Combination of 18F-FDG PET/CT and Diffusion-Weighted MR Imaging as a Predictor of Histologic Response to Neoadjuvant Chemotherapy: Preliminary Results in Osteosarcoma

A bibliometric analysis based on hotspots and frontier trends of positron emission tomography/computed tomography utility in bone and soft tissue sarcoma

Purpose

This study aimed to analyze articles on the diagnosis and treatment of bone and soft tissue sarcoma using positron emission tomography (PET)/computed tomography (CT) published in the last 13 years. The objective was to conduct a bibliometric analysis and identify the research hotspots and emerging trends.

Methods

Web of Science was used to search for articles on PET/CT diagnosis and treatment of bone and soft tissue sarcoma published from January 2010 to June 2023. CiteSpace was utilized to import data for bibliometric analysis.

Results

In total, 425 relevant publications were identified. Publications have maintained a relatively stable growth rate for the past 13 years. The USA has the highest number of published articles (139) and the highest centrality (0.35). The UDICE-French Research Universities group is the most influential institution. BYUN BH is a prominent contributor to this field. The Journal of Clinical Oncology has the highest impact factor in the field.

Conclusion

The clinical application of PET/CT is currently a research hotspot. Upcoming areas of study concentrate on the merging of PET/CT with advanced machine learning and/or alternative imaging methods, novel imaging substances, and the fusion of diagnosis and therapy. The use of PET/CT has progressively become a crucial element in the identification and management of sarcomas. To confirm its efficacy, there is a need for extensive, multicenter, prospective studies.

Relative Wash-In Rate in Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a New Prognostic Biomarker for Event-Free Survival in 82 Patients with Osteosarcoma: A Multicenter Study

BACKGROUND

The decreased perfusion of osteosarcoma in dynamic contrast-enhanced (DCE) MRI, reflecting a good histological response to neoadjuvant chemotherapy, has been described.

PURPOSE

In this study, we aim to explore the potential of the relative wash-in rate as a prognostic factor for event-free survival (EFS).

METHODS

Skeletal high-grade osteosarcoma patients, treated in two tertiary referral centers between 2005 and 2022, were retrospectively included. The relative wash-in rate (rWIR) was determined with DCE-MRI before, after, or during the second cycle of chemotherapy (pre-resection). A previously determined cut-off was used to categorize patients, where rWIR < 2.3 was considered poor and rWIR ≥ 2.3 a good radiological response. EFS was defined as the time from resection to the first event: local recurrence, new metastases, or tumor-related death. EFS was estimated using Kaplan-Meier's methodology. Multivariate Cox proportional hazard model was used to estimate the effect of histological response and rWIR on EFS, adjusted for traditional prognostic factors.

RESULTS

Eighty-two patients (median age: 17 years; IQR: 14-28) were included. The median follow-up duration was 11.8 years (95% CI: 11.0-12.7). During follow-up, 33 events occurred. Poor histological response was not significantly associated with EFS (HR: 1.8; 95% CI: 0.9-3.8), whereas a poor radiological response was associated with a worse EFS (HR: 2.4; 95% CI: 1.1-5.0). In a subpopulation without initial metastases, the binary assessment of rWIR approached statistical significance (HR: 2.3; 95% CI: 1.0-5.2), whereas its continuous evaluation demonstrated a significant association between higher rWIR and improved EFS (HR: 0.7; 95% CI: 0.5-0.9), underlining the effect of response to chemotherapy. The 2- and 5-year EFS for patients with a rWIR ≥ 2.3 were 85% and 75% versus 55% and 50% for patients with a rWIR < 2.3.

CONCLUSION

The predicted poor chemo response with MRI (rWIR < 2.3) is associated with shorter EFS even when adjusted for known clinical covariates and shows similar results to histological response evaluation. rWIR is a potential tool for future response-based individualized healthcare in osteosarcoma patients before surgical resection.

Molecular Imaging with PET-CT and PET-MRI in Pediatric Musculoskeletal Diseases

Molecular imaging has emerged as an integral part of oncologic imaging. Given the physiologic changes that precede anatomic changes, molecular imaging can enable early detection of disease and monitoring of response. [18F] Fluorodeoxyglucose (FDG) Positron emission tomography (PET) is the predominant molecular imaging modality used in oncologic assessment and can be performed using PET/CT or PET/MR. In pediatric patients, PET/MRI imaging is generally preferred due to low radiation exposure and PET/MRI is particularly advantageous for imaging musculoskeletal (MSK) diseases, as MRI provides superior characterization of tissue changes as compared to CT. In this article, we provide an overview of the typical role of PET CT/MRI in assessment of some common pediatric malignancies and benign MSK diseases with case examples. We also discuss the relative advantages of PET/MRI compared to PET/CT, and review published data with a primary focus on the use of PET/MR.

Comparative Analysis of Skip Metastasis in Pediatric Osteosarcoma: Clinical Features and Outcomes

BACKGROUND

Skip metastasis (SM) is a synchronous regional bone metastasis. Using new imaging modalities, the detection of SM is easier and possibly more common. We reviewed patients with SM and compared their characteristics and outcomes to other patients with osteosarcoma treated at our center.

METHODS

We reviewed retrospectively children (<18 years) with newly diagnosed osteosarcoma who presented from June 2006 to March 2022. Patients' characteristics, treatment modalities, and outcomes were analyzed. All cases were discussed in a multidisciplinary clinic that included 2 experienced radiologists.

RESULTS

We identified 155 patients with osteosarcoma, among which 13 (8.3%) patients had SM detected by MRI. Patients with SM had a median age at diagnosis of 11.2 years (range 7 to 17). Three patients had lung metastasis at diagnosis. Bone scan was positive for the SM in 8 patients (62%). All patients underwent primary tumor resection after neoadjuvant chemotherapy (amputation in 5, limb salvage surgery in 8). Five had postchemotherapy necrosis ≥90% in primary tumor. Seven patients relapsed/progressed (1 local and 6 in the lung), all relapsed patients died of disease. Compared to the rest of the patients, those with SM had similar clinical features to patients without SM; outcomes were similar with no significant differences in event-free survival and overall survival ( P =0.7 and 0.3, respectively).

CONCLUSION

In this study, we observed a percentage of patients with SM comparable to previous reports. Patients with SM exhibited clinical features akin to the rest of our patients. Thorough evaluation of imaging studies and multidisciplinary care, coupled with meticulous surgical planning, are crucial for achieving a cure, which remained unjeopardized in our patients with SM.

Evaluation of response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI: development and external validation of a model

OBJECTIVE

To identify which dynamic contrast-enhanced (DCE-)MRI features best predict histological response to neoadjuvant chemotherapy in patients with an osteosarcoma.

METHODS

Patients with osteosarcoma who underwent DCE-MRI before and after neoadjuvant chemotherapy prior to resection were retrospectively included at two different centers. Data from the center with the larger cohort (training cohort) was used to identify which method for region-of-interest selection (whole slab or focal area method) and which change in DCE-MRI features (time to enhancement, wash-in rate, maximum relative enhancement and area under the curve) gave the most accurate prediction of histological response. Models were created using logistic regression and cross-validated. The most accurate model was then externally validated using data from the other center (test cohort).

RESULTS

Fifty-five (27 poor response) and 30 (19 poor response) patients were included in training and test cohorts, respectively. Intraclass correlation coefficient of relative DCE-MRI features ranged 0.81-0.97 with the whole slab and 0.57-0.85 with the focal area segmentation method. Poor histological response was best predicted with the whole slab segmentation method using a single feature threshold, relative wash-in rate <2.3. Mean accuracy was 0.85 (95%CI: 0.75-0.95), and area under the receiver operating characteristic curve (AUC-index) was 0.93 (95%CI: 0.86-1.00). In external validation, accuracy and AUC-index were 0.80 and 0.80.

CONCLUSION

In this study, a relative wash-in rate of <2.3 determined with the whole slab segmentation method predicted histological response to neoadjuvant chemotherapy in osteosarcoma. Consistent performance was observed in an external test cohort.

Imaging Assessment of the Efficacy of Chemotherapy in Primary Malignant Bone Tumors: Recent Advances in Qualitative and Quantitative Magnetic Resonance Imaging and Radiomics

Recent studies have shown that MRI demonstrates promising results for evaluating the chemotherapy efficacy in bone sarcomas. This article reviews current methods for evaluating the efficacy of malignant bone tumors and the application of MRI in this area, and emphasizes the advantages and limitations of each modality. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

The expression of Ki-67 and Glypican -3 in hepatocellular carcinoma was evaluated by comparing DWI and 18F-FDG PET/CT

Objective

The value of DWI and 18F-FDG PET/CT in evaluating the expression of Ki-67 and GPC-3 in HCC was compared.

Materials and methods

Ninety-four patients with primary HCC confirmed by pathology were retrospectively divided into high- and low-Ki-67-expression groups and positive- and negative- GPC-3 groups. The ADC and SUVmax values of the lesions in both groups were measured. ROC curves were used to evaluate the identification efficiency of parameters with significant differences for each group of lesions, and AUCwas calculated. The combined ADC and SUVmax values were analyzed by binary logistic regression. The Delong test was used to compare the AUC values of the combined and single parameters. Pearson (in line with normal distribution) or Spearman (in line with abnormal distribution) correlation analysis was used to analyze the correlation.

Results

The ADC value of the high-Ki-67-expression group was lower than that of the low-Ki-67-expression group (P<0.05), and the SUVmax value of the high-expression group was higher than that of the low-expression group (P<0.05). The ADC value of the positive-GPC-3 group was lower than that of the negative group (P<0.0.tive group (P<0.05). The combined ADC and SUVmax values in the GPC-3 group were better than those of a single parameter (P<0.05). There was a strong negative correlation between the SUVmax value and ADC value in the Ki-67 group (R=-0.578, P<0.001) and a weak negative correlation between the SUVmax value and ADC value in the GPC-3 group (R=-0.279, P=0.006). The SUVmax value was strongly positively correlated with the Ki-67 expression index (R=0.733, P<0.001), while the ADC value was strongly negatively correlated with the Ki-67 expression index (R=-0.687, P<0.001).

Conclusion

DWI and 18F-FDG PET/CT can be used to evaluate the expression of Ki-67 and GPC-3 in HCC, and there is a certain correlation between the ADC value and SUVmax. Combined DWI and 18F-FDG PET/CT is superior to a single technique in evaluating the expression of GPC-3 in HCC patients. However, the combined model did not benefit the Ki-67 group.

Exploration of Imaging Biomarkers for Metabolically-Targeted Osteosarcoma Therapy in a Murine Xenograft Model

Background: Osteosarcoma (OS) is an aggressive pediatric cancer with unmet therapeutic needs. Glutaminase 1 (GLS1) inhibition, alone and in combination with metformin, disrupts the bioenergetic demands of tumor progression and metastasis, showing promise for clinical translation. Materials and Methods: Three positron emission tomography (PET) clinical imaging agents, [18F]fluoro-2-deoxy-2-D-glucose ([18F]FDG), 3'-[18F]fluoro-3'-deoxythymidine ([18F]FLT), and (2S, 4R)-4-[18F]fluoroglutamine ([18F]GLN), were evaluated in the MG63.3 human OS xenograft mouse model, as companion imaging biomarkers after treatment for 7 d with a selective GLS1 inhibitor (CB-839, telaglenastat) and metformin, alone and in combination. Imaging and biodistribution data were collected from tumors and reference tissues before and after treatment. Results: Drug treatment altered tumor uptake of all three PET agents. Relative [18F]FDG uptake decreased significantly after telaglenastat treatment, but not within control and metformin-only groups. [18F]FLT tumor uptake appears to be negatively affected by tumor size. Evidence of a flare effect was seen with [18F]FLT imaging after treatment. Telaglenastat had a broad influence on [18F]GLN uptake in tumor and normal tissues. Conclusions: Image-based tumor volume quantification is recommended for this paratibial tumor model. The performance of [18F]FLT and [18F]GLN was affected by tumor size. [18F]FDG may be useful in detecting telaglenastat's impact on glycolysis. Exploration of kinetic tracer uptake protocols is needed to define clinically relevant patterns of [18F]GLN uptake in patients receiving telaglenastat.

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.

18F-FDG PET/CT in the Management of Osteosarcoma

Osteosarcoma is the most common type of primary malignant bone tumor. ¹⁸F-FDG PET/CT is useful for staging, detecting recurrence, monitoring response to neoadjuvant chemotherapy, and predicting prognosis. Here, we review the clinical aspects of osteosarcoma management and assess the role of ¹⁸F-FDG PET/CT, in particular with regard to pediatric and young adult patients.

Methodological considerations on segmenting rhabdomyosarcoma with diffusion-weighted imaging-What can we do better?

PURPOSE

Diffusion-weighted MRI is a promising technique to monitor response to treatment in pediatric rhabdomyosarcoma. However, its validation in clinical practice remains challenging. This study aims to investigate how the tumor segmentation strategy can affect the apparent diffusion coefficient (ADC) measured in pediatric rhabdomyosarcoma.

MATERIALS AND METHODS

A literature review was performed in PubMed using search terms relating to MRI and sarcomas to identify commonly applied segmentation strategies. Seventy-six articles were included, and their presented segmentation methods were evaluated. Commonly reported segmentation strategies were then evaluated on diffusion-weighted imaging of five pediatric rhabdomyosarcoma patients to assess their impact on ADC.

RESULTS

We found that studies applied different segmentation strategies to define the shape of the region of interest (ROI)(outline 60%, circular ROI 27%), to define the segmentation volume (2D 44%, multislice 9%, 3D 21%), and to define the segmentation area (excludes edge 7%, excludes other region 19%, specific area 27%, whole tumor 48%). In addition, details of the segmentation strategy are often unreported. When implementing and comparing these strategies on in-house data, we found that excluding necrotic, cystic, and hemorrhagic areas from segmentations resulted in on average 5.6% lower mean ADC. Additionally, the slice location used in 2D segmentation methods could affect ADC by as much as 66%.

CONCLUSION

Diffusion-weighted MRI studies in pediatric sarcoma currently employ a variety of segmentation methods. Our study shows that different segmentation strategies can result in vastly different ADC measurements, highlighting the importance to further investigate and standardize segmentation.

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-25th-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.

Chemotherapy response evaluation using diffusion weighted MRI in Ewing Sarcoma: A single center experience

BACKGROUND

Non-invasive biomarkers for early chemotherapeutic response in Ewing sarcoma family of tumors (ESFT) are useful for optimizing existing treatment protocol.

PURPOSE

To assess the role of diffusion-weighted magnetic resonance imaging (MRI) in the early evaluation of chemotherapeutic response in ESFT.

MATERIAL AND METHODS

A total of 28 patients (mean age = 17.2 ± 5.6 years) with biopsy proven ESFT were analyzed prospectively. Patients underwent MRI acquisition on a 1.5-T scanner at three time points: before starting neoadjuvant chemotherapy (baseline), after first cycle chemotherapy (early time point), and after completion of chemotherapy (last time point). RECIST 1.1 criteria was used to evaluate the response to chemotherapy and patients were categorized as responders (complete and partial response) and non-responders (stable and progressive disease). Tumor diameter, absolute apparent diffusion coefficient (ADC), and normalized ADC (nADC) values in the tumor were measured. Baseline parameters and relative percentage change of parameters after first cycle chemotherapy were assessed for early detection of chemotherapy response.

RESULTS

The responder:non-responder ratio was 21:7. At baseline, ADC ([0.864 ± 0.266 vs. 0.977 ± 0.246]) × 10^-3mm²/s; P = 0.205) and nADC ([0.740 ± 0.254 vs. 0.925 ± 0.262] × 10^-3mm²/s; P = 0.033) among responders was lower than the non-responders and predicted response to chemotherapy with AUCs of 0.6 and 0.735, respectively. At the early time point, tumor diameter (27% ± 14% vs. 4.6% ± 10%; P = 0.002) showed a higher reduction and ADC (75% ± 44% vs. 52% ± 72%; P = 0.039) and nADC (81% ± 44% vs. 48% ± 67%; P = 0.008) showed a higher increase in mean values among responders than the non-responders and identified chemotherapy response with AUC of 0.890, 0.723, and 0.756, respectively.

CONCLUSION

Baseline nADC and its change after the first cycle of chemotherapy can be used as non-invasive surrogate markers of early chemotherapeutic response in patients with ESFT.

An evaluation of the response to neoadjuvant chemotherapy for osteosarcoma of extremities: PERCIST versus RECIST 1.1 criteria after long-term follow-up

OBJECTIVE

The aim of this study was to compare the recent Positron emission tomography (PET) Response Criteria in Solid Tumors (PERCIST) and Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria for evaluating the response of osteosarcoma to neoadjuvant chemotherapy of the extremities.

METHODS

We retrospectively reviewed patients with osteosarcoma of the extremities who received neoadjuvant chemotherapy and then surgical resection at Peking University People's Hospital. Fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and magnetic resonance imaging (MRI) were performed prior to chemotherapy and before surgical resection. Therapeutic response was assessed separately by the PERCIST and RECIST 1.1 criteria. The association between the data acquired by the PERCIST and RECIST 1.1 criteria was then analyzed by Wilcoxon's signed-rank test. The association between the PERCIST criteria and the pathological necrosis rate was analyzed by Fisher's exact test. Finally, the impact of a range of clinicopathological factors on overall survival (OS) and event-free survival (EFS) was analyzed by Cox proportional hazards regression.

RESULTS

We recruited 68 patients with a median follow-up of 74 months (range 45-102 months). The evaluations resulting from the RECIST 1.1 and PERCIST criteria were significantly different (p = 0.000). Only two responders were identified according to the RECIST 1.1 criteria. However, 34 responders were identified by the PERCIST criteria. Data arising from the PERCIST criteria were in accordance with the pathological necrosis rate. Survival analysis showed that metastasis at diagnosis, poor pathological response, and disease progression (according to the RECIST 1.1 or PERCIST criteria) were all associated with a poor prognosis (p < 0.05).

CONCLUSION

Our data indicate that the PERCIST criteria are significantly more sensitive than RECIST 1.1 criteria to identify more responders when evaluating the response of osteosarcoma to neoadjuvant chemotherapy.

Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram

OBJECTIVES

To implement a pipeline to automatically segment the ROI and to use a nomogram integrating the MRI-based radiomics score and clinical variables to predict responses to neoadjuvant chemotherapy (NAC) in osteosarcoma patients.

METHODS

A total of 144 osteosarcoma patients treated with NAC were separated into training (n = 101) and test (n = 43) groups. After normalisation, ROIs for the preoperative MRI were segmented by a deep learning segmentation model trained with nnU-Net by using two independent manual segmentations as labels. Radiomics features were extracted using automatically segmented ROIs. Feature selection was performed in the training dataset by five-fold cross-validation. The clinical, radiomics, and clinical-radiomics models were built using multiple machine learning methods with the same training dataset and validated with the same test dataset. The segmentation model was evaluated by the Dice coefficient. AUC and decision curve analysis (DCA) were employed to illustrate the model performance and clinical utility.

RESULTS

36/144 (25.0%) patients were pathological good responders (pGRs) to NAC, while 108/144 (75.0%) were non-pGRs. The segmentation model achieved a Dice coefficient of 0.869 on the test dataset. The clinical and radiomics models reached AUCs of 0.636 with a 95% confidence interval (CI) of 0.427-0.860 and 0.759 (95% CI, 0.589-0.937), respectively, in the test dataset. The clinical-radiomics nomogram demonstrated good discrimination, with an AUC of 0.793 (95% CI, 0.610-0.975), and accuracy of 79.1%. The DCA suggested the clinical utility of the nomogram.

CONCLUSION

The automatic nomogram could be applied to aid radiologists in identifying pGRs to NAC.

KEY POINTS

• The nnU-Net trained by manual labels enables the use of an automatic segmentation tool for ROI delineation of osteosarcoma. • A pipeline using automatic lesion segmentation and followed by a radiomics classifier could aid the evaluation of NAC response of osteosarcoma. • A predictive nomogram composed of clinical variables and MRI-based radiomics score provides support for individualised treatment planning.

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.

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.

One-stop local and whole-body staging of children with cancer

Accurate staging and re-staging of cancer in children is crucial for patient management. Currently, children with a newly diagnosed cancer must undergo a series of imaging tests, which are stressful, time-consuming, partially redundant, expensive, and can require repetitive anesthesia. New approaches for pediatric cancer staging can evaluate the primary tumor and metastases in a single session. However, traditional one-stop imaging tests, such as CT and positron emission tomography (PET)/CT, are associated with considerable radiation exposure. This is particularly concerning for children because they are more sensitive to ionizing radiation than adults and they live long enough to experience secondary cancers later in life. In this review article we discuss child-tailored imaging tests for tumor detection and therapy response assessment - tests that can be obtained with substantially reduced radiation exposure compared to traditional CT and PET/CT scans. This includes diffusion-weighted imaging (DWI)/MRI and integrated [F-18]2-fluoro-2-deoxyglucose (18F-FDG) PET/MRI scans. While several investigators have compared the value of DWI/MRI and 18F-FDG PET/MRI for staging pediatric cancer, the value of these novel imaging technologies for cancer therapy monitoring has received surprisingly little attention. In this article, we share our experiences and review existing literature on this subject.

Introducing a New Biomarker Named R2*-BOLD-MRI Parameter to Assess Treatment Response in Osteosarcoma

BACKGROUND

While histologic response to neoadjuvant chemotherapy (NChT) is the major prognostic factor for osteosarcoma treatment, evaluating that response is difficult.

PURPOSE

To evaluate the feasibility of the blood oxygen level-dependent (BOLD) technique to assess the response to NChT.

STUDY TYPE

Prospective.

POPULATION

Twelve patients with osteosarcoma undergoing NChT.

FIELD STRENGTH/SEQUENCE

3 T; T2*-weighted BOLD, dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) (b values of 0, 400, and 1400 seconds/mm² ) sequences.

ASSESSMENT

Examination was performed before treatment (first), after each cycle of treatment (second and third). At each time point, spin dephasing rates (R2*) from BOLD magnetic resonance imaging (MRI), parameters from DCE-MRI (volume transfer constant [K^trans ], reflux rate [k_ep ], volume fraction of the extravascular extracellular matrix [v_e ], and blood plasma volume [v_p ]), and the apparent diffusion coefficient (ADC) from DW-MRI were measured.

STATISTICAL TESTS

Wilcoxon's signed rank test, Spearman's correlation coefficient (ρ) were used. A P-value of <0.05 was considered statistically significant.

RESULTS

The difference and relative difference of the R2* values between the first/third MRIs in the extraosseous portion were statistically significant. Only the differences in the k_ep values between the first/second and between the first/third MRIs in the extraosseous portion were significant. The differences in the ADCs in the extraosseous and osseous portions were not statistically significant (P = 0.151, P = 0.733 each in extraosseous portion and P = 0.569, P = 0.129 each in osseous portion). The relative difference in R2* values in the extraosseous portion between the first/third MRI (ρ = 0.706) was significantly better correlated with the pathologic grade than those of k_ep and ADC over the same period (ρ = 0.286 and ρ = -0.091, respectively).

DATA CONCLUSION

The R2* from the BOLD MRI technique could be a useful biomarker for evaluating treatment response in osteosarcoma treated with NchT.

LEVEL OF EVIDENCE

5 TECHNICAL EFFICACY: Stage 2.

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.

PET-CT for the diagnosis and treatment of primary musculoskeletal tumors in Chinese patients - experience from 255 patients in a single center

OBJECTIVE

The current study was carried out to assess the value of positron emission tomography (PET)/CT on the diagnosis and staging of primary musculoskeletal tumors.

METHODS

PET-CT test results and histopathological study reports of all the patients with primary musculoskeletal tumors in our department from January 2006 to July 2015 were retrospectively reviewed. Maximum standardized uptake value (SUVmax) in these PET-CT reports were recorded and analyzed respectively for each type of sarcoma.

RESULTS

A total of 255 patients were included in the final analysis. Sensitivity of SUVmax based diagnosis was 96.6% for primary malignant osseous sarcomas and 91.2% for soft tissue sarcomas. SUVmax of high-grade osseous sarcomas (average 8.4 ± 5.5) was significantly higher (p < 0.001) than low-grade osseous sarcomas (average 3.9 ± 1.8); based on current case series, SUVmax of high-grade soft tissue sarcomas (7.5 ± 5.1) was not significantly different (p = 0.229) from that of low-grade soft tissue sarcomas (5.3 ± 3.7). Significant decrease of SUVmax value after chemotherapy was associated with favorable prognosis in patients with osteosarcoma.

CONCLUSION

Results of the current study indicate that, the SUVmax based application of PET-CT can be a valuable supplementary method to histopathological tests regarding the diagnosis and staging of primary musculoskeletal sarcomas.

ADVANCES IN KNOWLEDGE

SUVmax based application of PET-CT is a highly sensitive method in diagnosis of primary osseous and soft tissue sarcomas in Chinese patients.

KSNM60 in Clinical Nuclear Oncology

Since the foundation of the Korean Society of Nuclear Medicine in 1961, clinical nuclear oncology has been a major part of clinical nuclear medicine in Korea. There are several important events for the development of clinical nuclear oncology in Korea. First, a scintillating type gamma camera was adopted in 1969, which enabled to perform modern oncological gamma imaging. Second, Tc-99 m generator was imported to Korea since 1979, which promoted the wide clinical use of gamma camera imaging by using various kinds of Tc-99 m labeled radiopharmaceuticals. Third, a gamma camera with single photon emission tomography (SPECT) capability was first installed in 1980, which has been used for various kinds of tumor SPECT imaging. Fourth, in 1994, clinical positron emission tomography (PET) scanner and cyclotron with a production of F-18 fluorodeoxyglucose were first installed in Korea. Fifth, Korean Board of Nuclear Medicine was established in 1995, which contributed in the education and manpower training of dedicated nuclear medicine physicians in Korea. Finally, an integrated PET/CT scanner was first installed in 2002. Since that, PET/CT imaging has been a major imaging tool in clinical nuclear oncology in Korea. In this review, a brief history of clinical nuclear oncology in Korea is described.

PET/MRI Improves Management of Children with Cancer

Integrated PET/MRI has shown significant clinical value for staging and restaging of children with cancer by providing functional and anatomic tumor evaluation with a 1-stop imaging test and with up to 80% reduced radiation exposure compared with 18F-FDG PET/CT. This article reviews clinical applications of 18F-FDG PET/MRI that are relevant for pediatric oncology, with particular attention to the value of PET/MRI for patient management. Early adopters from 4 different institutions share their insights about specific advantages of PET/MRI technology for the assessment of young children with cancer. We discuss how whole-body PET/MRI can be of value in the evaluation of certain anatomic regions, such as soft tissues and bone marrow, as well as specific PET/MRI interpretation hallmarks in pediatric patients. We highlight how whole-body PET/MRI can improve the clinical management of children with lymphoma, sarcoma, and neurofibromatosis, by reducing the number of radiologic examinations needed (and consequently the radiation exposure), without losing diagnostic accuracy. We examine how PET/MRI can help in differentiating malignant tumors versus infectious or inflammatory diseases. Future research directions toward the use of PET/MRI for treatment evaluation of patients undergoing immunotherapy and assessment of different theranostic agents are also briefly explored. Lessons learned from applications in children might also be extended to evaluations of adult patients.

PET with 18F-Fluorodeoxyglucose/Computed Tomography in the Management of Pediatric Sarcoma

The role for PET with fludeoxyglucose F 18 (¹⁸F-FDG PET)/computed tomography (CT) in the management of pediatric sarcomas continues to be controversial. The literature supports a role for PET/CT in the staging and surveillance of certain specific pediatric sarcoma subtypes; however, the data are less clear regarding whether PET/CT can be used as a biomarker for prognostication. Despite the interest in using this imaging modality in the management of pediatric sarcomas, most studies are limited by retrospective design and small sample size. Additional data are necessary to fully understand how best to use ¹⁸F-FDG PET/CT in pediatric sarcoma management.

MRI-based radiomics signature for pretreatment prediction of pathological response to neoadjuvant chemotherapy in osteosarcoma: a multicenter study

OBJECTIVE

To develop and validate a radiomics signature based on magnetic resonance imaging (MRI) from multicenter datasets for preoperative prediction of pathologic response to neoadjuvant chemotherapy (NAC) in patients with osteosarcoma.

METHODS

We retrospectively enrolled 102 patients with histologically confirmed osteosarcoma who received chemotherapy before treatment from 4 hospitals (68 in the primary cohort and 34 in the external validation cohort). Quantitative imaging features were extracted from contrast-enhanced fat-suppressed T1-weighted images (CE FS T1WI). Four classification methods, i.e., the least absolute shrinkage and selection operator logistic regression (LASSO-LR), support vector machine (SVM), Gaussian process (GP), and Naive Bayes (NB) algorithm, were compared for feature selection and radiomics signature construction. The predictive performance of the radiomics signatures was assessed with the area under receiver operating characteristics curve (AUC), calibration curve, and decision curve analysis (DCA).

RESULTS

Thirteen radiomics features selected based on the LASSO-LR classifier were adopted to construct the radiomics signature, which was significantly associated with the pathologic response. The prediction model achieved the best performance between good and poor responders with an AUC of 0.882 (95% CI, 0.837-0.918) in the primary cohort. Calibration curves showed good agreement. Similarly, findings were validated in the external validation cohort with good performance (AUC, 0.842 [95% CI, 0.793-0.883]) and good calibration. DCA analysis confirmed the clinical utility of the selected radiomics signature.

CONCLUSION

The constructed CE FS T1WI-radiomics signature with excellent performance could provide a potential tool to predict pathologic response to NAC in patients with osteosarcoma.

KEY POINTS

• The radiomics signature based on multicenter contrast-enhanced MRI was useful to predict response to NAC. • The prediction model obtained with the LASSO-LR classifier achieved the best performance. • The baseline clinical characteristics were not associated with response to NAC.

Combination of 99mTc-Labeled PSMA-SPECT/CT and Diffusion-Weighted MRI in the Prediction of Early Response After Carbon Ion Therapy in Prostate Cancer: A Non-Randomized Prospective Pilot Study

Purpose

The purpose of this study was to assess the potential of ^99mTc-labeled PSMA-SPECT/CT and diffusion-weighted image (DWI) for predicting treatment response after carbon ion radiotherapy (CIRT) in prostate cancer.

Patients and Methods

We prospectively registered 26 patients with localized prostate cancer treated with CIRT. All patients underwent ^99mTc-labeled PSMA-SPECT/CT and multiparametric magnetic resonance imaging (MRI) before and after CIRT. The tumor/background ratio (TBR) and mean apparent diffusion coefficient (ADC_mean) were measured on the tumor and the percentage changes before and after therapy (ΔTBR and ΔADC_mean) were calculated. Patients were divided into two groups: good response and poor response according to clinical follow-up.

Results

The median follow up time was 38.3months. The TBR was significantly decreased (p=0.001), while the ADC_mean was significantly increased compared with the pretreatment value (p<0.001). The ΔTBR and ΔADC_mean were negatively correlated with each other (p = 0.002). On ROC curve analysis for predicting treatment response, the area under the ROC curve (AUC) of ΔTBR (0.867) for predicting good response was higher than that of ΔADC_mean (0.819). The AUC of combined with ΔTBR and ΔADC_mean (0.895) was higher than that of either ΔADC_mean or ΔTBR alone. The combined use of ΔTBR and ΔADC_mean showed 91.4% sensitivity and 95.2% specificity.

Conclusion

Our preliminary data indicate that the changes of TBR and ADC_mean maybe an early bio-marker for predicting prognosis after CIRT in localized prostate cancer patients. In addition, the ΔTBR seems to be a more powerful prognostic factor than ΔADC_mean in prostate cancer treated with CIRT.

Does the SUVmax of FDG-PET/CT Correlate with the ADC Values of DWI in Musculoskeletal Malignancies?

Purpose

To evaluate the correlation of maximum standardized uptake values (SUV_max) of ¹⁸F-Fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) with the apparent diffusion coefficient (ADC) of diffusion weighted imaging (DWI) in musculoskeletal malignancies.

Methods

Institutional ethics committee approved this retrospective study. Twenty-seven patients (mean age: 44.85 ± 24.07; 17 men and 10 women) with a total of 29 musculoskeletal tumors underwent both FDG-PET/CT and DWI between January 2017 and March 2020. Region-of-interest (ROI)-based maximal standardized uptake values (SUV_max) of the tumors were measured on FDG-PET/CT images. Two radiologists measured lesions' mean and minimum apparent diffusion coefficient (ADC_mean and ADC_min) using five distinct ROIs on DWI images. Pearson correlation analysis was used to assess the correlation between SUV_max and ADC values.

Results

There were 18 soft tissue tumors (62.1%) and 11 bone tumors (37.9%) with a mean maximum diameter of 9.4 ± 6.2 cm. The mean SUV_max, ADC_mean and ADC_min of the whole lesions were 12.93 ± 9.63, 0.85 ± 0.28 × 10^-3mm²/s and 0.61 ± 0.27 × 10^-3mm²/s, respectively. SUV_max had a weak correlation with tumor maximum diameter (r = 0.378, p = 0.043), whereas ADC_mean and ADC_min had none. There was strong inverse correlation between SUV_max and both ADC_mean (r = -0.616, p < 0.001) and ADC_min (r = -0.638, p < 0.001).

Conclusion

In musculoskeletal tumors, quantitative markers of FDG uptake and diffusion restriction strongly correlate.

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.

Personalising sarcoma care using quantitative multimodality imaging for response assessment

Over the last decades, technological developments in the field of radiology have resulted in a widespread use of imaging for personalising medicine in oncology, including patients with a sarcoma. New scanner hardware, imaging protocols, image reconstruction algorithms, radiotracers, and contrast media, enabled the assessment of the physical and biological properties of tumours associated with response to treatment. In this context, medical imaging has the potential to select sarcoma patients who do not benefit from (neo-)adjuvant treatment and facilitate treatment adaptation. Due to the biological heterogeneity in sarcomas, the challenge at hand is to acquire a practicable set of imaging features for specific sarcoma subtypes, allowing response assessment. This review provides a comprehensive overview of available clinical data on imaging-based response monitoring in sarcoma patients and future research directions. Eventually, it is expected that imaging-based response monitoring will help to achieve successful modification of (neo)adjuvant treatments and improve clinical care for these patients.

Metabolic response as assessed by 18 F-fluorodeoxyglucose positron emission tomography-computed tomography does not predict outcome in patients with intermediate- or high-risk rhabdomyosarcoma: A report from the Children's Oncology Group Soft Tissue Sarcoma Committee

BACKGROUND

Strategies to optimize management in rhabdomyosarcoma (RMS) include risk stratification to assign therapy aiming to minimize treatment morbidity yet improve outcomes. This analysis evaluated the relationship between complete metabolic response (CMR) as assessed by ¹⁸ F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG-PET) imaging and event-free survival (EFS) in intermediate-risk (IR) and high-risk (HR) RMS patients.

METHODS

FDG-PET imaging characteristics, including assessment of CMR and maximum standard uptake values (SUVmax) of the primary tumor, were evaluated by central review. Institutional reports of SUVmax were used when SUVmax values could not be determined by central review. One hundred and thirty IR and 105 HR patients had FDG-PET scans submitted for central review or had SUVmax data available from institutional report at any time point. A Cox proportional hazards regression model was used to evaluate the relationship between these parameters and EFS.

RESULTS

SUVmax at study entry did not correlate with EFS for IR (p = 0.32) or HR (p = 0.86) patients. Compared to patients who did not achieve a CMR, EFS was not superior for IR patients who achieved a CMR at weeks 4 (p = 0.66) or 15 (p = 0.46), nor for HR patients who achieved CMR at week 6 (p = 0.75) or 19 (p = 0.28). Change in SUVmax at week 4 (p = 0.21) or 15 (p = 0.91) for IR patients or at week 6 (p = 0.75) or 19 (p = 0.61) for HR patients did not correlate with EFS.

CONCLUSION

Based on these data, FDG-PET does not appear to predict EFS in IR or HR-RMS. It remains to be determined whether FDG-PET has a role in predicting survival outcomes in other RMS subpopulations.

Diffusion Kurtosis Imaging as a Prognostic Marker in Osteosarcoma Patients with Preoperative Chemotherapy

Background

The accurate prediction of prognosis is key to prompt therapy adjustment. The purpose of our study was to investigate the efficacy of diffusion kurtosis imaging (DKI) in predicting progression-free survival (PFS) and overall survival (OS) in osteosarcoma patients with preoperative chemotherapy.

Methods

Thirty patients who underwent DKI before and after chemotherapy, followed by tumor resection, were retrospectively enrolled. The patients were grouped into good responders (GRs) and poor responders (PRs). The Kaplan-Meier and log-rank test were used for survival analysis. The association between the DKI parameters and OS and PFS was performed by univariate and multivariate Cox proportional hazards models.

Results

Significantly worse OS and PFS were associated with a lower mean diffusivity (MD) after chemotherapy (HR, 5.8; 95% CI, 1.5-23.1; P = 0.012 and HR, 3.5; 95% CI, 1.2-10.1: P = 0.028, respectively) and a higher mean kurtosis (MK) after chemotherapy (HR, 0.3; 95% CI, 0.1-0.9; P = 0.041 and HR, 0.3; 95% CI, 0.1-0.8; P = 0.049, respectively). Likewise, shorter OS and PFS were also significantly associated with a change rate in MD (CR MD) of less than 13.53% (HR, 8.6; 95% CI, 1.8-41.8; P = 0.007 and HR, 2.9; 95% CI, 1.0-8.2; P = 0.045, respectively). Compared to GRs, PRs had an approximately 9- and 4-fold increased risk of death (HR, 9.4; 95% CI, 1.2-75; P = 0.034) and progression (HR, 4.2; 95% CI, 1.2-15; P = 0.026), respectively.

Conclusions

DKI has a potential to be a prognostic tool in osteosarcoma. Low MK and high MD after chemotherapy or high CR MD indicates favorite outcome, while prospective studies with large sample sizes are warranted.

Evaluation of 18F-FDG PET and DWI Datasets for Predicting Therapy Response of Soft-Tissue Sarcomas Under Neoadjuvant Isolated Limb Perfusion

Our purpose was to evaluate and compare the clinical utility of simultaneously obtained quantitative ¹⁸F-FDG PET and diffusion-weighted MRI datasets for predicting the histopathologic response of soft-tissue sarcoma (STS) to neoadjuvant isolated limb perfusion (ILP). Methods: In total, 37 patients with a confirmed STS of the extremities underwent ¹⁸F-FDG PET/MRI before and after ILP with melphalan and tumor necrosis factor-α. For each patient, the maximum tumor size, metabolic activity (SUV), and diffusion restriction (apparent diffusion coefficient, ADC) were determined in pre- and posttherapeutic examinations, and percentage changes during treatment were calculated. Mann-Whitney U testing and receiver-operating-characteristic analysis were used to compare the results of the different quantitative parameters to predict the histopathologic response to therapy. Results from histopathologic analysis after tumor resection served as the reference standard, and patients were defined as responders or nonresponders based on the grading scale by Salzer-Kuntschik. Results: Histopathologic analysis categorized 22 (59%) patients as responders (grades I-III) and 15 (41%) as nonresponders (grades IV-VI). Under treatment, tumors in responders showed a mean reduction in size (-9.7%) and metabolic activity (SUV_peak, -51.9%; SUV_mean, -43.8%), as well as an increase of the ADC values (ADC_min, +29.4%; ADC_mean, +32.8%). The percentage changes in nonresponders were -6.2% in tumor size, -17.3% in SUV_peak, -13.9% in SUV_mean, +15.3% in ADC_min, and +14.6% in ADC_mean Changes in SUV and ADC_mean significantly differed between responders and nonresponders (<0.01), whereas differences in tumor size and ADC_min did not (>0.05). The corresponding AUCs were 0.63 for tumor size, 0.87 for SUV_peak, 0.82 for SUV_mean, 0.63 for ADC_min, 0.84 for ADC_mean, and 0.89 for ratio of ADC_mean to SUV_peak Conclusion: PET- and MRI-derived quantitative parameters (SUV and ADC_mean) and their combination performed well in predicting the histopathologic therapy response of STS to neoadjuvant ILP. Therefore, integrated PET/MRI could serve as a valuable tool for pretherapeutic assessment as well as monitoring of neoadjuvant treatment strategies of STS.

Therapy Response Assessment of Pediatric Tumors with Whole-Body Diffusion-weighted MRI and FDG PET/MRI

Background Whole-body diffusion-weighted (DW) MRI can help detect cancer with high sensitivity. However, the assessment of therapy response often requires information about tumor metabolism, which is measured with fluorine 18 fluorodeoxyglucose (FDG) PET. Purpose To compare tumor therapy response with whole-body DW MRI and FDG PET/MRI in children and young adults. Materials and Methods In this prospective, nonrandomized multicenter study, 56 children and young adults (31 male and 25 female participants; mean age, 15 years ± 4 [standard deviation]; age range, 6-22 years) with lymphoma or sarcoma underwent 112 simultaneous whole-body DW MRI and FDG PET/MRI between June 2015 and December 2018 before and after induction chemotherapy (ClinicalTrials.gov identifier: NCT01542879). The authors measured minimum tumor apparent diffusion coefficients (ADCs) and maximum standardized uptake value (SUV) of up to six target lesions and assessed therapy response after induction chemotherapy according to the Lugano classification or PET Response Criteria in Solid Tumors. The authors evaluated agreements between whole-body DW MRI- and FDG PET/MRI-based response classifications with Krippendorff α statistics. Differences in minimum ADC and maximum SUV between responders and nonresponders and comparison of timing for discordant and concordant response assessments after induction chemotherapy were evaluated with the Wilcoxon test. Results Good agreement existed between treatment response assessments after induction chemotherapy with whole-body DW MRI and FDG PET/MRI (α = 0.88). Clinical response prediction according to maximum SUV (area under the receiver operating characteristic curve = 100%; 95% confidence interval [CI]: 99%, 100%) and minimum ADC (area under the receiver operating characteristic curve = 98%; 95% CI: 94%, 100%) were similar (P = .37). Sensitivity and specificity were 96% (54 of 56 participants; 95% CI: 86%, 99%) and 100% (56 of 56 participants; 95% CI: 54%, 100%), respectively, for DW MRI and 100% (56 of 56 participants; 95% CI: 93%, 100%) and 100% (56 of 56 participants; 95% CI: 54%, 100%) for FDG PET/MRI. In eight of 56 patients who underwent imaging after induction chemotherapy in the early posttreatment phase, chemotherapy-induced changes in tumor metabolism preceded changes in proton diffusion (P = .002). Conclusion Whole-body diffusion-weighted MRI showed significant agreement with fluorine 18 fluorodeoxyglucose PET/MRI for treatment response assessment in children and young adults. © RSNA, 2020 Online supplemental material is available for this article.

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.

Prediction of Poor Responders to Neoadjuvant Chemotherapy in Patients with Osteosarcoma: Additive Value of Diffusion-Weighted MRI including Volumetric Analysis to Standard MRI at 3T

OBJECTIVE

To evaluate the added value of diffusion weighted image (DWI) including volumetric analysis to standard magnetic resonance imaging (MRI) for predicting poor responders to neoadjuvant chemotherapy in patients with osteosarcoma at 3-Tesla.

METHODS

3-Tesla Standard MRI and DWI in 17 patients were reviewed by two independent readers. Standard MRI was reviewed using a five-level-confidence score. Two-dimensional (2D) apparent diffusion coefficient (ADC)mean and 2D ADCminimum were measured from a single-section region of interest. An ADC histogram derived from whole-tumor volume was generated including 3D ADCmean, 3D ADCskewness, and 3D ADCkurtosis. The Mann-Whitney-U test, receiver operating characteristic curve with area under the curve (AUC) analysis, and multivariate logistic regression analysis were performed.

RESULTS

There were 13 poor responders and 4 good responders. Statistical differences were found in posttreatment and percent change of both 2D ADCmean and 2D ADCminimum, posttreatment 3D ADCmean, and posttreatment 3D ADCskewness between two groups. The best predictors of poor responders were posttreatment 2D ADCmean and posttreatment 3D ADCskewness. Sensitivity and specificity of the 1st model (standard MRI alone), 2nd model (standard MRI+posttreatment 2D ADCmean), and 3rd model (standard MRI+posttreatment 2D ADCmean+posttreatment 3D ADCskewness) were 85% and 25%, 85% and 75%, and 85% and 100% for reader 1 and 77% and 25%, 77% and 50%, and 85% and 100% for reader 2, respectively. The AUC of the 1st, 2nd, and 3rd models were 0.548, 0.798, and 0.923 for reader 1 and 0.510, 0.635, and 0.923 for reader 2, respectively.

CONCLUSION

The addition of DWI including volumetric analysis to standard MRI improves the diagnostic accuracy for predicting poor responders to neoadjuvant chemotherapy in patients with osteosarcoma at 3-Tesla.

Monitoring Response to Neoadjuvant Chemotherapy of Primary Osteosarcoma Using Diffusion Kurtosis Magnetic Resonance Imaging: Initial Findings

Objective

To determine whether diffusion kurtosis imaging (DKI) is effective in monitoring tumor response to neoadjuvant chemotherapy in patients with osteosarcoma.

Materials and Methods

Twenty-nine osteosarcoma patients (20 men and 9 women; mean age, 17.6 ± 7.8 years) who had undergone magnetic resonance imaging (MRI) and DKI before and after neoadjuvant chemotherapy were included. Tumor volume, apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), and change ratio (ΔX) between pre- and post-treatment were calculated. Based on histologic response, the patients were divided into those with good response (≥ 90% necrosis, n = 12) and those with poor response (< 90% necrosis, n = 17). Several MRI parameters between the groups were compared using Student's t test. The correlation between image indexes and tumor necrosis was determined using Pearson's correlation, and diagnostic performance was compared using receiver operating characteristic curves.

Results

In good responders, MD_post, ADC_post, and MK_post values were significantly higher than in poor responders (p < 0.001, p < 0.001, and p = 0.042, respectively). The ΔMD and ΔADC were also significantly higher in good responders than in poor responders (p < 0.001 and p = 0.01, respectively). However, no significant difference was observed in ΔMK (p = 0.092). MD_post and ΔMD showed high correlations with tumor necrosis rate (r = 0.669 and r = 0.622, respectively), and MD_post had higher diagnostic performance than ADC_post (p = 0.037) and MK_post (p = 0.011). Similarly, ΔMD also showed higher diagnostic performance than ΔADC (p = 0.033) and ΔMK (p = 0.037).

Conclusion

MD is a promising biomarker for monitoring tumor response to preoperative chemotherapy in patients with osteosarcoma.

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.

Role of 18F-fluorodeoxyglucose positron emission tomography/computed tomography and magnetic resonance imaging in prediction of response to neoadjuvant chemotherapy in pediatric osteosarcoma

The aim of our study was to evaluate the role of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) in prediction of response to neoadjuvant chemotherapy (NAC) in pediatric osteosarcoma (OS) patients compared to percentage of tumor necrosis after surgical excision of the tumor. Forty-six pediatric OS patients treated with neoadjuvant chemotherapy and surgery were underwent PET/CT and MRI before, after 3 cycles, and after the completion of neoadjuvant chemotherapy. Imaging parameters include maximum standardized uptake value (SUVmax1, 2, and 3), tumor liver ratio (TLR 1, 2, and 3), and MRI tumor volume (MRTV 1, 2, and 3) at initial assessment before starting NAC, after finishing three cycles and after finishing 6 cycles before tumor excision, respectively. Cutoff values of the PET/CT and MRI parameters were determined using receiver operating characteristic (ROC) curve analysis and percentage of tumor necrosis of postsurgical specimen. Fourteen patients were good responders (30.4%), with more than 90% tumor necrosis, while 31 patients were poor responders (67.4%). The results of one patient were missed. We noticed that higher sensitivity for detecting poor responders was detected by SUVmax3/1, TLR3/1, and MRTV2/1 ratio cutoff values, while higher specificity was detected by TRL2 and SUVmax3 cutoff values. ROC curve analysis of MRTV2/1 and MRTV3/1 ratio was fair in predicting poor responders. PET/CT parameters are capable of predicting histological response to NAC in OS patients with overall sensitivity and specificity higher than MRI parameters.

Applications of PET-MRI in musculoskeletal disease

New integrated PET-MRI systems potentially provide a complete imaging modality for diagnosis and evaluation of musculoskeletal disease. MRI is able to provide excellent high-resolution morphologic information with multiple contrast mechanisms that has made it the imaging modality of choice in evaluation of many musculoskeletal disorders. PET offers incomparable abilities to provide quantitative information about molecular and physiologic changes that often precede structural and biochemical changes. In combination, hybrid PET-MRI can enhance imaging of musculoskeletal disorders through early detection of disease as well as improved diagnostic sensitivity and specificity. The purpose of this article is to review emerging applications of PET-MRI in musculoskeletal disease. Both clinical applications of malignant musculoskeletal disease as well as new opportunities to incorporate the molecular capabilities of nuclear imaging into studies of nononcologic musculoskeletal disease are discussed. Lastly, we discuss some of the technical considerations and challenges of PET-MRI as they specifically relate to musculoskeletal disease.

LEVEL OF EVIDENCE

5 TECHNICAL EFFICACY: Stage 3 J. Magn. Reson. Imaging 2018;48:27-47.

Comparison of 3T diffusion-weighted MRI and 18F-FDG PET/CT in musculoskeletal tumours: quantitative analysis of apparent diffusion coefficients and standardized uptake values

OBJECTIVE

To determine whether the apparent diffusion coefficient (ADC) on 3T MR imaging including diffusion-weighted MR imaging (DWI) correlate with the standardized uptake value (SUV) on 18F-FDG PET/CT in musculoskeletal tumours.

METHODS

This retrospective cohort study included 57 patients (36 males, 21 females, mean age 54 years, range 12-90 years) with pathologically confirmed soft tissue (n = 32) and bone (n = 25) tumours who underwent 3T MR imaging including DWI and whole-body 18F-FDG PET/CT before treatment. 14 patients had follow-up MR imaging and 18F-FDG PET/CT after treatment. The minimum (ADC_min) and mean (ADC_mean) ADCs of musculoskeletal tumour, ADC of normal skeletal muscle (ADC_mus), SUV_max and SUV_mean of musculoskeletal tumour were obtained. Correlation between ADCs and SUVs was assessed using Pearson correlation coefficients (r). ADC_min and SUV_max were compared between pretreatment and posttreatment by t-test.

RESULTS

There was inverse correlation between SUV_max and the ratio ADC_min/ADC_mus (r = - 0.505 to - 0.495, p ≤ 0.001) and between SUV_mean and the ratio ADC_mean/ADC_mus (r = - 0.501 to - 0.493, p = 0.001). After treatment ADC was significantly increased whereas SUV was significantly decreased (p = 0.001). There was significant correlation in percent change between the initial and follow-up values of ADC_min and SUV_max (r = 0.750 to 0.773, p ≤ 0.005). The ADC_min was increased by 163% and SUV_max was decreased by 61% in 11 patients with treatment response.

CONCLUSION

ADC at 3T MR DWI and SUV at 18F-FDG PET/CT have an inverse correlation in musculoskeletal tumours.

ADVANCES IN KNOWLEDGE

Our study showed that ADC at 3T DWI and SUV at 18F-FDG PET/CT had an inverse correlation in musculoskeletal tumours.

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.

MR Imaging of Pediatric Musculoskeletal Tumors:: Recent Advances and Clinical Applications

Pediatric musculoskeletal tumors comprise approximately 10% of childhood neoplasms, and MR imaging has been used as the imaging evaluation standard for these tumors. The role of MR imaging in these cases includes identification of tumor origin, tissue characterization, and definition of tumor extent and relationship to adjacent structures as well as therapeutic response in posttreatment surveillance. Technical advances have enabled quantitative evaluation of biochemical changes in tumors. This article reviews recent updates to MR imaging of pediatric musculoskeletal tumors, focusing on advanced MR imaging techniques and providing information on the relevant physics of these techniques, clinical applications, and pitfalls.

Pediatric Musculoskeletal Imaging: The Indications for and Applications of PET/Computed Tomography

The use of PET/computed tomography (CT) for the evaluation and management of children, adolescents, and young adults continues to expand. The principal tracer used is 18F-fluorodeoxyglucose and the principal indication is oncology, particularly musculoskeletal neoplasms. The purpose of this article is to review the common applications of PET/CT for imaging of musculoskeletal issues in pediatrics and to introduce the use of PET/CT for nononcologic issues, such as infectious/inflammatory disorders, and review the use of 18F-sodium fluoride in trauma and sports-related injuries.

Radioiodination, diagnostic nuclear imaging and bioevaluation of olmesartan as a tracer for cardiac imaging

The present work has been oriented to prepare radioiodinated olmesartan for a potential cardiac imaging. Olmesartan has been labeled using 125I or 131I with N-bromosuccinimide (NBS) as an oxidizing agent. Many factors like amount of N-bromosuccinimide, amount of substrate, pH, reaction temperature and reaction time, have been systematically studied to optimize high yield of [125I]iodoolmesartan. The biological distribution indicates the suitability of [125I]iodoolmesartan as a novel tracer to image heart.

Clinical PET/MRI: 2018 Update

OBJECTIVE

The purpose of this article is to provide an update on clinical PET/MRI, including current and developing clinical indications and technical developments.

CONCLUSION

PET/MRI is evolving rapidly, transitioning from a predominant research focus to exciting clinical practice. Key technical obstacles have been overcome, and further technical advances promise to herald significant advancements in image quality. Further optimization of protocols to address challenges posed by this hybrid modality will ensure the long-term success of PET/MRI.