different histotypes, low-grade from high-grade sarcomas, predict response to multimodality therapy, and thus better tailor patients’ treatments and finally improve their survivals. Although showing promising results, interobserver segmentation variability, feature reproducibility, and model validation are three main challenges of radiomics that need to be addressed in order to translate radiomics studies to clinical applications. These efforts, together with a better knowledge and application of the “Radiomics Quality Score” and Image Biomarker Standardization Initiative reporting guidelines, could improve the quality of sarcoma radiomics studies and facilitate radiomics towards clinical translation.

Prediction of Neoadjuvant Chemotherapy Response in Osteosarcoma Using Convolutional Neural Network of Tumor Center 18F-FDG PET Images

We compared the accuracy of prediction of the response to neoadjuvant chemotherapy (NAC) in osteosarcoma patients between machine learning approaches of whole tumor utilizing fluorine−¹⁸fluorodeoxyglucose (¹⁸F-FDG) uptake heterogeneity features and a convolutional neural network of the intratumor image region. In 105 patients with osteosarcoma, ¹⁸F-FDG positron emission tomography/computed tomography (PET/CT) images were acquired before (baseline PET0) and after NAC (PET1). Patients were divided into responders and non-responders about neoadjuvant chemotherapy. Quantitative ¹⁸F-FDG heterogeneity features were calculated using LIFEX version 4.0. Receiver operating characteristic (ROC) curve analysis of ¹⁸F-FDG uptake heterogeneity features was used to predict the response to NAC. Machine learning algorithms and 2-dimensional convolutional neural network (2D CNN) deep learning networks were estimated for predicting NAC response with the baseline PET0 images of the 105 patients. ML was performed using the entire tumor image. The accuracy of the 2D CNN prediction model was evaluated using total tumor slices, the center 20 slices, the center 10 slices, and center slice. A total number of 80 patients was used for k-fold validation by five groups with 16 patients. The CNN network test accuracy estimation was performed using 25 patients. The areas under the ROC curves (AUCs) for baseline PET maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), metabolic tumor volume (MTV), and gray level size zone matrix (GLSZM) were 0.532, 0.507, 0.510, and 0.626, respectively. The texture features test accuracy of machine learning by random forest and support vector machine were 0.55 and 0. 54, respectively. The k-fold validation accuracy and validation accuracy were 0.968 ± 0.01 and 0.610 ± 0.04, respectively. The test accuracy of total tumor slices, the center 20 slices, center 10 slices, and center slices were 0.625, 0.616, 0.628, and 0.760, respectively. The prediction model for NAC response with baseline PET0 texture features machine learning estimated a poor outcome, but the 2D CNN network using ¹⁸F-FDG baseline PET0 images could predict the treatment response before prior chemotherapy in osteosarcoma. Additionally, using the 2D CNN prediction model using a tumor center slice of ¹⁸F-FDG PET images before NAC can help decide whether to perform NAC to treat osteosarcoma patients.

The relation between staging fluorine-18 fluorodeoxyglucose positron emission tomog- raphy/computed tomography metabolic parameters and tumor necrosis rate in pediatric osteosarcoma patients

Background/aim

The aim of this study was to investigate the contribution of fluorine-18 (F-18) fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) imaging in staging of pediatric osteosarcoma patients and also to evaluate the ability of metabolic parameters from the primary tumor to predict tumor necrosis rate (TNR).

Material and methods

F-18 FDG-PET/CT imaging was performed in staging 37 pediatric osteosarcoma patients. The metabolic parameters SUVmax (maximum standardised uptake value), MTV (metabolic tumour volume), and TLG (total lesion glycolysis) were measured from the primary tumor. TNR level of the primary tumor was histopathologically measured after standard neoadjuvant chemotherapy treatment. The contribution of F-18 FDG-PET/CT to staging of pediatric osteosarcoma patients and the accuracy of metabolic parameters of the primary tumor to predict TNR were analized by regression analysis.

Results

MTV and TLG of the primary tumor were found to efficiently predict histopathologic TNR, whereas SUVmax was not (P = 0.012, P = 0.027, P = 0.25, respectively). Also 5 of 12 patients (41.6%) who were initially defined as localised osteosarcoma were upstaged in consequence of staging F-18 FDG-PET/CT findings.

Conclusion

F-18 FDG-PET/CT staging in pediatric osteosarcoma patients can effectively distinguish metastatic-localised disease. MTV and TLG values are important parameters, which can efficiently be used to predict TNR.

Preliminary Radiogenomic Evidence for the Prediction of Metastasis and Chemotherapy Response in Pediatric Patients with Osteosarcoma Using 18F-FDF PET/CT, EZRIN and KI67

Simple Summary

Pediatric osteosarcoma is one of the most aggressive cancers, and predictions of metastasis and chemotherapy response have a significant impact on pediatric patient survival. Radiogenomics, as methods of analyzing gene expression or image texture features, have previously been used for the diagnosis of chemotherapy responses and metastasis and can reveal the current state of cancer. In this study, we aimed to generate a predictive model using gene expression and ¹⁸F-FDG PET/CT image texture features in pediatric osteosarcoma in relation to metastasis and chemotherapy response. A predictive model using radiogenomics technology that incorporates both imaging features and gene expression can accurately predict metastasis and chemotherapy responses to improve patient outcomes.

Abstract

Chemotherapy response and metastasis prediction play important roles in the treatment of pediatric osteosarcoma, which is prone to metastasis and has a high mortality rate. This study aimed to estimate the prediction model using gene expression and image texture features. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) images of 52 pediatric osteosarcoma patients were used to estimate the machine learning algorithm. An appropriate algorithm was selected by estimating the machine learning accuracy. ¹⁸F-FDG PET/CT images of 21 patients were selected for prediction model development based on simultaneous KI67 and EZRIN expression. The prediction model for chemotherapy response and metastasis was estimated using area under the curve (AUC) maximum image texture features (AUC_max) and gene expression. The machine learning algorithm with the highest test accuracy in chemotherapy response and metastasis was selected using the random forest algorithm. The chemotherapy response and metastasis test accuracy with image texture features was 0.83 and 0.76, respectively. The highest test accuracy and AUC of chemotherapy response with AUC_max, KI67, and EZRIN were estimated to be 0.85 and 0.89, respectively. The highest test accuracy and AUC of metastasis with AUC_max, KI67, and EZRIN were estimated to be 0.85 and 0.8, respectively. The metastasis prediction accuracy increased by 10% using radiogenomics data.

Prediction of neoadjuvant chemotherapy response in high-grade osteosarcoma: added value of non-tumorous bone radiomics using CT images

Background

This study aimed to determine the impact of including radiomics analysis of non-tumorous bone region of interest in improving the performance of pathological response prediction to chemotherapy in high-grade osteosarcomas (HOS), compared to radiomics analysis of tumor region alone.

Methods

This retrospective study included 157 patients diagnosed with HOS between November 2013 and November 2017 (age range, 5-44 years; mean age, 16.99 ±7.42 years), in which 69 and 88 patients were diagnosed as pathological good response (pGR) and non-pGR, respectively. Radiomics features were extracted from tumor and non-tumorous bone regions based on diagnostic CT images. Pathological response classifiers were developed and validated via leave-one-out cross validation (LOOCV) and independent validation methods by using the area under the receiver operating characteristic curve (AUC) value as the figure of merit.

Results

Using the LOOCV, the classifiers combining features from tumor and non-tumorous regions showed better prediction performance than those from tumor region alone (AUC, 0.8207±0.0043 vs. 0.7799±0.0044). The combined classifier also showed better performance than the tumor feature-based classifier in both training and validation datasets [training dataset: 0.791, 95% confidence interval (CI), 0.706-0.860 vs. 0.766, 95% CI, 0.679-0.840; validation dataset: 0.816, 95% CI, 0.662-0.920 vs. 0.766, 95% CI, 0.606-0.885].

Conclusions

Radiomics analysis of combined tumor and non-tumorous bone features showed improved performance of pathological response prediction to chemotherapy in HOS compared to that of tumor features alone. Moreover, the proposed classifier had the potential to predict pathological response to chemotherapy for HOS patients.

Texture analysis for chemotherapy response evaluation in osteosarcoma using MR imaging

The efficacy of MRI-based statistical texture analysis (TA) in predicting chemotherapy response among patients with osteosarcoma was assessed. Forty patients (male: female = 31:9; age = 17.2 ± 5.7 years) with biopsy-proven osteosarcoma were analyzed in this prospective study. Patients were scheduled for three cycles of neoadjuvant chemotherapy (NACT) and diffusion-weighted MRI acquisition at three time points: at baseline (t0), after the first NACT (t1) and after the third NACT (t2) using a 1.5 T scanner. Eight patients (nonsurvivors) died during NACT while 34 patients (survivors) completed the NACT regimen followed by surgery. Histopathological evaluation was performed in the resected tumor to assess NACT response (responder [≤50% viable tumor] and nonresponder [>50% viable tumor]) and revealed nonresponder: responder = 20:12. Apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameters, diffusion coefficient (D), perfusion coefficient (D*) and perfusion fraction (f) were evaluated. A total of 25 textural features were evaluated on ADC, D, D* and f parametric maps and structural T1-weighted (T1W) and T2-weighted (T2W) images in the entire tumor volume using 3D TA methods gray-level cooccurrence matrix (GLCM), neighborhood gray-tone-difference matrix (NGTDM) and run-length matrix (RLM). Receiver-operating-characteristic curve analysis was performed on the selected textural feature set to assess the role of TA features (a) as marker(s) of tumor aggressiveness leading to mortality at baseline and (b) in predicting the NACT response among survivors in the course of treatment. Findings showed that the NGTDM features coarseness, busyness and strength quantifying tumor heterogeneity in D, D* and f maps and T1W and T2W images were useful markers of tumor aggressiveness in identifying the nonsurvivor group (area-under-the-curve [AUC] = 0.82-0.88) at baseline. The GLCM features contrast and correlation, NGTDM features contrast and complexity and RLM feature short-run-low-gray-level-emphasis quantifying homogeneity/terogeneity in tumor were effective markers for predicting chemotherapeutic response using D (AUC = 0.80), D* (AUC = 0.80) and T2W (AUC = 0.70) at t0, and D* (AUC = 0.80) and f (AUC = 0.70) at t1. 3D statistical TA features might be useful as imaging-based markers for characterizing tumor aggressiveness and predicting chemotherapeutic response in patients with osteosarcoma.

A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation

OBJECTIVES

To assess the methodological quality and risk of bias in radiomics studies investigating diagnosis, therapy response, and survival of patients with osteosarcoma.

METHODS

In this systematic review, literatures on radiomics in osteosarcoma were included and assessed for methodological quality through the radiomics quality score (RQS). The risk of bias and concern of application was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. A meta-analysis of studies focusing on predicting osteosarcoma response to neoadjuvant chemotherapy was performed.

RESULTS

Twelve radiomics studies exploring osteosarcoma were identified, and five were included in meta-analysis. The RQS reached an average of 20.4% (6.92 of 36) with good inter-rater agreement (ICC 0.95, 95% CI 0.85-0.99). Four studies validated results with an internal dataset, none of which used external dataset; one study was prospectively designed, and another one shared part of the dataset. The risk of bias and concern of application were mainly related to index test aspect. The meta-analysis showed a diagnostic odds ratio of 43.68 (95%CI 13.5-141.31) for predicting response to neoadjuvant chemotherapy with high heterogeneity and low methodological quality.

CONCLUSIONS

The overall scientific quality of included studies is insufficient; however, radiomics remains a promising technology for predicting treatment response, which might guide therapeutic decision-making and related to prognosis. Improvements in study design, validation, and open science needs to be made to demonstrate the generalizability of findings and to achieve clinical applications. Widespread application of RQS, pre-trained RQS scoring procedure, and modification of RQS in response to clinical needs are necessary.

KEY POINTS

• Limited radiomics studies were established in osteosarcoma with mean RQS of 20.4%, commonly due to unvalidated results, retrospective study design, and absence of open science. • Meta-analysis of radiomics studies predicting osteosarcoma response to neoadjuvant chemotherapy showed high diagnostic odds ratio 43.68, while high heterogeneity and low methodological quality were the main concerns. • A previously trained data extraction instrument allowed reaching moderate inter-rater agreement in RQS applications, while RQS still needs improvement to become a wide adaptive tool in reviews of radiomics studies, in routine self-check before manuscript submitting and in study design.

Rhabdomyosarcoma with an intratumoral adult type rhabdomyoma nodule with focal neuronal differentiation - diagnosis, prognosis and treatment of a rare disease

Rhabdomyosarcomas with areas reminiscent of adult type rhabdomyoma are rare and almost exclusive of pretreated tumors. We present a case of 17-year-old patient who sought medical assistance due to a right painless paratesticular mass. At gross examination, the paratesticular mass was a 5 cm tumor (embryonal rhabdomyosarcoma) with a discrete 2.0 cm grayish nodule at the periphery. At microscopy, smaller nodule showed large eosinophilic granular cells suggestive of adult type rhabdomyoma. These cells were strongly and diffusely positive for desmin and multifocally positive for myogenin. Focal neuronal and neural differentiations (NSE and GFAP expression) were also detected. Awareness of benign appearing intratumoral rhabdomyoma in rhabdomyosarcomas of paratestis/retroperitonium is of relevance. Such tumor heterogeneity may be a diagnostic pitfall especially in the scenario of needle biopsies and frozen section consultation.

A Delta-radiomics model for preoperative evaluation of Neoadjuvant chemotherapy response in high-grade osteosarcoma

Background

The difficulty of assessment of neoadjuvant chemotherapeutic response preoperatively may hinder personalized-medicine strategies that depend on the results from pathological examination.

Methods

A total of 191 patients with high-grade osteosarcoma (HOS) were enrolled retrospectively from November 2013 to November 2017 and received neoadjuvant chemotherapy (NCT). A cutoff time of November 2016 was used to divide the training set and validation set. All patients underwent diagnostic CTs before and after chemotherapy. By quantifying the tumor regions on the CT images before and after NCT, 540 delta-radiomic features were calculated. The interclass correlation coefficients for segmentations of inter/intra-observers and feature pair-wise correlation coefficients (Pearson) were used for robust feature selection. A delta-radiomics signature was constructed using the lasso algorithm based on the training set. Radiomics signatures built from single-phase CT were constructed for comparison purpose. A radiomics nomogram was then developed from the multivariate logistic regression model by combining independent clinical factors and the delta-radiomics signature. The prediction performance was assessed using area under the ROC curve (AUC), calibration curves and decision curve analysis (DCA).

Results

The delta-radiomics signature showed higher AUC than single-CT based radiomics signatures in both training and validation cohorts. The delta-radiomics signature, consisting of 8 selected features, showed significant differences between the pathologic good response (pGR) (necrosis fraction ≥90%) group and the non-pGR (necrosis fraction < 90%) group (P < 0.0001, in both training and validation sets). The delta-radiomics nomogram, which consisted of the delta-radiomics signature and new pulmonary metastasis during chemotherapy showed good calibration and great discrimination capacity with AUC 0.871 (95% CI, 0.804 to 0.923) in the training cohort, and 0.843 (95% CI, 0.718 to 0.927) in the validation cohort. The DCA confirmed the clinical utility of the radiomics model.

Conclusion

The delta-radiomics nomogram incorporating the radiomics signature and clinical factors in this study could be used for individualized pathologic response evaluation after chemotherapy preoperatively and help tailor appropriate chemotherapy and further treatment plans.

Chemoradiotherapy-induced Cytodifferentiation in Bladder/Prostate Rhabdomyosarcoma With Genetic Downregulation of Myogenin and MyoD1 Gene Expression: A Case Study and Review of the Literature

Rhabdomyosarcoma is the most common sarcoma diagnosed in childhood and adolescence, arising from the bladder/prostate in only 5%-10% of cases. Treatment-induced cytodifferention of tumor cells into mature rhabdomyoblasts has been reported following chemoradiation and is thought to suggest a more favorable outcome. We report a case of embryonal rhabdomyosarcoma of the bladder/prostate that exhibited extensive cytodifferentiation with downregulation of myogenin and MyoD1 gene expression in rhabdomyoblasts following treatment with chemoradiation therapy. The downregulation of myogenin and MyoD1 expression in rhabdomyoblasts following chemoradiation treatment has not previously been described in the literature and its significant remains uncertain.

Prediction of Chemotherapy Response of Osteosarcoma Using Baseline 18F-FDG Textural Features Machine Learning Approaches with PCA

Purpose

Patients with high-grade osteosarcoma undergo several chemotherapy cycles before surgical intervention. Response to chemotherapy, however, is affected by intratumor heterogeneity. In this study, we assessed the ability of a machine learning approach using baseline ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emitted tomography (PET) textural features to predict response to chemotherapy in osteosarcoma patients.

Materials and Methods

This study included 70 osteosarcoma patients who received neoadjuvant chemotherapy. Quantitative characteristics of the tumors were evaluated by standard uptake value (SUV), total lesion glycolysis (TLG), and metabolic tumor volume (MTV). Tumor heterogeneity was evaluated using textural analysis of ¹⁸F-FDG PET scan images. Assessments were performed at baseline and after chemotherapy using ¹⁸F-FDG PET; ¹⁸F-FDG textural features were evaluated using the Chang-Gung Image Texture Analysis toolbox. To predict the chemotherapy response, several features were chosen using the principal component analysis (PCA) feature selection method. Machine learning was performed using linear support vector machine (SVM), random forest, and gradient boost methods. The ability to predict chemotherapy response was evaluated using the area under the receiver operating characteristic curve (AUC).

Results

AUCs of the baseline ¹⁸F-FDG features SUVmax, TLG, MTV, 1st entropy, and gray level co-occurrence matrix entropy were 0.553, 0538, 0.536, 0.538, and 0.543, respectively. However, AUCs of the machine learning features linear SVM, random forest, and gradient boost were 0.72, 0.78, and 0.82, respectively.

Conclusion

We found that a machine learning approach based on ¹⁸F-FDG textural features could predict the chemotherapy response using baseline PET images. This early prediction of the chemotherapy response may aid in determining treatment plans for osteosarcoma patients.

Preclinical rationale for entinostat in embryonal rhabdomyosarcoma

Background

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in the pediatric cancer population. Survival among metastatic RMS patients has remained dismal yet unimproved for years. We previously identified the class I-specific histone deacetylase inhibitor, entinostat (ENT), as a pharmacological agent that transcriptionally suppresses the PAX3:FOXO1 tumor-initiating fusion gene found in alveolar rhabdomyosarcoma (aRMS), and we further investigated the mechanism by which ENT suppresses PAX3:FOXO1 oncogene and demonstrated the preclinical efficacy of ENT in RMS orthotopic allograft and patient-derived xenograft (PDX) models. In this study, we investigated whether ENT also has antitumor activity in fusion-negative eRMS orthotopic allografts and PDX models either as a single agent or in combination with vincristine (VCR).

Methods

We tested the efficacy of ENT and VCR as single agents and in combination in orthotopic allograft and PDX mouse models of eRMS. We then performed CRISPR screening to identify which HDAC among the class I HDACs is responsible for tumor growth inhibition in eRMS. To analyze whether ENT treatment as a single agent or in combination with VCR induces myogenic differentiation, we performed hematoxylin and eosin (H&E) staining in tumors.

Results

ENT in combination with the chemotherapy VCR has synergistic antitumor activity in a subset of fusion-negative eRMS in orthotopic “allografts,” although PDX mouse models were too hypersensitive to the VCR dose used to detect synergy. Mechanistic studies involving CRISPR suggest that HDAC3 inhibition is the primary mechanism of cell-autonomous cytoreduction in eRMS. Following cytoreduction in vivo, residual tumor cells in the allograft models treated with chemotherapy undergo a dramatic, entinostat-induced (70–100%) conversion to non-proliferative rhabdomyoblasts.

Conclusion

Our results suggest that the targeting class I HDACs may provide a therapeutic benefit for selected patients with eRMS. ENT’s preclinical in vivo efficacy makes ENT a rational drug candidate in a phase II clinical trial for eRMS.

Electronic supplementary material

The online version of this article (10.1186/s13395-019-0198-x) contains supplementary material, which is available to authorized users.

Utility of VS38c in the diagnostic and prognostic assessment of osteosarcoma and other bone tumours/tumour-like lesions

Background

VS38c is a monoclonal antibody that recognises a rough endoplasmic reticulum (rER) intracellular antigen termed cytoskeleton-linking membrane protein 63. rER is typically found in viable tumour cells and is abundant in osteosarcoma cells. The aim of this study was to determine the diagnostic and prognostic utility of VS38c in the histological assessment of osteosarcoma and other bone tumours/tumour-like leisons.

Methods

Immunohistochemical staining with VS38c was carried out on formalin-fixed specimens of osteosarcoma (pre/post-chemotherapy) and a wide range of benign and malignant bone lesions. In addition, VS38c staining of cultures of MG63 and Sa0S2 osteosarcoma cell cultures. (±cisplatin and actinomycin D-treatment) was analysed.

Results

VS38c strongly stained tumour cells in all low-grade and high-grade osteosarcomas and in undifferentiated sarcomas and high-grade chondrosarcomas. There was little or no VS38c staining of low-grade chondrosarcomas or chordomas and variable staining of Ewing sarcomas. Osteoblasts in benign bone-forming tumours and mononuclear stromal cells in chondroblastomas, giant cell tumours and non-ossifying fibromas strongly stained for VS38c. VS38c staining was absent in cisplatin and actinomycin D treated Sa0S2 and MG63 cells. In specimens of osteosarcoma post-neoadjuvant therapy, VS38c staining was absent in most morphologically necrotic areas of tumor although some cells with pyknotic nuclei stained for VS38c in these areas. Most tumour cells exhibiting atypical nuclear forms were not stained by VS38c.

Conclusions

Our findings show that VS38c is a sensitive but not specific diagnostic marker of osteosarcoma. Staining with VS38c identifies viable osteosarcoma cells, a feature which may be useful in the assessment of percentage tumour necrosis post-neoadjuvant chemotherapy.

Clinico-pathological Study of Limb Salvage Surgery for Osteosarcoma: Experience in a Rural Cancer Center

Although recent multimodality therapeutic protocols have led to improved survival in osteosarcoma (OS), the outcome still remains dismal. Ongoing international multicentric trials on OS aim to randomize patients for optimum management, based on histological response to NACT. The pathologic response to neoadjuvant chemotherapy (NACT) is the most important factor predicting prognosis. In this study of 23 cases of limb salvage surgery post neoadjuvant chemotherapy, mean age was 18.3 years, with male predominance. 65.5 % cases were conventional OS. Histologic assessment of chemotherapeutic effect done by Huvos grading revealed good response (Huvos lll and lV) in 15 (65.2 %) and poor response (Huvos l and ll) in eight (34.8 %). A scoring based on MRI with a scale of 1-6 was compared with histologic response. Five (62.5 %) of poor responders showed score of >3 and 73.3 % of good responders showed ≤3. Dose intensity of NACT was calculated and correlated with the histological response. 53.3 % of good responders showed ARDI > 0.9. Five (21.7 %) developed local recurrence and 10(43.4 %) had pulmonary metastasis. Adoption of more aggressive treatment modalities may ensure better histologic response and longer event free survival.

Survival and prognostic factors in Chinese patients with osteosarcoma: 13-year experience in 365 patients treated at a single institution

This study was designed to retrospectively analyze the survival and prognostic factors in Chinese osteosarcoma patients received neoadjuvant chemotherapy or/and surgery in a single institution. A total of 365 patients with pathological proved osteosarcoma undergoing neoadjuvant chemotherapy or/and surgery in a single institution between December 1999 and December 2012 were retrospectively analyzed for the demographic, tumor-related, and treatment-related variables, prognostic factors for survival rate and chemotherapy response. There were 231 males and 134 females (ratio, 1.72:1). The average age was 21±10years, with peak age between 10 and 20 years old (62%, 226/365). Of 365 patients, 319 (87.4%) suffered from primary tumor only, and 46 (12.6%) had metastases upon initial presentation. The overall 5-year survival rate was 65%. Upon univariate analysis, tumor site (femur 60.3%; other long bone 70.2%; trunk 33.6%; P=0.012), primary metastases (yes 36.7%; no 68.9%; P=0.000), tumor response to preoperative chemotherapy (good 89.8%; poor 47.5%; P=0.001) and recurrence/metastases after treatment (yes 36.2%; no 63.8%; P=0.000) were associated with higher 5-year survival rate. All factors except tumor site maintained their significance in multivariate testing. Male sex and nonconventional subtype of tumor were related to a higher likelihood of poor chemotherapy response.The absence of metastases at initial presentation, negative local recurrence or metastases after treatment, and tumor response to chemotherapy are of independent prognostic value in osteosarcoma. The overall prognostic factors and survival in Chinese patients are similar to those patients reported in western countries.

Histopathologic Features of Prognostic Significance in High-Grade Osteosarcoma

Context .- In osteosarcoma treated with neoadjuvant chemotherapy the extent of tumor necrosis on resection is considered an indicator of treatment response, and this has been shown to correlate with survival in most but not all studies. Objective .- To identify additional histologic variables of prognostic significance in high-grade osteosarcoma. Design .- Slides of pretreatment biopsy and primary postneoadjuvant chemotherapy resections from 165 patients with high-grade osteosarcoma were reviewed. Univariate (Kaplan-Meier) and multivariate (Cox regression) analyses were performed to identify clinical and histomorphologic attributes associated with overall survival. Results .- Univariate analyses confirmed the prognostic significance of metastatic status on presentation, primary tumor size, anatomic site, and histologic subtype. Additionally, the identification of lymphovascular invasion, 10% or more residual viable tumor, and 10 or more mitoses per 10 high-powered fields assessed in posttreatment resections were associated with poor survival, retaining significance in multivariate analyses. Based on results from multivariate analysis, we developed a prognostic index incorporating primary tumor size and site, and significant histologic features assessed on resection (ie, lymphovascular invasion status, mitotic rate, and extent of viable tumor). This scoring system segregates patients into 3 risk categories with significant differences in overall survival and retained significance in an independent validation set of 42 cases. Conclusions .- The integration of clinical and microscopic features improves prognostication of patients with osteosarcoma.

Adipocyte-Like Differentiation in a Posttreatment Embryonal Rhabdomyosarcoma

We describe a 16-year-old boy with rhabdomyosarcoma, consistent with embryonal subtype, of the lower extremity who received systemic neoadjuvant chemotherapy and subsequent excision. Microscopic sections of the postchemotherapy excision demonstrated diffuse, prominent, and immature adipocyte-like differentiation, in addition to skeletal muscle differentiation. Adipocyte-like differentiation was confirmed by a combination of positive Oil Red O and adipophilin immunohistochemical staining. To our knowledge, this represents the first report of an unusual phenomenon of differentiation of a soft tissue rhabdomyosarcoma into adipocyte-like cells after chemotherapy.

Usefulness of increased 18F-FDG uptake for detecting local recurrence in patients with extremity osteosarcoma treated with surgical resection and endoprosthetic replacement

OBJECTIVE

To investigate the changes of increased F-18 fluorodeoxyglucose ((18)F-FDG) uptake around the prosthesis and its ability to differentiate local recurrence from postsurgical change after endoprosthetic replacement in extremity osteosarcoma.

MATERIALS AND METHODS

A total of 355 positron emission tomography (PET)/computed tomography (CT) scans in 109 extremity osteosarcoma patients were retrospectively analyzed. All patients were followed up with (18)F-FDG PET/CT for more than 3 years after tumor resection. For semiquantitative assessment, we drew a volume of interest around the entire prosthesis of the extremity and measured the maximum standardized uptake value (SUV max). Independent samples t test was used to compare SUV max at each follow-up time. SUV max at 3 months (SUV1) and SUV max at the time of local recurrence in patients with recurrence or at the last follow-up in others (SUV2) were compared using the Mann-Whitney test. Diagnostic performances of PET parameters were assessed using ROC curve analyses.

RESULTS

Nine patients (8 %) showed a local recurrence. Mean SUV max at 3, 12, 24, and 36 months was 3.1 ± 1.5, 3.8 ± 1.9, 3.6 ± 1.9, and 3.7 ± 1.5 respectively. In ROC curve analysis, the combination of SUV2 >4.6 and ΔSUV >75.0 was a more useful parameter for predicting local recurrence than SUV2 or ΔSUV alone. The sensitivity, specificity, and accuracy for identifying local recurrence were 89, 76, 77 % for SUV2; 78, 81, 81 % for ΔSUV; and 78, 94, 93 % for the combined criterion respectively.

CONCLUSION

The combination of SUV2 and ΔSUV was more useful than the SUV2 or ΔSUV used alone for the prediction of local recurrence.

Early response monitoring to neoadjuvant chemotherapy in osteosarcoma using sequential ¹⁸F-FDG PET/CT and MRI

PURPOSE

We evaluated the potential of sequential fluorine-18 fluorodeoxyglucose ((18) F-FDG) positron emission tomography (PET)/computed tomography (CT) and MRI (PET/MRI) after one cycle of neoadjuvant chemotherapy to predict a poor histologic response in osteosarcoma.

METHODS

A prospective study was conducted on 30 patients with osteosarcoma treated with two cycles of neoadjuvant chemotherapy and surgery. All patients underwent PET/MRI before, after one cycle, and after the completion of neoadjuvant chemotherapy, respectively. Imaging parameters [maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and tumor volume based on magnetic resonance (MR) images (MRV)] and their % changes were calculated on each PET/MRI data set, and histological responses were evaluated on the postsurgical specimen.

RESULTS

A total of 17 patients (57%) exhibited a poor histologic response after two cycles of chemotherapy. Unlike the little volumetric change in MRI, PET parameters significantly decreased after one and two cycles of chemotherapy, respectively. After one cycle of chemotherapy, SUVmax, MTV, and TLG predicted the poor responders. Among these parameters, either MTV ≥ 47 mL or TLG ≥ 190 g after one cycle of chemotherapy was significantly associated with a poor histologic response on multivariate logistic regression analysis (OR 8.98, p = 0.039). The sensitivity, specificity, and accuracy of these parameters were 71%, 85% and 77%; and 71%, 85% and 77 %, respectively.

CONCLUSION

The histologic response to neoadjuvant chemotherapy in osteosarcoma can be predicted accurately by FDG PET after one course of chemotherapy. Among PET parameters, MTV and TLG were independent predictors of the histologic response.

Rhabdomyosarcoma with pseudolipoblasts arising in ovarian carcinosarcoma: a distinctive postchemotherapy morphologic variant mimicking pleomorphic liposarcoma

We describe a case of ovarian carcinosarcoma occurring in a 60-year-old female. The neoplasm was excised after neoadjuvant chemotherapy and contained a predominant heterologous pleomorphic rhabdomyosarcomatous component in which there were numerous multivacuolated rhabdomyoblasts that strongly mimicked lipoblasts. The clear cell variant of rhabdomyosarcoma is rarely documented, but this case shows a highly unusual finding in which the rhabdomyoblasts show the prominent multivacuolation with nuclear indentation characteristic of and indistinguishable from pleomorphic lipoblasts. This appears to represent a posttreatment phenomenon. As this finding might conceivably occur in other rhabdomyosarcomas after chemotherapy, we highlight the potential for diagnostic confusion with pleomorphic liposarcoma, which is usually diagnosed by morphology so that immunohistochemistry for muscle markers might not be performed.

Initial metabolic tumor volume measured by 18F-FDG PET/CT can predict the outcome of osteosarcoma of the extremities

We evaluated the ability of metabolic and volumetric parameters measured by pretreatment (18)F-FDG PET/CT to predict the survival of patients with osteosarcoma of the extremities.

METHODS

The records of 83 patients with American Joint Committee on Cancer stage II extremity osteosarcoma treated with surgery and chemotherapy were retrospectively reviewed. Imaging parameters (maximum standardized uptake value, metabolic tumor volume [MTV], total lesion glycolysis, and tumor volume based on MR images) were measured before treatment, and histologic responses to neoadjuvant chemotherapy were assessed by examination of postsurgical specimens. Receiver-operating-characteristic curve analyses and the Cox proportional hazards model were used to analyze whether imaging and clinicopathologic parameters could predict metastasis-free survival.

RESULTS

Of the imaging parameters, MTV at the fixed standardized uptake value threshold of 2.0 (MTV(2.0)) most accurately predicted metastasis by receiver-operating-characteristic curve analysis (area under the curve = 0.679, P = 0.011). By multivariate analysis, MTV(2.0) > 105 mL (relative risk, 3.93; 95% confidence interval, 1.55-9.92) and poor response to neoadjuvant chemotherapy (relative risk, 4.83; 95% confidence interval, 1.64-14.21) independently shortened metastasis-free survival (P = 0.004 for both parameters). The stratification of patients by the combined criteria of MTV(2.0) and histologic response predicted outcome in more detail.

CONCLUSION

MTV is an independent predictor of metastasis in patients with osteosarcoma of the extremities. The combination of MTV and histologic response predicts survival more accurately than the chemotherapeutic response alone.

¹⁸F-FDG PET SUVmax as an indicator of histopathologic response after neoadjuvant chemotherapy in extremity osteosarcoma

PURPOSE

This study evaluated the usefulness of the maximum standardized uptake value (SUVmax) as a measure of histologic response to neoadjuvant chemotherapy in patients with extremity osteosarcoma. The correlation between [(18) F]FDG PET SUVmax values and histologic response to preoperative chemotherapy was also assessed prospectively using PET/MRI.

METHODS

A total of 26 consecutive patients with high-grade osteosarcoma were prospectively enrolled. All patients underwent parallel PET and MRI scans before and after neoadjuvant chemotherapy. Using the PET and MRI images and pathologic mapping, we assessed the percentage necrosis by histology at the highest metabolic activity point in the tumors. This was defined as the minimum histologic response. The predictive values of SUVmax before (SUV1) and after (SUV2) chemotherapy and the SUV change ratio were determined. Correlations were also investigated among SUV2, minimum histologic response and histologic response.

RESULTS

Histologically, 13 patients were classified as good responders and 13 as poor responders. Patients with an SUV2 of >5 showed a poor histologic response. A significant correlation was found between SUV2 and histologic response (Spearman's rho -0.642; P < 0.001), and SUV2 and histologic response were both found to be significantly correlated with minimum histologic response (Spearman's rho -0.515 and 0.911; P = 0.007 and P < 0.001, respectively).

CONCLUSION

A SUVmax of more than 5 after neoadjuvant chemotherapy identified the majority of histologic nonresponders (sensitivity 61.3 %, PPV 88.9 %). Tumor necrosis at the point of maximum metabolic activity was found to be significantly correlated with the histologic response of entire resected specimen.

Some general considerations about the clinicopathologic aspects of soft tissue tumors in children and adolescents

Soft tissue tumors in children and adolescents are an important group of neoplasms, pseudoneoplasms, and tumefactive malformations with some distinctive clinicopathologic, genetic, syndromic, and therapeutic implications. In addition to the basic pathologic examination, there is the availability of diagnostic adjuncts in various settings based upon the histopathologic features that facilitate and/or corroborate a diagnosis. Immunohistochemistry, cytogenetics, molecular genetics, and an ever-increasing array of new technologies are available to address specific diagnostic questions and even potential therapeutic strategies. This review focuses upon some of the unique aspects of soft tissue tumors in children, including the classification, approach to the diagnosis, grading, clinical and pathologic staging, therapy-related changes, pathogenesis, and risk factors.

Guidelines for histopathological specimen examination and diagnostic reporting of primary bone tumours

This review is intended to provide histopathologists with guidelines for clinical assessment, specimen handling and diagnostic reporting of benign and malignant primary bone tumours. Information from radiology, surgical, oncology and other clinical colleagues involved in the diagnosis and treatment of primary bone tumours should be properly assessed before undertaking a structured approach to specimen handling and histological reporting. This ensures that the information needed for planning appropriate treatment of these complex tumours is provided. Consistency in diagnostic evaluation with respect to both terminology and report content facilitates liaison at multidisciplinary bone tumour meetings and collaboration between cancer units and networks, as well as providing a common database for audit of the clinical, radiological and pathological aspects of bone tumours.

Modern Diagnosis of Small Cell Malignancies of Children

Small cell malignancies of children constitute a continuing diagnostic challenge for surgical pathologists, although modern methods of ancillary diagnosis provide powerful tools that resolve most difficult cases. Current techniques range from identification of DNA alternations, including gene fusions, chromosome translocations, and genetic deletions, to recognition of characteristic patterns of protein expression, usually visualized with immunohistochemistry. In spite of these advances, recognition of key cellular and histologic features remains the keystone of diagnosis but requires adequately fixed and carefully stained histologic sections. Cytologic features now suffice for diagnosis if confirmed by appropriate testing. This article outlines key histologic features of pediatric small cell neoplasms and the algorithms that allow diagnostic confirmation and the initiation of appropriate therapy.

Runx2, p53, and pRB status as diagnostic parameters for deregulation of osteoblast growth and differentiation in a new pre-chemotherapeutic osteosarcoma cell line (OS1)

Osteosarcomas are the most prevalent primary bone tumors found in pediatric patients. To understand their molecular etiology, cell culture models are used to define disease mechanisms under controlled conditions. Many osteosarcoma cell lines (e.g., SAOS-2, U2OS, MG63) are derived from Caucasian patients. However, patients exhibit individual and ethnic differences in their responsiveness to irradiation and chemotherapy. This motivated the establishment of osteosarcoma cell lines (OS1, OS2, OS3) from three ethnically Chinese patients. OS1 cells, derived from a pre-chemotherapeutic tumor in the femur of a 6-year-old female, were examined for molecular markers characteristic for osteoblasts, stem cells, and cell cycle control by immunohistochemistry, reverse transcriptase-PCR, Western blotting and flow cytometry. OS1 have aberrant G-banded karyotypes, possibly reflecting chromosomal abnormalities related to p53 deficiency. OS1 had ossification profiles similar to human fetal osteoblasts rather than SAOS-2 which ossifies ab initio (P < 0.05). Absence of p53 correlates with increased Runx2 expression, while the slow proliferation of OS1 cells is perhaps attenuated by pRB retention. OS1 express mesenchymal stem cell markers (CD44, CD105) and differ in relative expression of CD29, CD63, and CD71 to SAOS-2. (P < 0.05). Cell cycle synchronization with nocodazole did not affect Runx2 and CDK1 levels but decreased cyclin-E and increased cyclin-A (P < 0.05). Xenotransplantion of OS1 in SCID mice yields spontaneous tumors that were larger and grew faster than SAOS-2 transplants. Hence, OS1 is a new osteosarcoma cell culture model derived from a pre-chemotherapeutic ethnic Chinese patient, for mechanistic studies and development of therapeutic strategies to counteract metastasis and deregulation of mesenchymal development.

Promises and challenges of positron emission tomography for assessment of sarcoma in daily clinical practice

A correct histological diagnosis, careful staging and detection of tumour response to treatment are all crucial in the management of sarcomas. Imaging is important in all of these stages. Sarcomas have distinct biological and treatment-related features posing challenges for imaging. For example, size measurements may not adequately reflect response rates. Techniques which can measure tissue function rather than generate merely anatomical data such as positron emission tomography (PET) are rapidly gaining interest. We discuss the importance of imaging in different stages of patient management, emphasising the unique characteristics of sarcoma. Furthermore, we discuss the potential of PET for the various indications, focussing on therapy evaluation.