Value of diffusion-weighted imaging for evaluating chemotherapy response in osteosarcoma: A meta-analysis

Imaging of pediatric bone tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper

Malignant primary bone tumors are uncommon in the pediatric population, accounting for 3%-5% of all pediatric malignancies. Osteosarcoma and Ewing sarcoma comprise 90% of malignant primary bone tumors in children and adolescents. This paper provides consensus-based recommendations for imaging in children with osteosarcoma and Ewing sarcoma at diagnosis, during therapy, and after therapy.

Non-invasive intravoxel incoherent motion MRI in prediction of histopathological response to neoadjuvant chemotherapy and survival outcome in osteosarcoma at the time of diagnosis

BACKGROUND

Early prediction of response to neoadjuvant chemotherapy (NACT) is important to aid personalized treatment in osteosarcoma. Diffusion-weighted Intravoxel Incoherent Motion (IVIM) MRI was used to evaluate the predictive value for response to NACT and survival outcome in osteosarcoma.

METHODS

Total fifty-five patients with biopsy-proven osteosarcoma were recruited prospectively, among them 35 patients were further analysed. Patients underwent 3 cycles of NACT (Cisplatin + Doxorubicin) followed by surgery and response adapted adjuvant chemotherapy. Treatment outcomes were histopathological response to NACT (good-response ≥ 50% necrosis and poor-response < 50% necrosis) and survival outcome (event-free survival (EFS) and overall survival (OS)). IVIM MRI was acquired at 1.5T at baseline (t0), after 1-cycle (t1) and after 3-cycles (t2) of NACT. Quantitative IVIM parameters (D, D*, f & D*.f) were estimated using advanced state-of-the-art spatial penalty based IVIM analysis method bi-exponential model with total-variation penalty function (BETV) at 3 time-points and histogram analysis was performed.

RESULTS

Good-responders: Poor-responders ratio was 13 (37%):22 (63%). EFS and OS were 31% and 69% with 16.27 and 25.9 months of median duration respectively. For predicting poor-response to NACT, IVIM parameters showed AUC = 0.87, Sensitivity = 86%, Specificity = 77% at t0, and AUC = 0.96, Sensitivity = 86%, Specificity = 100% at t1. Multivariate Cox regression analysis showed smaller tumour volume (HR = 1.002, p = 0.001) higher ADC-25^th-percentile (HR = 0.047, p = 0.005) & D-Mean (HR = 0.1, p = 0.023) and lower D*-Mean (HR = 1.052, p = 0.039) were independent predictors of longer EFS (log-rank p-values: 0.054, 0.0034, 0.0017, 0.0019 respectively) and non-metastatic disease (HR = 4.33, p < 10^-3), smaller tumour-volume (HR = 1.001, p = 0.042), lower D*-Mean (HR = 1.045, p = 0.056) and higher D*.f-skewness (HR = 0.544, p = 0.048) were independent predictors of longer OS (log-rank p-values: < 10^-3, 0.07, < 10^-3, 0.019 respectively).

CONCLUSION

IVIM parameters obtained with a 1.5T scanner along with novel BETV method and their histogram analysis indicating tumour heterogeneity were informative in characterizing NACT response and survival outcome in osteosarcoma.

Multiparametric MRI evaluation of bone sarcomas in children

Osteosarcoma and Ewing sarcoma are the most common bone sarcomas in children. Their clinical presentation is very variable depending on the age of the patient and tumor location. MRI is the modality of choice to assess these bone sarcomas and has an important function at diagnosis and also for monitoring recurrence or tumor response. Anatomic sequences include T1- and T2-weighted images and provide morphological assessment that is crucial to localize the tumor and describe anatomical boundaries. Multiparametric MRI provides functional information that helps in the assessment of tumor response to therapy by using different imaging sequences and biomarkers. This review manuscript illustrates the role of MRI in osteosarcoma and Ewing sarcoma in the pediatric population, with emphasis on a functional perspective, highlighting the use of diffusion-weighted imaging and dynamic contrast-enhanced MRI at diagnosis, and during and after treatment.

Correlation of histopathology and multi-modal magnetic resonance imaging in childhood osteosarcoma: Predicting tumor response to chemotherapy

Background

Osteosarcoma, which is the most common malignant pediatric bone cancer, remains dependent on an imprecise systemic treatment largely unchanged in 30 years. In this study, we correlated histopathology with magnetic resonance imaging (MRI), used the correlation to extract MRI-specific features representative of tumor necrosis, and subsequently developed a novel classification model for predicting tumor response to neoadjuvant chemotherapy in pediatric patients with osteosarcoma using multi-modal MRI. The model could ultimately serve as a testable biomarker for a high-risk malignancy without successful precision treatments.

Methods

Patients with newly diagnosed high-grade appendicular osteosarcoma were enrolled in a single-center observational study, wherein patients underwent pre-surgical evaluation using both conventional MRI (post-contrast T1-weighted with fat saturation, pre-contrast T1-weighted, and short inversion-time inversion recovery (STIR)) and advanced MRI (diffusion weighted (DW) and dynamic contrast enhanced (DCE)). A classification model was established based on a direct correlation between histopathology and MRI, which was achieved through histologic-MR image co-registration and subsequent extraction of MR image features for identifying histologic tumor necrosis. By operating on the MR image features, tumor necrosis was estimated from different combinations of MR images using a multi-feature fuzzy clustering technique together with a weighted majority ruling. Tumor necrosis calculated from MR images, for either an MRI plane of interest or whole tumor volume, was compared to pathologist-estimated necrosis and necrosis quantified from digitized histologic section images using a previously described deep learning classification method.

Results

15 patients were enrolled, of whom two withdrew, one became ineligible, and two were subjected to inadequate pre-surgical imaging. MRI sequences of n = 10 patients were subsequently used for classification model development. Different MR image features, depending on the modality of MRI, were shown to be significant in distinguishing necrosis from viable tumor. The scales at which MR image features optimally signified tumor necrosis were different as well depending on the MR image type. Conventional MRI was shown capable of differentiating necrosis from viable tumor with an accuracy averaging above 90%. Conventional MRI was equally effective as DWI in distinguishing necrotic from viable tumor regions. The accuracy of tumor necrosis prediction by conventional MRI improved to above 95% when DCE-MRI was added into consideration. Volume-based tumor necrosis estimations tended to be lower than those evaluated on an MRI plane of interest.

Conclusions

The study has shown a proof-of-principle model for interpreting chemotherapeutic response using multi-modal MRI for patients with high-grade osteosarcoma. The model will continue to be evaluated as MR image features indicative of tumor response are now computable for the disease prior to surgery.

Efficacy of Diffusion-Weighted Imaging in Neoadjuvant Chemotherapy for Osteosarcoma: A Systematic Review and Meta-Analysis

RATIONALE AND OBJECTIVES

Diffusion-weighted imaging (DWI) is a noninvasive imaging technique that reflects the diffusion movement of water molecules through apparent diffusion coefficient (ADC) values. The role of DWI in predicting the histological response to neoadjuvant chemotherapy in osteosarcoma is being increasingly researched, and a systematic review and meta-analysis of this topic is urgently required to help determine the potential diagnostic value of DWI.

MATERIALS AND METHODS

The present meta-analysis included 13 studies (303 patients). We divided the target population into good responders and poor responders based on tumor necrosis on histological biopsy (≥90%, good responders). The mean ADC values and ADC ratio were extracted and/or calculated for the two groups.

RESULTS

The mean difference in ADC values before and after neoadjuvant chemotherapy was significantly higher in good responders than in poor responders (mean difference, 0.33; 95% confidence interval [CI], 0.18-0.49; p< 0.0001), and significant heterogeneity was present among the 10 studies that reported these values (I² = 66%, p< 0.05). The ADC ratio was also significantly higher in good responders than in poor responders (mean difference, 28.34; 95% CI, 1.83-54.85; p = 0.04), and significant heterogeneity in ADC ratio was present among 7 studies (I² = 97%, p< 0.05).

CONCLUSION

The mean differences in ADC values and ADC ratios before and after neoadjuvant chemotherapy for osteosarcoma were significantly higher in good responders than in poor responders.

The role of diffusion-weighted MRI in assessment of response to chemotherapy in osteosarcoma

Background

The most effective treatment for osteosarcoma is neoadjuvant chemotherapy along with surgical resection of the tumor. The prognosis significantly correlates with the degree of tumor necrosis following preoperative chemotherapy. The tumor necrosis will result in loss of the cell membrane integrity and expansion of the extracellular diffusion space which can be detected as an increase in the mean ADC value. The aim of our work is to evaluate the use of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) value measurement for monitoring the therapeutic response after chemotherapy in osteosarcoma.

Results

This study included 25 cases of osteosarcoma: 15 males and 10 females. The age of the patients ranged from 7 to 46 years with mean age 22 years. All were assessed by magnetic resonance imaging (MRI) including DWI and the mean and minimum ADC values were calculated before and after chemotherapy. Follow-up DWI post-therapy revealed a rise in mean ADC value in 17 patients who considered having good response. The ADC value had been raised from 1.05 ± 0.4 × 10−3 mm2/s to 1.82 ± 0.45 × 10−3 mm2/s (P < 0.027) that is statistically moderately significant. In 8 patients, the post-therapy ADC value was similar to that of pre- or with a little change and they were considered having poor response. It showed changes from 1.29 ± 0.35 × 10−3 mm2/s to 1.32 ± 0.36 × 10−3 mm2/s (P > 0.05) that means no significant difference.

Conclusion

DWI and ADC value measurement play an important role in monitoring the therapeutic response after chemotherapy in osteosarcoma patients by comparing the mean ADC values before and after treatment.

Pediatric skeletal diffusion-weighted magnetic resonance imaging, part 2: current and emerging applications

Diffusion-weighted imaging (DWI) complements the more established T1, fluid-sensitive and gadolinium-enhanced magnetic resonance pulse sequences used to assess several pediatric skeletal pathologies. There is optimism that the technique might not just be complementary but could serve as an alternative to gadolinium and radiopharmaceuticals for several indications. As a non-contrast, free-breathing and noninvasive technique, DWI is especially valuable in children and is readily incorporated into existing MRI protocols. The indications for skeletal DWI in children include distinguishing between benign and malignant skeletal processes, initial assessment and treatment response assessment for osseous sarcomas, and assessment of inflammatory arthropathies and femoral head ischemia, among others. A notable challenge of diffusion MRI is the dynamic nature of the growing pediatric skeleton. It is important to consider the child's age when placing DWI findings in context with potential marrow pathology. This review article summarizes the current and evolving applications of DWI for assessing the pediatric skeleton, rounding off the discussion with evolving directions for further research in this realm.

Imaging biomarkers for evaluating tumor response: RECIST and beyond

Response Evaluation Criteria in Solid Tumors (RECIST) is the gold standard for assessment of treatment response in solid tumors. Morphologic change of tumor size evaluated by RECIST is often correlated with survival length and has been considered as a surrogate endpoint of therapeutic efficacy. However, the detection of morphologic change alone may not be sufficient for assessing response to new anti-cancer medication in all solid tumors. During the past fifteen years, several molecular-targeted therapies and immunotherapies have emerged in cancer treatment which work by disrupting signaling pathways and inhibited cell growth. Tumor necrosis or lack of tumor progression is associated with a good therapeutic response even in the absence of tumor shrinkage. Therefore, the use of unmodified RECIST criteria to estimate morphological changes of tumor alone may not be sufficient to estimate tumor response for these new anti-cancer drugs. Several studies have reported the low reliability of RECIST in evaluating treatment response in different tumors such as hepatocellular carcinoma, lung cancer, prostate cancer, brain glioma, bone metastasis, and lymphoma. There is an increased need for new medical imaging biomarkers, considering the changes in tumor viability, metabolic activity, and attenuation, which are related to early tumor response. Promising imaging techniques, beyond RECIST, include dynamic contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI), diffusion-weight imaging (DWI), magnetic resonance spectroscopy (MRS), and ¹⁸ F-fluorodeoxyglucose (FDG) positron emission tomography (PET). This review outlines the current RECIST with their limitations and the new emerging concepts of imaging biomarkers in oncology.

Alkaline phosphatase, lactic dehidrogenase, inflammatory variables and apparent diffusion coefficients from MRI for prediction of chemotherapy response in osteosarcoma. A cross sectional study

BACKGROUND

This present study aimed to assess if clinical, laboratory and MRI were an accurate benchmark in assessing the effectiveness of neoadjuvant chemotherapy in osteosarcoma patients.

METHODS

This was an observational analytic study with a cross-sectional design. We correlated among clinical, laboratory and magnetic resonance imaging (MRI) data before and after neoadjuvant chemotherapy; and percentage of tumor necroses from osteosarcoma patients during the period between January 2017-July 2019.

RESULTS

Of the 58 patients included in this study, 38 were male and 20 were female aged 5 - 67 years (mean: 16-year-old. 37(63.8%) patients underwent neoadjuvant chemotherapy with CAI regimens and 13 (36.2%) with CA regiments. The tumors were classified as stage IIB in 43 (74.1%) patients and stage III in 15 (25.9%) patients. Wilcoxon test showed significant differences between alkaline phosphatase (ALP), erythrocyte sedimentation rate (ESR), and neutrophil to lymphocyte ratio (NLR) before and after neoadjuvant chemotherapy in the poor-response group. We found no significant difference between lactic dehydrogenase (LDH) and lymphocyte-to-monocyte ratio (LMR) before and after neoadjuvant chemotherapy in the good-response group. MRI revealed decreased tumor volume in patients in the good-response to chemotherapy.

CONCLUSION

We demonstrated that ALP level was statistically significant in the poor-response group. We also found that LDH value before neoadjuvant chemotherapy had a strong correlation with degree of necrosis and could be used as a predictive indicator. MRI plays an important role in evaluating tumor volumes and preoperative radiological changes to predict histological necrosis.

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.

Multiparametric MRI with diffusion-weighted imaging in predicting response to chemotherapy in cases of osteosarcoma and Ewing's sarcoma

OBJECTIVE

To evaluate the multiparametric MRI in predicting chemotherapy response in pathologically proven cases of osteosarcoma and Ewing's sarcoma. Correlation between the tumor size changes and internal breakdown using RECIST 1.1, modified RECIST, quantitative apparent diffusion coefficient (ADC) and tumor volume as well as dynamic contrast-enhanced MRI (DCE-MRI).

METHODS

The study included 104 patients pathologically proved osteosarcoma (53) and Ewing`s sarcoma (51) underwent MRI examinations; before and after chemotherapy. All patients were assessed using the RECIST 1.1 criteria, m-RECIST, quantitative ADC, and tumor volume evaluation. 21 patients underwent DCE-MRI curve type with quantitative parameters. Correlation between the different evaluations was carried out. Results were correlated with the post-operative pathology in 42 patients who underwent surgery and for statistical evaluation, Those patients were classified into responders (≥90% necrosis) and non-responders (<90% necrosis).

RESULTS

The initial mean ADC of 104 patients of osteosarcoma and Ewing's sarcoma (0.90 ± 0.29) and (0.71 ± 0.16) respectively, differed significantly from that after treatment (1.62 ± 0.46) and (1.6 ± 0.39) respectively with (p<0.001).ADC variations (ADC%) in the non-progressive group were higher than those of the progressive group (128.3 ± 63.49 vs 36.34 ± 78.7) % with (p<0.001).ADC values and ADC variations were inversely correlated with morphologic changes, regardless of the effectiveness of chemotherapy expressed as changes in tumor size based on (RECIST 1.1, RECIST, and 3D volume). Linear regression analysis revealed a Pearson correlation coefficient of r=-0.427, -0.498 and -0.408, respectively with (p<0.001).An increase in the ADC value was not always associated with a reduction in tumor volume. The disease control rate (defined as the percentage of CR+PR+SD patients) was 89.4% and 93.9% according to RECIST 1.1 and m-RECIST respectively.42 out of the 104 patients had postsurgical histological evaluation as regards the chemotherapeutic response divided into two groups. ADC values showed a statistically significant difference between Group A and Group B being more evident with minimum ADC% (p<0.001).

CONCLUSION

Quantitative diffusion-weighted imaging with ADC mapping and ADC % after chemotherapy allows a detailed analysis of the treatment response in osteosarcoma and Ewing's sarcoma. The therapeutic response can be underestimated using RECIST 1.1, so the modified RECIST should be also considered.

ADVANCES IN KNOWLEDGE

Quantitative ADC especially ADC% provided an accurate non-invasive tool in the assessment of post-therapeutic cases of osteosarcoma and Ewing's sarcoma.

Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study

BACKGROUND

Response evaluation of neoadjuvant chemotherapy (NACT) in patients with osteosarcoma is significant for the termination of ineffective treatment, the development of postoperative chemotherapy regimens, and the prediction of prognosis. However, histological response and tumour necrosis rate can currently be evaluated only in resected specimens after NACT. A preoperatively accurate, noninvasive, and reproducible method of response assessment to NACT is required. In this study, the value of multi-parametric magnetic resonance imaging (MRI) combined with machine learning for assessment of tumour necrosis after NACT for osteosarcoma was investigated.

METHODS

Twelve patients with primary osteosarcoma of limbs underwent NACT and received MRI examination before surgery. Postoperative tumour specimens were made corresponding to the transverse image of MRI. One hundred and two tissue samples were obtained and pathologically divided into tumour survival areas (non-cartilaginous and cartilaginous tumour viable areas) and tumour-nonviable areas (non-cartilaginous tumour necrosis areas, post-necrotic tumour collagen areas, and tumour necrotic cystic/haemorrhagic and secondary aneurismal bone cyst areas). The MRI parameters, including standardised apparent diffusion coefficient (ADC) values, signal intensity values of T2-weighted imaging (T2WI) and subtract-enhanced T1-weighted imaging (ST1WI) were used to train machine learning models based on the random forest algorithm. Three classification tasks of distinguishing tumour survival, non-cartilaginous tumour survival, and cartilaginous tumour survival from tumour nonviable were evaluated by five-fold cross-validation.

RESULTS

For distinguishing non-cartilaginous tumour survival from tumour nonviable, the classifier constructed with ADC achieved an AUC of 0.93, while the classifier with multi-parametric MRI improved to 0.97 (P = 0.0933). For distinguishing tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.83, while the classifier with multi-parametric MRI improved to 0.90 (P < 0.05). For distinguishing cartilaginous tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.61, while the classifier with multi-parametric MRI parameters improved to 0.81(P < 0.05).

CONCLUSIONS

The combination of multi-parametric MRI and machine learning significantly improved the discriminating ability of viable cartilaginous tumour components. Our study suggests that this method may provide an objective and accurate basis for NACT response evaluation in osteosarcoma.

Diffusion weighted magnetic resonance imaging (DW-MRI) as a non-invasive, tissue cellularity marker to monitor cancer treatment response

Background

Diffusion weighted magnetic resonance imaging (DW-MRI) holds great potential for monitoring treatment response in cancer patients shortly after initiation of radiotherapy. It is hypothesized that a decrease in cellular density of irradiated cancerous tissue will lead to an increase in quantitative apparent diffusion coefficient (ADC) values. DW-MRI can therefore serve as a non-invasive marker of cell death and apoptosis in response to treatment. In the present study, we aimed to investigate the applicability of DW-MRI in preclinical models to monitor radiation-induced treatment response. In addition, we compared DW-MRI with ex vivo measures of cell density, cell death and apoptosis.

Methods

DW-MRI was tested in two different syngeneic mouse models, a colorectal cancer (CT26) and a breast cancer (4 T1). ADC values were compared with quantitative determinations of apoptosis and cell death by flow cytometry. Furthermore, ADC-values were also compared to histological measurement of cell density on tumor sections.

Results

We found a significant correlation between ADC-values and apoptotic state in the CT26 model (P = 0.0031). A strong correlation between the two measurements of ADC-value and apoptotic state was found in both models, which were also present when comparing ADC-values to cell densities.

Conclusions

Our findings demonstrate that DW-MRI can be used for non-invasive monitoring of radiation-induced changes in cell state during cancer therapy. ADC values reflect ex vivo cell density and correlates well with apoptotic state, and can hereby be described as a marker for the cell state after therapy and used as a non-invasive response marker.

The value of diffusion weighted imaging and apparent diffusion coefficient in primary Osteogenic and Ewing sarcomas for the monitoring of response to treatment: Initial experience

PURPOSE

To assess the value of using Apparent Diffusion Coefficient (ADC) mapping in Diffusion Weighted Imaging (DWI) when monitoring treatment response in pediatric Osteogenic and Ewing sarcomas and to correlate with level of necrosis on post-surgical excision pathology.

METHOD

This retrospective study includes 7 Osteosarcoma and 8 Ewing sarcoma patients. Pre-treatment and post-treatment focal MRIs were evaluated for ADC values, tumor volumes and variability of both measurements. We also compared the measurement between Ewing and Osteosarcoma groups, as well as between good (=/>90 % necrosis post-excision) and poor (<90 % necrosis post-excision) responders.

RESULTS

All measurements except Maximum ADC (p = 0.20) showed a statistically significant difference when comparing them before and after treatment. When we segregated our population according to pathologic complete response, there was no difference in ADC measurements, volumetric measurements or either variability between good (8 Patients) and poor responders (7 Patients). When comparing the before-after changes in our measurement between the Ewing sarcoma and Osteosarcoma cases, there was no significant difference in the change between pre and post treatment (Δ) Mean or Maximum ADC, or in Δtumor-volume when measured on STIR or SPIR T1 post-contrast sequences. Only the ΔMinimum-ADC showed a statistically significant difference (p < 0.02) in this group.

CONCLUSIONS

ADC can potentially reflect cellular changes associated with chemotherapy use, reflecting a response to treatment. However, quantitative use of those parameters to dictate a change in management, treatment regimen or chemotherapy dose in order to target a good response (>/ = 90 % necrosis post-excision) needs further investigation.

Whole-body magnetic resonance imaging in pediatric oncology - recommendations by the Oncology Task Force of the ESPR

The purpose of this recommendation of the Oncology Task Force of the European Society of Paediatric Radiology (ESPR) is to indicate reasonable applications of whole-body MRI in children with cancer and to address useful protocols to optimize workflow and diagnostic performance. Whole-body MRI as a radiation-free modality has been increasingly performed over the last two decades, and newer applications, as in screening of children with germ-line mutation cancer-related gene defects, are now widely accepted. We aim to provide a comprehensive outline of the diagnostic value for use in daily practice. Based on the results of our task force session in 2018 and the revision in 2019 during the ESPR meeting, we summarized our group's experiences in whole-body MRI. The lack of large evidence by clinical studies is challenging when focusing on a balanced view regarding the impact of whole-body MRI in pediatric oncology. Therefore, the final version of this recommendation was supported by the members of Oncology Task Force.

The current status of MRI in the pre-operative assessment of intramedullary conventional appendicular osteosarcoma

Osteosarcoma is the commonest primary malignant bone tumour in children and adolescents, the majority of cases being conventional intra-medullary high-grade tumours affecting the appendicular skeleton. Treatment is typically with a combination of neo-adjuvant chemotherapy, tumour resection with limb reconstruction and post-operative chemotherapy. The current article reviews the role of magnetic resonance imaging (MRI) in the pre-operative assessment of high-grade central conventional osteosarcoma.