Evaluation of tumour necrosis during chemotherapy with diffusion-weighted MR imaging: preliminary results in osteosarcomas

Magnetic Resonance Imaging Biomarkers of Bone and Soft Tissue Tumors

Magnetic resonance imaging (MRI) is essential in the management of musculoskeletal (MSK) tumors. This review delves into the diverse MRI modalities, focusing on anatomical, functional, and metabolic sequences that provide essential biomarkers for tumor detection, characterization, disease extent determination, and assessment of treatment response. MRI's multimodal capabilities offer a range of biomarkers that enhance MSK tumor evaluation, aiding in better patient management.

Pitfalls of Diffusion-Weighted Imaging: Clinical Utility of T2 Shine-through and T2 Black-out for Musculoskeletal Diseases

Diffusion-weighted imaging (DWI) with an apparent diffusion coefficient (ADC) value is a relatively new magnetic resonance imaging (MRI) sequence that provides functional information on the lesion by measuring the microscopic movement of water molecules. While numerous studies have evaluated the promising role of DWI in musculoskeletal radiology, most have focused on tumorous diseases related to cellularity. This review article aims to summarize DWI-acquisition techniques, considering pitfalls such as T2 shine-through and T2 black-out, and their usefulness in interpreting musculoskeletal diseases with imaging. DWI is based on the Brownian motion of water molecules within the tissue, achieved by applying diffusion-sensitizing gradients. Regardless of the cellularity of the lesion, several pitfalls must be considered when interpreting DWI with ADC values in musculoskeletal radiology. This review discusses the application of DWI in musculoskeletal diseases, including tumor and tumor mimickers, as well as non-tumorous diseases, with a focus on lesions demonstrating T2 shine-through and T2 black-out effects. Understanding these pitfalls of DWI can provide clinically useful information, increase diagnostic accuracy, and improve patient management when added to conventional MRI in musculoskeletal diseases.

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.

Expression and Clinical Significance of High-Mobility Group AT-hook 2 (HMGA2) in Osteosarcoma

Objective

Although high‐mobility group AT‐hook 2 (HMGA2) has been shown to have crucial roles in the pathogenesis and metastasis of various malignancies, its expression and significance in osteosarcoma remain unknown. Here we evaluate the expression, clinical prognostic value, and overall function of HMGA2 in osteosarcoma.

Methods

Sixty‐nine osteosarcoma patient specimens within a tissue microarray (TMA) were analyzed by immunohistochemistry for HMGA2 expression. Demographics and clinicopathological information including age, gender, tumor location, metastasis, recurrence, chemotherapy response, follow‐up time, and disease status were also collected. After validation of expression, we determined whether there was a correlation between HMGA2 expression and patient clinicopathology. HMGA2 expression was also evaluated in osteosarcoma cell lines and patient tissues by Western blot, we analyzed the expression of HMGA2 in the human osteosarcoma cell lines MG63, 143B, U2OS, Saos‐2, MNNG/HOS, and KHOS. HMGA2‐specific siRNA and clonogenic assays were then used to determine the effect of HMGA2 inhibition on osteosarcoma cell proliferation, growth, and chemosensitivity.

Results

HMGA2 expression was elevated in the osteosarcoma patient specimens and human osteosarcoma cell lines. HMGA2 was differentially expressed in human osteosarcoma cell lines. Specifically, a relatively high expression of HMGA2 was present in KHOS, MNNG/HOS, 143B and a relatively low expression was in MG63, U2OS as well as Saos‐2. HMGA2 expression is correlated with metastasis and shorter overall survival. High HMGA2 expression is an independent predictor of poor osteosarcoma prognosis. There was no significant correlation between HMGA2 expression and the age, gender, or tumor site of the patient. HMGA2 expression is predominantly within the nucleus. The expression of HMGA2 also directly correlated to neoadjuvant chemoresistance. There was a significant reduction of HMGA2 expression in the siRNA transfection group. After the use of siRNA, the proliferation of osteosarcoma cells is decreased and the chemosensitivity of osteosarcoma cells is significantly increased.

Conclusion

Our study supports HMGA2 as a potential prognostic biomarker and therapeutic target in osteosarcoma.

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.

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.

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.

[Pediatric bone marrow alterations]

The age-dependent development of the bone marrow follows a constant pattern and has an impact on the localization and morphology of various bone marrow processes. Physiological, reactive and benign bone marrow alterations must be differentiated from inflammatory or malignant infiltrations. In many cases, a specific age distribution pattern and typical morphological characteristics in magnetic resonance imaging (MRI) enable a diagnostic classification. The only adequate imaging modality that can provide information about the bone marrow composition is MRI.

Added Value of Diffusion-Weighted Magnetic Resonance Imaging in Differentiating Musculoskeletal Tumors Using Sensitivity and Specificity: A Retrospective Study and Review of Literature

Background: Diffusion-weighted imaging (DWI) provides added value to conventional MRI imaging in diagnosing and differentiating various benign and malignant musculoskeletal tumors.

Objective: The study aims to evaluate the diagnostic efficacies of diffusion-weighted imaging along with the conventional MRI sequences for differentiating benign and malignant musculoskeletal tumors using sensitivity and specificity.

Materials and methods: This retrospective study was carried out on 73 histopathologically proven patients of various musculoskeletal tumors who presented to a tertiary care center between March 2017 to October 2018. Relevant clinical examinations and MRI scan of the requested body part of the musculoskeletal system were performed. Mean apparent diffusion coefficient (ADC) values were calculated in the bone as well as soft tissue tumors after placing uniform-sized region of interest (ROI) in the non-necrotic portion of the tumor.

Statistical analysis: Independent t-test and one-way analysis of variance (ANOVA) test were used to compare the mean ADC values of the various tumors with the histopathology. Receiver operating characteristic (ROC) curve analysis was done to determine the cut-off mean ADC values in the various bone and soft tissue tumors.

Results: Of 73 patients with musculoskeletal tumors (benign=20, malignant = 53), 47 patients were bone tumors (benign=12, malignant=35) and 26 patients were soft tissue tumors (benign=eight, malignant=18). Mean ADC value of benign bone tumor was 1.257±0.327[SD] x 10^-3mm2/s and malignant was 0.951 ± 0.177[SD] x 10^-3mm2/s. The mean ADC value of benign soft tissue tumor was 1.603±0.444[SD] x 10^-3mm2/s and malignant was 1.036 ± 0.186[SD] x 10^-3mm2/s. The cut-off mean ADC value was 1.058 x 10^-3mm2/s for differentiating benign from malignant bone tumor with a sensitivity of 83.3%, specificity of 66.7% and accuracy of 78.7% while the cut-off mean ADC value of 1.198 x 10^-3mm2/s for differentiating benign from malignant soft tissue tumors with a sensitivity of 83.3%, specificity of 87.5% and accuracy of 84.6%.

Conclusions: DWI with ADC mapping can be used as an additional reliable tool along with conventional MRI sequences in discriminating benign and malignant musculoskeletal tumors.

Diffusion-weighted imaging in differentiating mid-course responders to chemotherapy for long-bone osteosarcoma compared to the histologic response: an update

BACKGROUND

Diffusion-weighted imaging (DWI) has been described to correlate with tumoural necrosis in response to preoperative chemotherapy for osteosarcoma.

OBJECTIVE

To assess the accuracy of DWI in evaluating the response to neoadjuvant chemotherapy at the mid-course treatment of long-bone osteosarcoma and in predicting survival.

MATERIALS AND METHODS

We conducted a prospective single-centre study over a continuous period of 11 years. Consecutive patients younger than 20 years treated with a neoadjuvant regimen for peripheral conventional osteosarcoma were eligible for inclusion. Magnetic resonance imaging (MRI) with DWI was performed at diagnosis, and mid- and end-course chemotherapy with mean apparent diffusion coefficients (ADC) calculated at each time point. A percentage less than or equal to 10% of the viable residual tissue at the histological analysis of the surgical specimen was defined as a good responder to chemotherapy. Survival comparisons were calculated using the Kaplan-Meier method. Uni- and multivariate analyses with ADC change were performed by Cox modelling. This is an expansion and update of our previous work.

RESULTS

Twenty-six patients between the ages of 4.8 and 19.6 years were included, of whom 14 were good responders. At mid-course chemotherapy, good responders had significantly higher mean ADC values (P=0.046) and a higher increase in ADC (P=0.015) than poor responders. The ADC change from diagnosis to mid-course MRI did not appear to be a prognosticator of survival and did not impact survival rates of both groups.

CONCLUSION

DWI at mid-course preoperative chemotherapy for osteosarcoma should be considered to evaluate the degree of histological necrosis and to predict survival. The anticipation of a response to neoadjuvant treatment by DWI may have potential implications on preoperative management.

Saturation transfer properties of tumour xenografts derived from prostate cancer cell lines 22Rv1 and DU145

Histopathology is currently the most reliable tool in assessing the aggressiveness and prognosis of solid tumours. However, developing non-invasive modalities for tumour evaluation remains crucial due to the side effects and complications caused by biopsy procedures. In this study, saturation transfer MRI was used to investigate the microstructural and metabolic properties of tumour xenografts in mice derived from the prostate cancer cell lines 22Rv1 and DU145, which express different aggressiveness. The magnetization transfer (MT) and chemical exchange saturation transfer (CEST) effects, which are associated with the microstructural and metabolic properties in biological tissue, respectively, were analyzed quantitatively and compared amongst different tumour types and regions. Histopathological staining was performed as a reference. Higher cellular density and metabolism expressed in more aggressive tumours (22Rv1) were associated with larger MT and CEST effects. High collagen content in the necrotic regions might explain their higher MT effects compared to tumour regions.

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.

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.

Imaging Analyses of Bone Tumors

Despite the evolution in imaging, especially the introduction of advanced imaging technologies, radiographs still are the key for the initial assessment of a bone tumor. Important aspects to be considered in radiographs are the location, shape and size or volume, margins, periosteal reaction, and internal mineralization of the tumor's matrix; careful evaluation of these may provide for accurate diagnosis in >80% of cases. Computed tomography and magnetic resonance imaging are often diagnostic for lesions with typical findings such as the nidus of osteoid osteoma and bone destruction such as in Ewing sarcoma and lymphoma that may be difficult to detect with radiographs; they may also be used for surgical planning. Magnetic resonance imaging accurately determines the intraosseous extent and articular and vascular involvement by the tumor. This article summarizes the diagnostic accuracy of imaging analyses in bone tumors and emphasizes the specific radiographic findings for optimal radiographic diagnosis of the patients with these tumors.

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.

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.

Radiomics signature extracted from diffusion-weighted magnetic resonance imaging predicts outcomes in osteosarcoma

OBJECTIVE

Osteosarcoma often requires multidisciplinary treatment including surgery, chemotherapy and radiotherapy. However, tumor behavior can vary widely among patients and selection of appropriate therapies in any individual patient remains a critical challenge. Radiomics seeks to quantify complex aspects of tumor images under the assumption that this information is related to tumor biology. This study tested the hypothesis that a radiomic signature extracted from Diffusion-weighted magnetic resonance images (DWI-MRI) can improve prediction of overall survival (OS) compared with clinical factors alone in localised osteosarcoma.

MATERIALS/METHODS

Pre-treatment DWI-MRI were collected from 112 patients (9-67 years of age) with histological-proven osteosarcoma that were treated with curative intent. The entire dataset was divided in two subsets: the training and validation cohorts containing 76 and 24% of the data respectively. Clinical data were extracted from our medical record. Two experienced radiotherapists evaluated DWI-MRIs for quality and segmented the tumor. A total of 103 radiomic features were calculated for each image. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features. Association between the radiomics signature and OS was explored. Further validation of the radiomics signature as an independent biomarker was performed by using multivariate Cox regression. The Cox proportional-hazard regression model was also used to analyze the correlation between the prognostic factor and the survival for the clinical (C) model after the univariate analysis. Radiomics (R) model identified radiomics signature, which is the best predictor from the radiomic variable classes based on LASSO regression. Harrell's C-index was used to demonstrate the incremental value of the radiomics signature to the traditional clinical risk factors for the individualized prediction performance.

RESULTS

Cox proportional-hazard regression model shows that: Tumor size, alkaline phosphatase (ALP) status before treatment and number of courses of chemotherapy were proven as the dependent clinical prognostic factors of osteosarcoma's overall survival time. The radiomics signature was significantly associated with OS, independent of clinical risk factors (radiomics signature: HR: 5.11, 95% CI: 2.85, 9.18, P < 0.001). Incorporating the radiomics signature into the coalition (C+R) model resulted in better performance (P < .001) for the estimation of OS (C-index: 0.813; 95% CI: 0.75, 0.89) than with the clinical (C) model (C-index: 0.764; 95% CI: 0.69, 0.85), or the single radiomics (R) model (C-index: 0.712; 95% CI: 0.65, 0.78).

CONCLUSION

This study shows that the radiomics signature extracted from pre-treatment DWI-MRI improve prediction of OS over clinical features alone. Combination of the radiomics signature and the traditional clinical risk factors performed better for individualized OS estimation in patients with osteosarcoma, which might enable a step forward precise medicine. This method may help better select patients most likely to benefit from intensified multimodality diagnosis and therapies. Future studies will focus on multi-center validation of an optimized model.

Evaluation of muscle tears in professional athletes using diffusion-weighted imaging and apparent diffusion coefficient: preliminary results

PURPOSE

Many studies have evaluated the role of DWI in musculoskeletal diseases but less is known on muscle tears. Especially for professional athletes, muscle injuries are responsible for large time lost. The aim of this study was to investigate on potential relationship between the muscle tear degree and the diffusion characteristics.

METHODS

In this retrospective study, patients signed a comprehensive consent form according to Good Clinical Practice guidelines before proceeding with all examinations. It satisfied all the requirements of the Declaration of Helsinki and the Italian national law for the protection of personal data. We have analyzed 38 professional athletes (36 males; mean age±standard deviation 27±8 years) with a muscle tear. They were 26 football and 12 athletics players, with clinically suspected injuries of the lower limbs muscles. All of patients underwent a 1.5-T MRI with standard protocol (STIR, TSE T2, SE T1, PD T2, PD fat sat T2) plus the DWI sequences with 0, 400 and 800 B-values (s/mm2). Per each B value, an experienced radiologist measured the signal intensity (SI, in arbitrary units [au]) using a region of interest (ROI) placed within the tear on DWI images. SI drop off at the third B value was calculated referred to the first B value. Similarly, ADC was measured using the ADC map in a small ROI within the tear. Bivariate associations were evaluated using the Student t test. Logistic regression was performed using the tear degree as dependent variable. Data were given as mean±standard deviation.

RESULTS

According the Muller-Wohlfarth classification, the 38 muscle tears were classified in type 3a in 22/38 cases and 3b in 16/38 cases. At bivariate analysis, 3a-tears had a SI at the third B value (24±9 au) lower (P=0.003) than that of 3b-tears (34±9 au). Similarly, 3a-tears had a SI drop off (73±10%) lower (P=0.008) than that of 3b-tears (82±9%). ADC was not significantly associated to tear degree (P=0.093). At regression analysis, SI at the third B value was the only independent predictor of the tear degree (P=0.032), while the SI drop off was borderline significant (P=0.070).

CONCLUSION

This preliminary data showed a positive correlation between the degree of muscle tears and the SI at the third B-value. Compared to 3a- tears, 3b-tears tend to show higher SI and a higher SI drop off.

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

Purpose

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

Materials and Methods

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

Results

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

Conclusion

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

Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology

Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens. Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667). Results: Upper and lower 95% limits of agreement were 7.1 and -6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = -0.42, p = 0.01, 95% confidence interval (CI) -0.22 to -0.59 for ADC; r = -0.45, p = 0.005, 95% CI -0.25 to -0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10-7, 95% CI 0.69-0.86). Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas.

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.

MRI biomarkers in osseous tumors

Although radiography continues to play a critical role in osseous tumor assessment, there have been remarkable advances in cross-sectional imaging. MRI has taken a lead in this assessment due to high tissue contrast and spatial resolution, which are well suited for bone lesion assessment. More recently, although somewhat lagging other organ systems, quantitative parameters have shown promising potential as biomarkers for osseous tumors. Among these sequences are chemical shift imaging (CSI), apparent diffusion coefficient (ADC), and intravoxel incoherent motion (IVIM) from diffusion-weighted imaging (DWI), quantitative dynamic contrast enhanced (DCE)-MRI, and magnetic resonance spectroscopy (MRS). In this article, we review the background and recent roles of these quantitative MRI biomarkers for osseous tumors. Level of Evidence: 3 Technical Efficacy Stage: 3 J. MAGN. RESON. IMAGING 2019. J. Magn. Reson. Imaging 2019;50:702-718.

In vivo, noninvasive functional measurements of bone sarcoma using diffuse optical spectroscopic imaging

Diffuse optical spectroscopic imaging (DOSI) is an emerging near-infrared imaging technique that noninvasively measures quantitative functional information in thick tissue. This study aimed to assess the feasibility of using DOSI to measure optical contrast from bone sarcomas. These tumors are rare and pose technical and practical challenges for DOSI measurements due to the varied anatomic locations and tissue depths of presentation. Six subjects were enrolled in the study. One subject was unable to be measured due to tissue contact sensitivity. For the five remaining subjects, the signal-to-noise ratio, imaging depth, optical properties, and quantitative tissue concentrations of oxyhemoglobin, deoxyhemoglobin, water, and lipids from tumor and contralateral normal tissues were assessed. Statistical differences between tumor and contralateral normal tissue were found in chromophore concentrations and optical properties for four subjects. Low signal-to-noise was encountered during several subject's measurements, suggesting increased detector sensitivity will help to optimize DOSI for this patient population going forward. This study demonstrates that DOSI is capable of measuring optical properties and obtaining functional information in bone sarcomas. In the future, DOSI may provide a means to stratify treatment groups and monitor chemotherapy response for this disease.

Pre-clinical Evaluation of a Cyanine-Based SPECT Probe for Multimodal Tumor Necrosis Imaging

PURPOSE

Recently we showed that a number of carboxylated near-infrared fluorescent (NIRF) cyanine dyes possess strong necrosis avid properties in vitro as well as in different mouse models of spontaneous and therapy-induced tumor necrosis, indicating their potential use for cancer diagnostic- and prognostic purposes. In the previous study, the detection of the cyanines was achieved by whole body optical imaging, a technique that, due to the limited penetration of near-infrared light, is not suitable for investigations deeper than 1 cm within the human body. Therefore, in order to facilitate clinical translation, the purpose of the present study was to generate a necrosis avid cyanine-based NIRF probe that could also be used for single photon emission computed tomography (SPECT). For this, the necrosis avid NIRF cyanine HQ4 was radiolabeled with ¹¹¹indium, via the chelate diethylene triamine pentaacetic acid (DTPA).

PROCEDURES

The necrosis avid properties of the radiotracer [¹¹¹In]DTPA-HQ4 were examined in vitro and in vivo in different breast tumor models in mice using SPECT and optical imaging. Moreover, biodistribution studies were performed to examine the pharmacokinetics of the probe in vivo.

RESULTS

Using optical imaging and radioactivity measurements, in vitro, we showed selective accumulation of [¹¹¹In]DTPA-HQ4 in dead cells. Using SPECT and in biodistribution studies, the necrosis avidity of the radiotracer was confirmed in a 4T1 mouse breast cancer model of spontaneous tumor necrosis and in a MCF-7 human breast cancer model of chemotherapy-induced tumor necrosis.

CONCLUSIONS

The radiotracer [¹¹¹In]DTPA-HQ4 possessed strong and selective necrosis avidity in vitro and in various mouse models of tumor necrosis in vivo, indicating its potential to be clinically applied for diagnostic purposes and to monitor anti-cancer treatment efficacy.

Quantitative diffusion-weighted magnetic resonance imaging assessment of chemotherapy treatment response of pediatric osteosarcoma and Ewing sarcoma malignant bone tumors

OBJECTIVE

Assessment of tumor response to chemotherapy is essential in managing malignant pediatric bone tumors prior to resection.

SUBJECTS AND METHODS

Pre-chemotherapy and post-chemotherapy osteosarcoma and Ewing sarcoma cases (n=18) were analyzed with apparent diffusion coefficient (ADC) values measured by two readers.

RESULTS

Treated tumors demonstrated significantly greater ADC values compared to untreated tumors (p<0.001). Intraclass correlation coefficients ranged between 0.858 and 0.935. No significant tumor volume differences were observed. Regression analysis demonstrated average ADC as the best predictor of treatment.

CONCLUSIONS

Our study suggests that ADC values may be useful for evaluating chemotherapeutic response of malignant pediatric bone tumors.

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

The histological examination of the tumor necrosis upon surgery remains the most reliable prognostic factor for osteosarcoma. However, the detection of more early prognostic factors is desirable in order to increase the survival rates and decrease the risk rates for iatrogenic toxicity. The purpose of the current systematic review and meta-analysis was to provide an up-to-date summary of the role of diffusion-weighted imaging (DWI) for the preoperative assessment of the chemotherapy response in osteosarcoma. Articles evaluating DWI for the preoperative assessment of the chemotherapy response of osteosarcoma were systematically searched for in four electronic literature databases. The mean difference in apparent diffusion coefficient (ADC) following neoadjuvant chemotherapy between good and poor histological responders was assessed in 5 studies. The mean difference in the ADC ratio (the percentage change in ADC between post-neoadjuvant and pre-neoadjuvant chemotherapy) reported in 3 studies was also assessed. Five articles with 106 patients fulfilled all of the inclusion criteria for the meta-analysis. Significant mean differences were found between good and poor responders in the ADC in the 5 studies (P=0.03) and the ADC ratio in the 3 studies (P<0.00001). The good responders demonstrated a higher ADC and a higher ADC ratio than the poor responders. DWI performed with ADC values was useful for predicting the chemotherapeutic response of osteosarcoma. This method may have promising potential as a preoperative non-invasive modality.

Rationale for Modernising Imaging in Advanced Prostate Cancer

CONTEXT

To effectively manage patients with advanced prostate cancer (APC), it is essential to have accurate, reproducible, and validated methods for detecting and quantifying the burden of bone and soft tissue metastases and for assessing their response to therapy. Current standard of care imaging with bone and computed tomography (CT) scans have significant limitations for the assessment of bone metastases in particular.

OBJECTIVE

We aimed to undertake a critical comparative review of imaging methods used for diagnosis and disease monitoring of metastatic APC from the perspective of their availability and ability to assess disease presence, extent, and response of bone and soft tissue disease.

EVIDENCE ACQUISITION

An expert panel of radiologists, nuclear medicine physicians, and medical physicists with the greatest experience of imaging in advanced prostate cancer prepared a review of the practicalities, performance, merits, and limitations of currently available imaging methods.

EVIDENCE SYNTHESIS

Meta-analyses showed that positron emission tomography (PET)/CT with different radiotracers and whole-body magnetic resonance imaging (WB-MRI) are more accurate for bone lesion detection than CT and bone scans (BSs). At a patient level, the pooled sensitivities for bone disease by using choline (CH)-PET/CT, WB-MRI, and BS were 91% (95% confidence interval [CI], 83-96%), 97% (95% CI, 91-99%), and 79% (95% CI, 73-83%), respectively. The pooled specificities for bone metastases detection using CH-PET/CT, WB-MRI, and BS were 99% (95% CI, 93-100%), 95% (95% CI, 90-97%), and 82% (95% CI, 78-85%), respectively. The ability of PET/CT and WB-MRI to assess therapeutic benefits is promising but has not been comprehensively evaluated. There is variability in the cost, availability, and quality of PET/CT and WB-MRI.

CONCLUSIONS

Standardisation of acquisition, interpretation, and reporting of WB-MRI and PET/CT scans is required to assess the performance of these techniques in clinical trials of treatment approaches in APC.

PATIENT SUMMARY

PET/CT and whole-body MRI scans have the potential to improve detection and to assess response to treatment of all states of advanced prostate cancer. Consensus recommendations on quality standards, interpretation, and reporting are needed but will require validation in clinical trials of established and new treatment approaches.

Diffusion MRI in early cancer therapeutic response assessment

Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. Copyright © 2016 John Wiley & Sons, Ltd.

Increased zinc accumulation in mineralized osteosarcoma tissue measured by confocal synchrotron radiation micro X-ray fluorescence analysis

Abnormal tissue levels of certain trace elements such as zinc (Zn) were reported in various types of cancer. Little is known about the role of Zn in osteosarcoma. Using confocal synchrotron radiation micro X-ray fluorescence analysis, we characterized the spatial distribution of Zn in high-grade sclerosing osteosarcoma of nine patients (four women/five men; seven knee/one humerus/one femur) following chemotherapy and wide surgical resection. Levels were compared with adjacent normal tissue. Quantitative backscattered electron imaging as well as histological examinations was also performed. On average, the ratio of medians of Zn count rates (normalized to calcium) in mineralized tumor tissue was about six times higher than in normal tissue. There was no difference in Zn levels between tumor fraction areas with a low fraction and a high fraction of mineralized tissue, which were clearly depicted using quantitative backscattered electron imaging. Moreover, we found no correlation between the Zn values and the type of tumor regression according to the Salzer-Kuntschik grading. The underlying mechanism of Zn accumulation remains unclear. Given the emerging data on the role of trace elements in other types of cancer, our novel results warrant further studies on the role of trace elements in bone cancer. Copyright © 2016 The Authors. X-Ray Spectrometry published by John Wiley & Sons Ltd.

Necrosis avid near infrared fluorescent cyanines for imaging cell death and their use to monitor therapeutic efficacy in mouse tumor models

Quantification of tumor necrosis in cancer patients is of diagnostic value as the amount of necrosis is correlated with disease prognosis and it could also be used to predict early efficacy of anti-cancer treatments. In the present study, we identified two near infrared fluorescent (NIRF) carboxylated cyanines, HQ5 and IRDye 800CW (800CW), which possess strong necrosis avidity. In vitro studies showed that both dyes selectively bind to cytoplasmic proteins of dead cells that have lost membrane integrity. Affinity for cytoplasmic proteins was confirmed using quantitative structure activity relations modeling. In vivo results, using NIRF and optoacoustic imaging, confirmed the necrosis avid properties of HQ5 and 800CW in a mouse 4T1 breast cancer tumor model of spontaneous necrosis. Finally, in a mouse EL4 lymphoma tumor model, already 24 h post chemotherapy, a significant increase in 800CW fluorescence intensity was observed in treated compared to untreated tumors. In conclusion, we show, for the first time, that the NIRF carboxylated cyanines HQ5 and 800CW possess strong necrosis avid properties in vitro and in vivo. When translated to the clinic, these dyes may be used for diagnostic or prognostic purposes and for monitoring in vivo tumor response early after the start of treatment.

Correlation between apparent diffusion coefficient and histopathology subtypes of osteosarcoma after neoadjuvant chemotherapy

Background Neoadjuvant chemotherapy has made limb-salvage surgery possible for the patients with osteosarcoma. Diffusion-weighted magnetic resonance imaging (DWI) has been used to monitor chemotherapy response. Purpose To correlate the apparent diffusion coefficient (ADC) values with histopathology subtypes of osteosarcoma after neoadjuvant chemotherapy. Material and Methods Twelve patients with osteoblastic (n = 7), chondroblastic (n = 4), and fibroblastic (n = 1) osteosarcomas underwent post-chemotherapy DWI before limb-salvage surgery. ADCs corresponding to 127 histological tissue samples from the 12 resected specimens were compared to histological features. Results The mean ADC value of non-cartilaginous viable tumor (38/91, ADC = 1.22 ± 0.03 × 10^-3mm²/s) was significantly ( P < 0.001) lower than that of non-cartilaginous tumor cell necrosis without stroma disintegration (25/91, ADC =1.77 ± 0.03 × 10^-3mm²/s), cartilaginous viable tumor (14/91, ADC = 2.19 ± 0.04 × 10^-3mm²/s), and cystic areas including liquefied necrosis, blood space, and secondary aneurysmal bone cyst (14/91, ADC = 2.29 ± 0.05 × 10^-3mm²/s). The mean ADC value of non-cartilaginous tumor cell necrosis was also significantly ( P < 0.001) smaller than those of viable cartilaginous tumor and cystic/hemorrhagic necrosis whereas the mean ADC values were not significantly ( P > 0.05) different between viable cartilaginous tumor and cystic/hemorrhagic necrosis. Conclusion DWI allows assessment of tumor necrosis after neoadjuvant chemotherapy by ADC differences between viable tumor and necrosis in fibroblastic and osteoblastic osteosarcomas whereas viable chondroblastic osteosarcoma has high ADC and cannot be distinguished reliably from necrosis.

The Necrosis-Avid Small Molecule HQ4-DTPA as a Multimodal Imaging Agent for Monitoring Radiation Therapy-Induced Tumor Cell Death

PURPOSE

Most effective antitumor therapies induce tumor cell death. Non-invasive, rapid and accurate quantitative imaging of cell death is essential for monitoring early response to antitumor therapies. To facilitate this, we previously developed a biocompatible necrosis-avid near-infrared fluorescence (NIRF) imaging probe, HQ4, which was radiolabeled with 111Indium-chloride (111In-Cl3) via the chelate diethylene triamine pentaacetic acid (DTPA), to enable clinical translation. The aim of the present study was to evaluate the application of HQ4-DTPA for monitoring tumor cell death induced by radiation therapy. Apart from its NIRF and radioactive properties, HQ4-DTPA was also tested as a photoacoustic imaging probe to evaluate its performance as a multimodal contrast agent for superficial and deep tissue imaging.

MATERIALS AND METHODS

Radiation-induced tumor cell death was examined in a xenograft mouse model of human breast cancer (MCF-7). Tumors were irradiated with three fractions of 9 Gy each. HQ4-DTPA was injected intravenously after the last irradiation, NIRF and photoacoustic imaging of the tumors were performed at 12, 20, and 40 h after injection. Changes in probe accumulation in the tumors were measured in vivo, and ex vivo histological analysis of excised tumors was performed at experimental endpoints. In addition, biodistribution of radiolabeled [111In]DTPA-HQ4 was assessed using hybrid single-photon emission computed tomography-computed tomography (SPECT-CT) at the same time points.

RESULTS

In vivo NIRF imaging demonstrated a significant difference in probe accumulation between control and irradiated tumors at all time points after injection. A similar trend was observed using in vivo photoacoustic imaging, which was validated by ex vivo tissue fluorescence and photoacoustic imaging. Serial quantitative radioactivity measurements of probe biodistribution further demonstrated increased probe accumulation in irradiated tumors.

CONCLUSION

HQ4-DTPA has high specificity for dead cells in vivo, potentiating its use as a contrast agent for determining the relative level of tumor cell death following radiation therapy using NIRF, photoacoustic imaging and SPECT in vivo. Initial preclinical results are promising and indicate the need for further evaluation in larger cohorts. If successful, such studies may help develop a new multimodal method for non-invasive and dynamic deep tissue imaging of treatment-induced cell death to quantitatively assess therapeutic response in patients.

Diffusion-weighted imaging and the skeletal system: a literature review

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) sequence that has a well-established role in neuroimaging, and is increasingly being utilised in other clinical contexts, including the assessment of various skeletal disorders. It utilises the variability of Brownian motion of water molecules; the differing patterns of water molecular diffusion in various biological tissues help determine the contrast obtained in DWI. Although early research on the clinical role of DWI focused mainly on the field of neuroimaging, there are now more studies demonstrating the promising role DWI has in the diagnosis and monitoring of various osseous diseases. DWI has been shown to be useful in assessing a patient's skeletal tumour burden, monitoring the post-chemotherapy response of various bony malignancies, detecting hip ischaemia in patients with Legg-Calvé-Perthes disease, as well as determining the quality of repaired articular cartilage. Despite its relative successes, DWI has several limitations, including its limited clinical value in differentiating chondrosarcomas from benign bone lesions, as well as osteoporotic vertebral compression fractures from compression fractures due to malignancy. This literature review aims to provide an overview of the recent developments in the use of DWI in imaging the skeletal system, and to clarify the role of DWI in assessing various osseous diseases.

Musculoskeletal Sarcoma: Update on Imaging of the Post-treatment Patient

Post-treatment imaging of musculoskeletal sarcoma remains challenging, but newer imaging techniques are improving our ability to recognize both local and distant recurrence and accurately distinguish local recurrence from post-treatment change. We review recent advances in dynamic contrast-enhanced magnetic resonance imaging, diffusion-weighted magnetic resonance imaging with apparent diffusion coefficient mapping and positron emission tomography/computed tomography in the post-treatment follow-up of musculoskeletal sarcoma. We also describe our multidisciplinary sarcoma team approach to patient care and the essential role of the radiologist in the clinical follow-up scheme.

Volumetric segmentation of ADC maps and utility of standard deviation as measure of tumor heterogeneity in soft tissue tumors

PURPOSE

Determine interobserver concordance of semiautomated three-dimensional volumetric and two-dimensional manual measurements of apparent diffusion coefficient (ADC) values in soft tissue masses (STMs) and explore standard deviation (SD) as a measure of tumor ADC heterogeneity.

RESULTS

Concordance correlation coefficients for mean ADC increased with more extensive sampling. Agreement on the SD of tumor ADC values was better for large regions of interest and multislice methods. Correlation between mean and SD ADC was low, suggesting that these parameters are relatively independent.

CONCLUSION

Mean ADC of STMs can be determined by volumetric quantification with high interobserver agreement. STM heterogeneity merits further investigation as a potential imaging biomarker that complements other functional magnetic resonance imaging parameters.

Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification

PURPOSE

A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range. The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation.

MATERIALS AND METHODS

Fifty-three patients with endometrial (n=28) and cervical (n=25) cancers underwent pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk). A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI outlined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT="mean minus three SD") and higher threshold (HT="mean plus one SD"). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10-3mm(2)/s. A Kruskal-Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation-coefficient (ICC).

RESULTS

DV values were significantly different among G and risk groups in both endometrial (p<0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones. For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones. The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86).

CONCLUSIONS

DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.

Assessment of Musculoskeletal Malignancies with Functional MR Imaging

Functional MR imaging is the technique of choice to evaluate and manage malignant musculoskeletal masses. Advanced MR imaging sequences include chemical shift MR imaging, diffusion-weighted imaging with apparent diffusion coefficient mapping, MR spectroscopy imaging, and dynamic contrast-enhanced perfusion imaging. Functional MR imaging adds value to morphologic sequences in the detection, characterization, staging, and posttherapy assessment of malignant musculoskeletal malignancies. This article reviews the technical role of each functional sequence and their clinical applications to allow more confident decisions to be made. Multiparametric analysis of functional and anatomic MR sequences allows musculoskeletal tumors analysis to be improved.

Advanced Noncontrast MR Imaging in Musculoskeletal Radiology

Multiple nonmorphologic magnetic resonance sequences are available in musculoskeletal imaging that can provide additional information to better characterize and diagnose musculoskeletal disorders and diseases. These sequences include blood-oxygen-level-dependent (BOLD), arterial spin labeling (ASL), diffusion-weighted imaging (DWI), and diffusion-tensor imaging (DTI). BOLD and ASL provide different methods to evaluate skeletal muscle microperfusion. The BOLD signal reflects the ratio between oxyhemoglobin and deoxyhemoglobin. ASL uses selective tagging of inflowing blood spins in a specific region for calculating local perfusion. DWI and DTI provide information about the structural integrity of soft tissue including muscles and fibers as well as pathologies.

Assessing response to treatment of bone metastases from breast cancer: what should be the standard of care?

Bone is the most common site for breast cancer metastases, occurring in up to 70% of those with metastatic disease. In order to effectively manage these patients, it is essential to have consistent, reproducible and validated methods of assessing response to therapy. We present current clinical practice of imaging response assessment of bone metastases. We also review the biology of bone metastases and measures of response assessment including clinical assessment, tumour markers and imaging techniques; bone scans (BSs), computed tomography (CT), positron emission tomography, magnetic resonance imaging (MRI) and whole-body diffusion-weighted MRI (WB DW-MRI). The current standard of care of BSs and CT has significant limitations and are not routinely recommended for the purpose of response assessment in the bones. WB DW-MRI has the potential to address this unmet need and should be evaluated in clinical trials.

Diffusion-weighted imaging in pediatric body MR imaging: principles, technique, and emerging applications

Diffusion-weighted (DW) imaging is an emerging technique in body imaging that provides indirect information about the microenvironment of tissues and lesions and helps detect, characterize, and follow up abnormalities. Two main challenges in the application of DW imaging to body imaging are the decreased signal-to-noise ratio of body tissues compared with neuronal tissues due to their shorter T2 relaxation time, and image degradation related to physiologic motion (eg, respiratory motion). Use of smaller b values and newer motion compensation techniques allow the evaluation of anatomic structures with DW imaging. DW imaging can be performed as a breath-hold sequence or a free-breathing sequence with or without respiratory triggering. Depending on the mobility of water molecules in their microenvironment, different normal tissues have different signals at DW imaging. Some normal tissues (eg, lymph nodes, spleen, ovarian and testicular parenchyma) are diffusion restricted, whereas others (eg, gallbladder, corpora cavernosa, endometrium, cartilage) show T2 shine-through. Epiphyses that contain fatty marrow and bone cortex appear dark on both DW images and apparent diffusion coefficient maps. Current and emerging applications of DW imaging in pediatric body imaging include tumor detection and characterization, assessment of therapy response and monitoring of tumors, noninvasive detection and grading of liver fibrosis and cirrhosis, detection of abscesses, and evaluation of inflammatory bowel disease.

Does amputation offer any survival benefit over limb salvage in osteosarcoma patients with poor chemonecrosis and close margins?

A poor response to chemotherapy (≤ 90% necrosis) for osteosarcomas leads to poorer survival and an increased risk of local recurrence, particularly if there is a close margin of excision. We evaluated whether amputation confers any survival benefit over limb salvage surgery (LSS) with narrow margins in patients who respond poorly to chemotherapy.

We only analysed patients with an osteosarcoma of the limb, a poor response to chemotherapy and close margins on LSS (marginal/intralesional) or primary amputation: 360 patients (36 LSS (intralesional margins), 197 LSS (marginal margins) and 127 amputations) were included. Local recurrence developed in 13 (36%) following LSS with intralesional margins, and 39 (20%) following LSS with marginal margins. There was no local recurrence in patients who underwent amputation. The five-year survival for all patients was 41% (95% confidence interval (CI) 35 to 46), but for those treated by LSS with marginal margins was 46.2% (95% CI 38 to 53), 36.3% (95% CI 27 to 45) for those treated by amputation, and 28% (95 CI 14 to 44) for those treated by LSS with intralesional margins. Patients who had LSS and then developed local recurrence as a first event had the same survival as those who had primary amputation without local recurrence. Prophylactic adjuvant radiotherapy was used in 40 patients but had no discernible effect in preventing local recurrence.

Although amputation offered better local control, it conferred no clear survival benefit over LSS with marginal margins in these patients with a poor overall prognosis.

Cite this article: Bone Joint J 2015;97-B:115–20.

Insights into quantitative diffusion-weighted MRI for musculoskeletal tumor imaging

OBJECTIVE

The purposes of this article are to discuss the technical considerations for performing quantitative diffusion-weighted MRI (DWI) with apparent diffusion coefficient (ADC) mapping, examine the role of DWI in whole-body MRI, and review how DWI with ADC mapping can serve as an adjunct to information gleaned from conventional MRI in the radiologic evaluation of musculoskeletal lesions.

CONCLUSION

The primary role of whole-body DWI is in tumor detection; localized DWI is helpful in differentiating malignant bone and soft-tissue lesions. After treatment, an increase in tumor ADC values correlates with response to cytotoxic therapy. The use of DWI in the evaluation of musculoskeletal lesions requires knowledge of potential diagnostic pitfalls that stem from technical challenges and confounding biochemical factors that influence ADC maps but are unrelated to lesion cellularity.