Monitoring therapeutic responses of primary bone tumors by diffusion-weighted image: Initial results

The Role of Whole-Body MRI in Pediatric Musculoskeletal Oncology: Current Concepts and Clinical Applications

Whole-body magnetic resonance imaging (WB-MRI) has gained importance in the field of musculoskeletal oncology over the last decades, consisting in a one-stop imaging method that allows a wide coverage assessment of both bone and soft tissue involvement. WB-MRI is valuable for diagnosis, staging, and follow-up in many oncologic diseases and is especially advantageous for the pediatric population since it avoids redundant examinations and exposure to ionizing radiation in patients who often undergo long-term surveillance. Its clinical application has been studied in many pediatric neoplasms, such as cancer predisposition syndromes, Langerhans cell histiocytosis, lymphoma, sarcomas, and neuroblastoma. The addition of diffusion-weighted sequences allows functional evaluation of neoplastic lesions, which is helpful in the assessment of viable tumor and response to treatment after neoadjuvant or adjuvant therapy. WB-MRI is an excellent alternative to fluorodeoxyglucose-positron emission tomography/computed tomography in oncologic children, with comparable accuracy and the convenience of being radiation-free, fast to perform, and available at a similar cost. The development of new techniques and protocols makes WB-MRI increasingly faster, safer, and more accessible, and it is important for referring physicians and radiologists to recognize the role of this imaging method in pediatric oncology. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Bone tumors: state-of-the-art imaging

Imaging plays a central role in the management of patients with bone tumors. A number of imaging modalities are available, with different techniques having unique applications that render their use advantageous for various clinical purposes. Coupled with detailed clinical assessment, radiological imaging can assist clinicians in reaching a proper diagnosis, determining appropriate management, evaluating response to treatment, and monitoring for tumor recurrence. Although radiography is still the initial imaging test of choice for a patient presenting with a suspected bone tumor, technological innovations in the last decades have advanced the role of other imaging modalities for assessing bone tumors, including advances in computed tomography, magnetic resonance imaging, scintigraphy, and hybrid imaging techniques that combine two existing modalities, providing clinicians with diverse tools for bone tumor imaging applications. Determining the most suitable modality to use for a particular application requires familiarity with the modality in question, its advancements, and its limitations. This review highlights the various imaging techniques currently available and emphasizes the latest developments in imaging, offering a framework that can help guide the imaging of patients with bone tumors.

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.

Diffusion weighted imaging of extremity bone tumors-inter-reader analysis and incremental value over conventional MR imaging

OBJECTIVE

To determine whether the addition of diffusion-weighted imaging (DWI) to conventional MRI improves diagnostic accuracy of bone tumor characterization with the hypothesis that the DWI has incremental value in the diagnosis of osseous tumors.

METHODS

In this multireader cross-sectional validation study, four musculoskeletal radiologists evaluated osseous tumors blinded to final diagnosis in two rounds-first without DWI or apparent diffusion coefficient (ADC) maps, then months later with these available. Each reader recorded a binary result as to whether the lesion is benign or malignant. Intraclass correlation (ICC) and Conger's κ were used. Diagnostic performance measures including area under the receiver operating curve (AUC) were reported.

RESULTS

133 osseous tumors of the extremities (76 benign, 57 malignant) were tested. Blinded to DWI, average reader sensitivity, specificity, positive-predictive value, and negative-predictive value were 0.83, 0.92, 0.94, and 0.82, respectively. With DWI, the values were 0.85, 0.92, 0.94, and 0.83, respectively. Interreader agreement was good for both rounds (0.67 and 0.71, respectively, p-value > 0.05). Average reader confidence was 4.1 and 4.4, respectively (p-value < 0.001). ADC values and DWI/ADC ratios showed significant differences between benign and malignant tumors.

CONCLUSION

DWI and ADC show statistically significantly different values of benign from malignant osseous tumors and mildly increased radiologist confidence with similar interreader reliability. However, given similar diagnostic accuracy, conventional MR imaging is adequate for bone tumor characterization and incremental value of DWI is limited.

ADVANCES IN KNOWLEDGE

This paper is the first of its kind to report the use of DWI/ADC ratio for the diagnosis of bone tumors.

Predicting Non-Small-Cell Lung Cancer Survival after Curative Surgery via Deep Learning of Diffusion MRI

BACKGROUND

the objective of this study is to evaluate the predictive power of the survival model using deep learning of diffusion-weighted images (DWI) in patients with non-small-cell lung cancer (NSCLC).

METHODS

DWI at b-values of 0, 100, and 700 sec/mm2 (DWI0, DWI100, DWI700) were preoperatively obtained for 100 NSCLC patients who underwent curative surgery (57 men, 43 women; mean age, 62 years). The ADC0-100 (perfusion-sensitive ADC), ADC100-700 (perfusion-insensitive ADC), ADC0-100-700, and demographic features were collected as input data and 5-year survival was collected as output data. Our survival model adopted transfer learning from a pre-trained VGG-16 network, whereby the softmax layer was replaced with the binary classification layer for the prediction of 5-year survival. Three channels of input data were selected in combination out of DWIs and ADC images and their accuracies and AUCs were compared for the best performance during 10-fold cross validation.

RESULTS

66 patients survived, and 34 patients died. The predictive performance was the best in the following combination: DWI0-ADC0-100-ADC0-100-700 (accuracy: 92%; AUC: 0.904). This was followed by DWI0-DWI700-ADC0-100-700, DWI0-DWI100-DWI700, and DWI0-DWI0-DWI0 (accuracy: 91%, 81%, 76%; AUC: 0.889, 0.763, 0.711, respectively). Survival prediction models trained with ADC performed significantly better than the one trained with DWI only (p-values < 0.05). The survival prediction was improved when demographic features were added to the model with only DWIs, but the benefit of clinical information was not prominent when added to the best performing model using both DWI and ADC.

CONCLUSIONS

Deep learning may play a role in the survival prediction of lung cancer. The performance of learning can be enhanced by inputting precedented, proven functional parameters of the ADC instead of the original data of DWIs only.

Prediction of pathological response grading for esophageal squamous carcinoma after neoadjuvant chemoradiotherapy based on MRI imaging using PDX

Introduction

To confirm the efficacy of magnetic resonance-diffusion weighted imaging (MR-DWI) in esophageal squamous cell carcinoma (ESCC) early pathological response prediction and assessment to neoadjuvant chemoradiotherapy (nCRT) using patient-derived xenografts (PDXs).

Methods

PDX-bearing mice were randomly divided into two groups: the experimental group receiving cisplatin combined with radiotherapy, whereas the control group receiving normal saline. MRI scans were performed in treatment groups in the before, middle, and end of treatment. The correlations between tumor volumes, ADC values and tumor pathological response at different time nodes were explored. Then, expression of proliferation marker and apoptotic marker were detected using immunohistochemistry, and apoptosis rate was detected by TUNEL assay to further verify the results observed in the PDX models.

Results

The ADC values of the experimental group were significantly higher than the control group in the both middle and end stage of treatment (all P< 0.001), however, significant difference was only observed in tumor volume at the end stage of treatment (P< 0.001). Furthermore, the △ADC_mid-pre in our study may able to identify tumors with or without pCR to nCRT at an early stage, due to these changes were prior to the changes of tumor volume after treatment. Finally, TUNEL results also showed that the apoptosis rate of the experiment groups increased the most in the middle stage of treatment, especially the groups with pCR, but the highest apoptosis rate occurred in the end of the treatment. Further, the two PDX models with pCR exhibited the highest levels of apoptotic marker (Bax), and lowest levels of proliferation marker (PCNA and Ki-67) in the both middle and end stage of the treatment.

Conclusions

ADC values could be used to determine the tumor's response to nCRT, especially in the middle stages of treatment and before the tumor tissue morphology changes, and further, the ADC values were consistent with the potential biomarkers reflecting histopathological changes. Therefore, we suggest that radiation oncologists could refer to the ADC values in the middle stages of treatment when predicting the tumor histopathological response to n CRT in patients with ESCC.

MRI-guided microwave ablation and albumin-bound paclitaxel for lung tumors: Initial experience

Magnetic resonance-guided microwave ablation (MRI-guided MWA) is a new, minimally invasive ablation method for cancer. This study sought to analyze the clinical value of MRI-guided MWA in non-small cell lung cancer (NSCLC). We compared the precision, efficiency, and clinical efficacy of treatment in patients who underwent MRI-guided MWA or computed tomography (CT)-guided microwave ablation (CT-guided MWA). Propensity score matching was used on the prospective cohort (MRI-MWA group, n = 45) and the retrospective observational cohort (CT-MWA group, n = 305). To evaluate the advantages and efficacy of MRI-guided MWA, data including the accuracy of needle placement, scan duration, ablation time, total operation time, length of hospital stay, progression-free survival (PFS), and overall survival (OS) were collected and compared between the two groups. The mean number of machine scans required to adjust the needle position was 7.62 ± 1.69 (range 4–12) for the MRI-MWA group and 9.64 ± 2.14 (range 5–16) for the CT-MWA group (p < 0.001). The mean time for antenna placement was comparable between the MRI and CT groups (54.41 ± 12.32 min and 53.03 ± 11.29 min, p = 0.607). The microwave ablation time of the two groups was significantly different (7.62 ± 2.65 min and 9.41 ± 2.86 min, p = 0.017), while the overall procedure time was comparable (91.28 ± 16.69 min vs. 93.41 ± 16.03 min, p = 0.568). The overall complication rate in the MRI-MWA group was significantly lower than in the CT-MWA group (12% vs. 51%, p = 0.185). The median time to progression was longer in the MRI-MWA group than in the CT-MWA group (11 months [95% CI 10.24–11.75] vs. 9 months [95% CI 8.00–9.99], p = 0.0003; hazard ratio 0.3690 [95% CI 0.2159–0.6306]). OS was comparable in both groups (MRI group 26.0 months [95% CI 25.022–26.978] vs. CT group 23.0 months [95% CI 18.646–27.354], p = 0.18). This study provides hitherto-undocumented evidence of the clinical effects of MRI-guided MWA on patients with NSCLC and determines the relative safety and efficiency of MRI- and CT-guided MWA.

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.

Multiparametric MRI evaluation of bone sarcomas in children

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

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

Background

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

Methods

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

Results

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

Conclusions

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

Diffusion kurtosis imaging assessment of the response to radiotherapy in a VX2 bone tumor model: an animal study

BACKGROUND

Neoadjuvant radiotherapy plays a vital role in the treatment of malignant bone tumors, and non-invasive imaging methods are needed to evaluate the response to treatment.

PURPOSE

To assess the value of diffusion kurtosis imaging (DKI) for monitoring early response to radiotherapy in malignant bone tumors.

MATERIAL AND METHODS

Treatment response was evaluated in a rabbit VX2 bone tumor model (n = 35) using magnetic resonance imaging (MRI), DKI, and histopathologic examinations. Subjects were divided into three groups: pre-treatment, post-treatment, and control groups. The post-treatment group was subclassified into good response and poor response groups according to the results of histopathologic examination. Apparent diffusion coefficient (ADC) and DKI parameters (mean diffusion coefficient [MD] and mean kurtosis [MK]) were recorded. The relationship between ADC, DKI parameters, and histopathologic changes after radiotherapy was determined using Pearson's correlation coefficient. The diagnostic performance of these parameters was assessed using receiver operating characteristic analysis.

RESULTS

MD in the good response group was higher after treatment than before treatment (P < 0.001) and higher than that in the poor response group (P = 0.009). MD was highly correlated with tumor cell density and apoptosis rate (r = -0.771, P < 0.001 and r = 0.625, P < 0.001, respectively). MD was superior to other parameters for determining the curative effect of radiotherapy, with a sensitivity of 75.0%, specificity of 100.0%, and area under the curve of 0.917 (P < 0.001).

CONCLUSION

The correlations between MD, tumor cell density, and apoptosis suggest that MD could be useful for assessing the early response to radiotherapy in rabbit VX2 malignant bone tumors.

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.

Update on MR Imaging of Soft Tissue Tumors of Head and Neck

This article reviews soft tissue tumors of the head and neck following the 2020 revision of WHO Classification of Soft Tissue and Bone Tumours. Common soft tissue tumors in the head and neck and tumors are discussed, along with newly added entities to the classification system. Salient clinical and imaging features that may allow for improved diagnostic accuracy or to narrow the imaging differential diagnosis are covered. Advanced imaging techniques are discussed, with a focus on diffusion-weighted and dynamic contrast imaging and their potential to help characterize soft tissue tumors and aid in distinguishing malignant from benign tumors.

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.

Diffusion-weighted imaging for the differentiation of Ewing sarcoma from osteosarcoma

OBJECTIVE

The purpose of this study is to assess the ability of apparent diffusion coefficient (ADC) values in differentiating Ewing sarcoma and osteosarcoma.

MATERIALS AND METHODS

This retrospective cross-sectional observational study included a total of 35 patients with a recent diagnosis of Ewing sarcoma (n = 13) and osteosarcoma (n = 22) who underwent conventional MRI and diffusion-weighted imaging (DWI). Three ADC measurements from the areas of the lowest diffusivity in ADC maps (ADC_min), and other areas with low diffusivity (ADC_other), were made independently by two observers on pre-treatment MRI, and the means of these measurements were compared using independent samples t-test. Intraclass correlation coefficient was calculated for inter-observer agreement.

RESULTS

There was a significant difference between the ADC_min (P < 0.001) and ADC_other (P < 0.001) in Ewing sarcoma and osteosarcoma for both observers. For Ewing sarcoma and osteosarcoma, mean ADC_min was 0.566 ± 0.07 and 1.193 ± 0.33 × 10^-3 mm²/s; 0.551 ± 0.08 and 1.182 ± 0.33 × 10^-3 mm²/s; and mean ADC_other was 0.813 ± 0.11 and 1.510 ± 0.35 × 10^-3 mm²/s; 0811 ± 0.12 and 1.501 ± 0.33 × 10^-3 mm²/s for observers 1 and 2, respectively. Inter-observer correlation coefficient for mean ADC_min was 0.994 and for mean ADC_other was 0.995.

CONCLUSION

Diffusion-weighted imaging and ADC values could be used in the differentiation of Ewing sarcoma and osteosarcoma in borderline cases.

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.

Osseous Tumor Reporting and Data System-Multireader Validation Study

OBJECTIVE

To develop and validate an Osseous Tumor Reporting and Data System (OT-RADS) with the hypothesis that the proposed guideline is reliable and assists in separating benign from malignant osseous tumors with a good area under the curve, and that could assist further patient management.

METHODS

In this multireader cross-sectional validation study, an agreement was reached for OT-RADS categories based on previously described magnetic resonance imaging features and consensus of expert musculoskeletal radiologists. World Health Organization classification was used, and a wide spectrum of benign and malignant osseous tumors was evaluated. Magnetic resonance imaging categories were as follows: OT-RADS 0-incomplete imaging; OT-RADS I-negative; OT-RADS II-definitely benign; OT-RADS III-probably benign; OT-RADS IV-suspicious for malignancy or indeterminate; OT-RADS V-highly suggestive of malignancy; and OT-RADS VI-known biopsy-proven malignancy or recurrent malignancy in the tumor bed. Four blinded readers categorized each tumor according to OT-RADS classification. Intraclass correlation (ICC) and Conger κ were used. Diagnostic performance measures including area under the receiver operating curve were reported. Osseous Tumor Reporting and Data System was dichotomized as benign (I-III) and malignant (IV and V) for calculating sensitivity and specificity.

RESULTS

Interreader agreement for OT-RADS (ICC = 0.78) and binary distinction of benign versus malignant (κ = 0.67) were good to excellent, while agreement for individual tumor feature characteristics were poor to fair (ICC = 0.25-0.36; κ = 0.16-0.39). The sensitivities, specificities, and area under the receiver operating curve of the readers ranged from 0.93-1.0, 0.71-0.86, and 0.92-0.97, respectively.

CONCLUSIONS

Osseous Tumor Reporting and Data System lexicon is reliable and helps stratify tumors into benign and malignant categories. It can be practically used by radiologists to guide patient management, improve multidisciplinary communications, and potentially impact outcomes.

Imaging biomarkers for evaluating tumor response: RECIST and beyond

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

Evaluation of the Predictive Potential of 18F-FDG PET and DWI Data Sets for Relevant Prognostic Parameters of Primary Soft-Tissue Sarcomas

BACKGROUND

To evaluate the potential of simultaneously acquired 18F-FDG PET- and MR-derived quantitative imaging data sets of primary soft-tissue sarcomas for the prediction of neoadjuvant treatment response, the metastatic status and tumor grade.

METHODS

A total of 52 patients with a high-risk soft-tissue sarcoma underwent a 18F-FDG PET/MR examination within one week before the start of neoadjuvant treatment. For each patient, the maximum tumor size, metabolic activity (SUVs), and diffusion-restriction (ADC values) of the tumor manifestations were determined. A Mann-Whitney-U test was used, and ROC analysis was performed to evaluate the potential to predict histopathological treatment response, the metastatic status or tumor grade. The results from the histopathological analysis served as reference standard.

RESULTS

Soft-tissue sarcomas with a histopathological treatment response revealed a significantly higher metabolic activity than tumors in the non-responder group. In addition, grade 3 tumors showed a significant higher 18F-FDG uptake than grade 2 tumors. Furthermore, no significant correlation between the different outcome variables and tumor size or calculated ADC-values could be identified.

CONCLUSION

Measurements of the metabolic activity of primary and untreated soft-tissue sarcomas could non-invasively deliver relevant information that may be used for treatment planning and risk-stratification of high-risk sarcoma patients in a pretherapeutic setting.

Shear-wave velocity for colorectal cancer liver metastases as a potential prognostic factor after chemotherapy: a preliminary study

AIM

To evaluate whether shear-wave velocity (SWV) can be used for predicting the prognoses of patients with colorectal cancer liver metastases (CRLMs) after chemotherapy.

MATERIALS AND METHODS

Our institutional review board approved this prospective study, and written informed consent was obtained. SWV of CRLMs were obtained using point shear-wave elastography using acoustic radiation force impulse from 25 patients prior to and 2, 7, and 14 days after chemotherapy. Progression-free survival (PFS) after chemotherapy was estimated using the Kaplan-Meier method. The Cox proportional hazard regression model was used to determine significant predictive factors for PFS. For measurement reproducibility, an additional 37 patients with CRLMs were enrolled and assessed using intraclass correlation coefficients (ICCs).

RESULTS

After chemotherapy, 10 and 15 patients were classified into responder and non-responder groups, respectively. The estimated 1- and 3-year PFS values in the whole cohort were 36% and 8%, respectively. A decrease in the SWV value on day 2 relative to the initial value was a significant predictive factor for better PFS outcome (hazard ratio = 0.20, 95% confidence interval = 0.07-0.57, p=0.003). The estimated 1 and 3-year PFS rates were 66.7% and 22.2%, respectively, in nine patients with decreased SWV values on day 2 and significantly higher than 18.8% and 0% of 16 patients with increased SWV values on day 2. The ICC value of SWV of CRLMs in the additional 37 patients was 0.823 (95% CI = 0.685-0.905), indicating good agreement.

CONCLUSION

SWV values of CRLMs could provide prognostic information in patients with CRLMs treated with chemotherapy, as decreased SWV values on day 2 after chemotherapy was a significant predictive factor for better PFS.

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.

Prognostic value of tumoral and peritumoral magnetic resonance parameters in osteosarcoma patients for monitoring chemotherapy response

Objectives

To evaluate parameters of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as early imaging indicators of tumor histologic response to pre-operative neoadjuvant chemotherapy and as probable prognostic factors for event-free survival (EFS) and overall survival in osteosarcoma (OS) in both tumoral and peritumoral areas.

Methods

Thirty-four OS patients who received three courses of neoadjuvant chemotherapy followed by surgery during 2014–2018 were enrolled in this study. All patients underwent baseline and post-chemotherapy DWI and DCE-MRI. Lesion region was defined as the tumoral area and peritumoral area. Parameters of apparent diffusion coefficient, capacity transfer constant (Ktrans), elimination rate constant, extravascular extracellular space volume ratio (Ve), and initial area under the curve as well as corresponding differences between pre- and post-chemotherapy in lesion regions were evaluated. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of these parameters. The associations of all parameters with tumor histologic response, EFS, and overall survival were also calculated.

Results

In the tumor area, moderate evidence was found that post-Ktrans was lower in responders as compared with that in poor responders (p = 0.04, false discovery rate [FDR] corrected), and ΔKtrans exhibited significant between-groups differences (p = 0.04, Bonferroni corrected; or p = 0.006, FDR corrected). Weak evidence for the between-groups difference was found in the Ve in the peritumoral area (p = 0.025 before treatment and p = 0.021 after treatment, uncorrected). Furthermore, lower post-Ktrans in the tumoral area and lower pre-Ve in the peritumoral area were significant prognostic indicators for longer EFS (p = 0.002, p = 0.026) and overall survival (p = 0.003, p = 0.023).

Conclusions

In OS, DWI and DCE-MRI parameters in both tumoral and peritumoral areas can reflect the chemotherapy response and prognosticate EFS and overall survival.

Key Points

• Peritumoral MRI parameters can reflect the chemotherapy response in OS patients.

• Peritumoral MRI parameters can predict EFS and overall survival in OS patients.

• MRI parameters may be predictive factors for evaluating chemotherapy efficacy and EFS.

The Role of Diffusion-weighted Imaging in Patients with Gastric Wall Thickening

BACKGROUND

Gastric cancer is the second leading cause of cancer death worldwide.

AIMS

In the benign and malign gastric pathologies, we measured the Apparent Diffusion Coefficient (ADC) value from the thickened section of the stomach wall. We assessed the diagnostic value of ADC and we wanted to see whether this value could be used to diagnose gastric pathologies.

STUDY DESIGN

This study has a prospective study design.

METHODS

A total of 90 patients, 27 with malign gastric pathologies 63 with benign gastric pathologies with Gastric Wall (GW) thickening in multidector CT, were evaluated by T2 weighted axial MR imaging and Diffusion-Weighted Imaging (DWI). Measurements were made both from the thickened wall and from the normal GW. Also, a new method called GW/spine ADC ratio was performed in image analysis. The value found after ADC measurement from the GW was proportioned to the spinal cord ADC value in the same section.

RESULTS

The ADC values measured from the pathological wall in patients with gastric malignancy (1.115 ± 0.156 x10-3 mm2/s) were significantly lower than the healthy wall measurements (1.621 ± 0.292 × 10-3 mm2/s) and benign gastric diseases (1.790± 0.359 x10-3 mm2/s). GW/spine ADC ratio was also lower in gastric malignancy group.

CONCLUSION

ADC measurement in DWI can be used to distinguish between benign and malign gastric pathologies.

Quantitative Musculoskeletal Tumor Imaging

The role of quantitative magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) techniques continues to grow and evolve in the evaluation of musculoskeletal tumors. In this review we discuss the MRI quantitative techniques of volumetric measurement, chemical shift imaging, diffusion-weighted imaging, elastography, spectroscopy, and dynamic contrast enhancement. We also review quantitative PET techniques in the evaluation of musculoskeletal tumors, as well as virtual surgical planning and three-dimensional printing.

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.

Analysis of Apparent Diffusion Coefficients of the Brain in Healthy Controls: A Comparison Study between Single-Shot Echo-Planar Imaging and Read-out-Segmented Echo-Planar Imaging

OBJECTIVE

To compare apparent diffusion coefficients (ADCs) of brain segments by using two diffusion-weighted imaging acquisition modes, single-shot echo-planar imaging (ss-EPI) and read-out-segmented echo-planar imaging (rs-EPI), and to assess their correlation and agreement in healthy controls.

MATERIALS AND METHODS

T2-weighted (T2W) images, rs-EPI, and ss-EPI of 30 healthy subjects were acquired using a 3T magnetic resonance scanner. The T2W images were co-registered to the rs-EPI and ss-EPI, which were then segmented into the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) to generate masking templates. ADC maps of rs-EPI and ss-EPI were also segmented into the GM, WM, and CSF by using the generated templates. ADCs of rs-EPI and ss-EPI were compared using Student's t tests and correlated using Pearson's correlation coefficients. Bland-Altman plots were used to assess the agreement between acquisitions.

RESULTS

ADCs of rs-EPI and ss-EPI were significantly different in the GM (p < 0.001) and WM (p < 0.001). ADCs showed high agreement and correlation in the whole brain and CSF (r > 0.988; p < 0.001). ADC of the WM showed the least correlation (r = 0.894; p < 0.001), and ADCs of the WM and GM showed poor agreement. Pearson's correlation equations for each brain segment were y = 1.1x - 59.4 (GM), y = 1.45x - 255 (WM), and y = 0.98x - 63.5 (CSF), where x and y indicated ADCs of rs-EPI and ss-EPI, respectively.

CONCLUSION

While ADCs of rs-EPI and ss-EPI showed high correlation and agreement in the whole brain and CSF, ADCs of the WM and GM showed significant differences and large variability, reflecting brain parenchymal inhomogeneity due to different regional microenvironments. ADCs of different acquisition methods should be interpreted carefully, especially in intra-individual comparisons.

Development and external validation of an MRI-based radiomics nomogram for pretreatment prediction for early relapse in osteosarcoma: A retrospective multicenter study

PURPOSE

To develop and externally validate an MR-based radiomics nomogram from retrospective multicenter datasets for pretreatment prediction of early relapse (≤ 1 year) in osteosarcoma after surgical resection.

METHODS

This multicenter study retrospectively enrolled 93 patients (training cohort: 62 patients from four hospitals; validation cohort: 31 patients from two hospitals) with clinicopathologically confirmed osteosarcoma who received neoadjuvant chemotherapy and surgical resection at six hospitals between January 2009 and October 2017. Radiomics features were extracted from contrast-enhanced fat-suppressed T1-weighted (CE FS T1-w) images. Least absolute shrinkage and selection operator (LASSO) regression was applied for feature selection and radiomics signature construction. The radiomics nomogram that incorporated the radiomics signature and subjective MRI-assessed candidate predictors was developed to predict early relapse with a multivariate logistic regression model in the training cohort and validated in the external validation cohort. The performance of the nomogram was assessed by its discrimination, calibration, and clinical usefulness.

RESULTS

The radiomics signature comprised six selected features and achieved favorable prediction efficacy. The radiomics nomogram incorporating the radiomics signature and subjective MRI-assessed candidate predictors (joint invasion and perivascular involvement) from the multicenter datasets achieved better discrimination in the training cohort (C-index：0.907, 95 % CI: 0.838-0.977) and external validation cohort (C-index: 0.811, 95 % CI: 0.653-0.970), and good calibration. Decision curve analysis suggested that the combined nomogram was clinically useful.

CONCLUSION

The proposed MRI-based radiomics nomogram could provide a non-invasive tool to predict early relapse of osteosarcoma, which has the potential to improve personalized pretreatment management of osteosarcoma.

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.

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

PURPOSE

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

[Bone tumors and metastases: tips for initial diagnosis and follow-up : Update 2019]

Benign bone tumors are frequently discovered as incidental findings, whereas malignant tumors and metastases often become clinically noticeable due to pain or swelling. The initial radiological diagnostics by conventional X‑ray imaging, magnetic resonance imaging (MRI) and computed tomography (CT) play an important role in the assessment of dignity and further treatment planning. The aftercare of bone tumors is necessary for the recognition of recurrences and distant metastases as well as the detection of complications, e.g. after implantation of a prosthesis. Implanted metal and posttherapeutic alterations can impede the aftercare due to artifacts and treatment-associated tissue alterations. In addition to the recommendations of the Association of the Scientific Medical Societies in Germany (AWMF), the European Organisation for Research and Treatment of Cancer (EORTC) and the European Society of Musculoskeletal Radiology (ESSR), study protocols can be used as orientation for the aftercare of individual primary malignant bone 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.

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.

Combined dynamic DCE-MRI and diffusion-weighted imaging to evaluate the effect of neoadjuvant chemotherapy in cervical cancer

PURPOSE

To prospectively investigate changes in quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and the apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) in patients with cervical cancer before and after neoadjuvant chemotherapy (NACT).

METHODS

Thirty-eight patients with cervical cancer underwent DCE-MRI and DWI 1 week before and 4 weeks after NACT. The patients were classified into 2 groups: significant reaction (sCR) group and the non-sCR group. DCE-MRI parameters and ADC values were measured and compared between the 2 groups.

RESULTS

Before NACT, the mean K^trans value was higher, but the mean V_e was lower, in the sCR group compared with the non-sCR group; these differences were statistically significant (p<0.05). After NACT, the mean K^trans value and the delta (i.e., changed) value of K^trans were significantly lower in the sCR group compared with the non-sCR group (p<0.05). However, the mean ADC and the delta value of the mean ADC between the 2 groups were slightly higher in the sCR group compared with the non-sCR group (p<0.05). The area under the curve of pre-mean K^trans, DK^trans, and pre-mean K^trans combined with post-mean ADC values were 0.801, 0.955, and 0.878, respectively (p<0.05). The optimal cutoff values for distinguishing sCR from non-sCR were pretreatment K^trans (0.7020 min^-1) and DK^trans (0.0437 min^-1).

CONCLUSIONS

Quantitative parameters (pre-mean K^trans, DK^trans, and pre-mean K^trans) combined with post-mean ADC could predict treatment efficacy more precisely. However, quantitative DCE-MRI combined with DWI could not significantly improve prognostic efficacy.

Usefulness of diffusion-weighted MRI in the initial assessment of osseous sarcomas in children and adolescents

BACKGROUND

Concern regarding gadolinium deposition in the brain after repeated administration of intravenous gadolinium-based contrast agents has prompted evaluation of imaging alternatives.

OBJECTIVE

The study purpose was to determine if magnetic resonance imaging (MRI) using conventional sequences with diffusion-weighted imaging (DWI) instead of gadolinium-based contrast-enhanced MRI is valid for local staging and guiding biopsies in osseous sarcomas.

MATERIALS AND METHODS

Initial pretreatment MRI with DWI and gadolinium-based contrast-enhanced images in patients ≤ 18 years with histopathologically proven osseous sarcomas were included. Two radiologists blinded to collated demographic and clinical data, independently reviewed conventional/DWI and conventional/gadolinium-based contrast-enhanced MRI then conventional sequences alone, recording tumor size, skip lesions, necrosis, neurovascular invasion, enlarged lymph nodes and diffusion restriction. Discrepancies were resolved by a third reader. A single reader measured apparent diffusion coefficient (ADC) values in non-necrotic tumors, then correlated minimum ADC values -- with and without normalization to skeletal muscle -- with relative enhancement.

RESULTS

Twenty-one patients (mean age: 11.3±4.2 years, 15 [71%] females) had 14 osteosarcomas and 7 Ewing sarcomas, 50% centered in the femur. Conventional/DWI versus conventional/gadolinium-based contrast-enhanced MRI showed agreement for tumor size estimation with significant associations for necrosis (P=0.021), neurovascular involvement (P<0.001) and enlarged lymph nodes (P=0.005). Diagnostic accuracy of conventional/DWI is comparable to conventional/gadolinium-based contrast-enhanced MRI and superior to conventional sequences alone. Comparison between minimum ADC values and relative enhancement showed no correlation (P>0.05).

CONCLUSION

Significant associations of key imaging features in the initial assessment of osseous sarcomas support DWI as an alternative to gadolinium-based contrast-enhanced MRI. The lack of association between ADC values and relative enhancement suggests that they measure independent constructs, DWI dependent upon tumor cellularity and perfusion.

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.

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.

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.

New challenges in integrated diagnosis by imaging and osteo-immunology in bone lesions

INTRODUCTION

High-resolution imaging is the gold standard to measure the functional and biological features of bone lesions. Imaging markers have allowed the characterization both of tumour heterogeneity and metabolic data. Besides, ongoing studies are evaluating a combined use of 'imaging markers', such as SUVs, MATV, TLG, ADC from PET and MRI techniques respectively, and several 'biomarkers' spanning from chemokine immune-modulators, such as PD-1, RANK/RANKL, CXCR4/CXCL12 to transcription factors, such as TP53, RB1, MDM2, RUNX family, EZH2, YY1, MAD2. Osteoimmunology may improve diagnosis and prognosis leading to precision medicine in bone lesion treatment. Areas covered: We investigated modalities (molecular and imaging approach) useful to identify bone lesions deriving both from primary bone tumours and from osteotropic tumours, which have a higher incidence, prevalence and prognosis. Here, we summarized the recent advances in imaging techniques and osteoimmunology biomarkers which could play a pivotal role in personalized treatment. Expert commentary: Although imaging and molecular integration could allow both early diagnosis and stratification of cancer prognosis, large scale clinical trials will be necessary to translate pilot studies in the current clinical setting.

ABBREVIATIONS

ADC: apparent diffusion coefficient; ALCAM: Activated Leukocyte Cell Adhesion Molecule; ALP: Alkaline phosphatases; BC: Breast cancer; BSAP: B-Cell Lineage Specific Activator; BSAP: bone-specific alkaline phosphatase; BSP: bone sialoprotein; CRIP1: cysteine-rich intestinal protein 1; CD44: cluster of differentiation 44; CT: computed tomography; CXCL12: C-X-C motif ligand 12; CXCR4: C-X-C C-X-C chemokine receptor type 4; CTLA-4: Cytotoxic T-lymphocyte antigen 4; CTX-1: C-terminal end of the telopeptide of type I collagen; DC: dendritic cell; DWI: Diffusion-weighted MR image; EMT: mesenchymal transition; ET-1: endothelin-1; FDA: Food and Drug Administration; FDG: ¹⁸F-2-fluoro-2-deoxy-D-glucose; FGF: fibroblast growth factor; FOXC2: forkhead box protein C2: HK-2: hexokinase-2; ICTP: carboxyterminal cross-linked telopeptide of type I collagen; IGF-1R: Insulin Like Growth Factor 1 Receptor; ILC: innate lymphocytes cells; LC: lung cancer; IL-1: interleukin-1; LYVE1: lymphatic vessel endothelial hyaluronic acid receptor 1; MAD2: mitotic arrest deficient 2; MATV: metabolically active tumour volume; M-CSF: macrophage colony stimulating factor; MM: multiple myeloma; MIP1a: macrophage inflammatory protein 1a; MSC: mesenchymal stem cell; MRI: magnetic resonance imaging; PC: prostate cancer; NRP2: neuropilin 2; OPG: osteoprotogerin; PDGF: platelet-derived growth factor; PD-1: Programmed Cell Death 1; PET: positron emission tomography; PINP: procollagen type I N propeptide; PROX1: prospero homeobox protein 1; PSA: Prostate-specific antigen; PTH: parathyroid hormone; RANK: Receptor activator of NF-kB ligand; RECK: Reversion-inducing-cysteine-rich protein; SEMAs: semaphorins; SPECT: single photon computed tomography; SUV: standard uptake value; TLG: total lesion glycolysis; TP53: tumour protein 53; VCAM-1: vascular endothelial molecule-1; VOI: volume of interest; YY1: Yin Yang 1.

Adeno-associated virus 2 mediated gene transfer of vascular endothelial growth factor Trap: a new treatment option for glioma

Background: Adeno-associated virus 2 mediated gene transfer of vascular endothelial growth factor Trap (AAV2-VEGF-Trap) has been reported to inhibit the growth of primary tumor as well as distant metastasis in 4T1 metastatic breast cancer models. The aim of this study was to investigate the inhibiting efficacy of AAV2-VEGF-Trap for glioma.

Methods: The intracranial transplanted model of glioma in rats was established. They were treated with AAV2-VEGF-Trap, bevacizumab (BEV), temozolomide (TMZ), TMZ combined with AAV2-VEGF-Trap, TMZ combined with BEV and the control group, respectively. A 7.0 Tesla magnetic resonance (MR) was used to assess the tumor volumes and obtain the apparent diffusion coefficient (ADC) values. Immunohistochemical and terminal dexynucleotidyl transferase (TdT)-mediated dUTP nick end labeling (TUNEL) staining were used to evaluate the effects on tumor angiogenesis, proliferation and apoptosis.

Results: The combination of TMZ with AAV2-VEGF-Trap or BEV showed greater tumor growth inhibition than the other groups, and the ADC values in these two groups were larger than that of the control group. The decreased microvessel density in treatment groups which contain AAV2-VEGF-Trap or BEV was observed. The reduced proliferation activity in groups containing TMZ and increased apoptotic tumor cells in TMZ combined with AAV2-VEGF-Trap group and TMZ combined with BEV group were detected. In addition, there were no differences in antitumor effect, ADC values, Ki-67 and CD31 staining and apoptosis analysis between the two combined therapy groups.

Conclusion: AAV2-VEGF-Trap has an obvious anti-angiogenic effect and inhibits the growth of glioma just by a single intravenous injection, which is similar to BEV. Moreover, there is a synergistic antitumor effect between AAV2-VEGF-Trap and TMZ.

Discriminating Depth of Response to Therapy in Multiple Myeloma Using Whole-body Diffusion-weighted MRI with Apparent Diffusion Coefficient: Preliminary Results From a Single-center Study

RATIONALE AND OBJECTIVES

This study aimed to measure apparent diffusion coefficient (ADC) in Chinese patients with newly diagnosed multiple myeloma by whole-body diffusion-weighted magnetic resonance imaging (WB-DWI MRI) and assess the diagnostic accuracy of ADC in the discrimination of deep response to induction chemotherapy.

MATERIALS AND METHODS

Seventeen patients underwent WB-DWI MRI before and after induction chemotherapy (week 20). DWI images and ADC maps were produced and 89 regions of interest were chosen. ADC percent changes were compared between deep (complete response or very good partial response) and non-deep responders (partial response, minimal response, stable disease, or progressive disease) as International Myeloma Working Group criteria. Diagnostic accuracy of ADC was calculated using specific cut offs. Predictive positive value of ADC was calculated to predict deep response to consolidation therapy.

RESULTS

Lesions reduced in size and number and signal intensity decreased in follow-up DWI, which did not differ between deep and non-deep responders. ADC percent changes were significantly higher in deep responders (36.79%) than in non-deep responders (11.50%) after induction therapy (P = .02) in per lesion analysis. ADC percent increases by 46.96%, 78.0% yielded specificity at 81.4%, 90.7% in discriminating deep response to induction therapy. Predictive positive value predicting deep response to consolidation therapy was 60.5% by using ADC cutoff >1.00 × 10^-3 mm²/s at week 20.

CONCLUSIONS

ADC from WB-DWI MRI increased remarkably in patients who achieved deep response at the end of induction chemotherapy, which represented a confirmatory diagnostic tool to discriminate deep response to induction therapy for patients with multiple myeloma. ADC may have a potential to predict deep response to consolidation therapy.

Correlation of ADC With Pathological Treatment Response for Radiation Therapy of Pancreatic Cancer

PURPOSE: To investigate the feasibility of using apparent diffusion coefficient (ADC) to assesspathological treatment response in pancreatic ductal adenocarcinoma (PDAC) following neoadjuvant chemoradiation (nCR). MATERIALS/METHODS: MRI and pathological data collected for 25patients with resectable and borderline resectable PDAC following nCR were retrospectively analyzed. Pre- and post-nCR mean ADC values in the tumors were compared using Wilcoxon matched pairs test. Correlation of pathological treatment response and ADC values was assessed using Pearson’s correlation coefficient test and receiver-operating-curve (ROC) analysis. RESULTS: The average mean and standard deviation (SD) of the ADC values for all the patients analyzed were significantly higher in post-nCR (1.667±0.161×10^-3) compared with those prior to nCR (1.395±0.136×10^-3 mm²/sec), (P<0.05). The mean ADC values after nCR were significantly correlated with the pathological responses (r=-0.5172); P=0.02. The area under the curve (AUC) of the ADC values for differentiating G1, G2 and G3 pathological responses, using ROC analysis, was found to be 0.6310 and P=0.03. CONCLUSION: Changes of pre- and post-treatment ADC values significantly correlated with pathological treatment response for PDAC patients treated with chemoradiation therapy, indicating that the ADC could be used to assesstreatment response for PDAC.