MRI biomarkers in osseous tumors

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.

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.

Fat quantification: Imaging methods and clinical applications in cancer

Recently, the study of the relationship between lipid metabolism and cancer has evolved. The characteristics of intratumoral and peritumoral fat are distinct and changeable during cancer development. Subcutaneous and visceral adipose tissue are also associated with cancer prognosis. In non-invasive imaging, fat quantification parameters such as controlled attenuation parameter, fat volume fraction, and proton density fat fraction from different imaging methods complement conventional images by providing concrete fat information. Therefore, measuring the changes of fat content for further understanding of cancer characteristics has been applied in both research and clinical settings. In this review, the authors summarize imaging advances in fat quantification and highlight their clinical applications in cancer precaution, auxiliary diagnosis and classification, therapy response monitoring, and prognosis.

Bone marrow MR perfusion imaging and potential for tumor evaluation

The physiology of bone perfusion is reviewed outlining how it can be measured with dynamic contrast-enhanced MRI as well as intravoxel incoherent imaging. Evaluation of bone perfusion provides a potential means of assessing tumor activity and treatment response beyond that possible with standard MR imaging.

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.

Apparent diffusion coefficient (ADC): A potential in vivo biological surrogate of the incidentally discovered bone lesions at 3T MRI

PURPOSE

To probe the potential of apparent diffusion coefficient (ADC) to rectify the incidentally detected bone lesion on MRI into benign or malignant lesions.

MATERIALS AND METHODS

We retrospectively recruited 44 patients (24 males and 20 females); with 52 bone lesions, who underwent diffusion weighted (DW) imaging using multiple b-values on 3 T MRI. ADC maps were derived and analyzed by two radiologists; blinded to the final diagnosis. The mean ADC values were used for statistical analyses. The diagnosis was deduced by histopathological confirmation; in 32 lesions and strict clinical and imaging follow-up for at least 12 months; in 20 lesions.

RESULTS

The mean ADC value (mean±SD) of all malignant tumors (including cartilaginous neoplasms) was [0.92 ± 0.40] × 10-3 mm2/s. This significantly differed from those of both primary benign tumors [1.14 ± 0.24] × 10-3 mm2/s, (p = 0.011), and all non-malignant lesions collectively [1.29 ± 0.44] × 10-3 mm2/s, (p < 0.001). Using mADC value of ≤ 1.1 × 10-3 mm2/s resulted in 86.1% sensitivity and 62.5% specificity for characterizing a lesion as a malignant. The inter-rater reliability was almost perfect (95% CI = 0.954-0.985).

CONCLUSION

ADC could be a non-invasive in-vivo surrogate that may be able to discern the incidentally discovered osseous lesions into benign and malignant pathologies and guide further diagnostic workup.

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.

An update in musculoskeletal tumors: from quantitative imaging to radiomics

In the last two decades, relevant progress has been made in the diagnosis of musculoskeletal tumors due to the development of new imaging tools, such as diffusion-weighted imaging, diffusion kurtosis imaging, magnetic resonance spectroscopy, and diffusion tensor imaging. Another important role has been played by the development of artificial intelligence software based on complex algorithms, which employ computing power in the detection of specific tumor types. The aim of this article is to report the most advanced imaging techniques focusing on their advantages in clinical practice.

Free radical imaging of endogenous redox molecules using dynamic nuclear polarisation magnetic resonance imaging

Redox reactions accompanied by the oxidation-reduction of endogenous molecules play important roles in maintaining homeostasis in living organisms. In humans, numerous endogenous molecules that contribute towards maintaining physiological conditions form free radicals via electron transfer. A typical example of this is the mitochondrial electron transport chain, which is involved in energy production. If free radicals derived from endogenous molecules could be visualised and exploited as biological and functional probes, redox reactions mediated by endogenous molecules could be detected non-invasively. We succeeded in visualising the free radicals derived from endogenous molecules using an in vivo dynamic nuclear polarisation (DNP) magnetic resonance imaging (MRI) system. In this review, we describe the visualisation of endogenous redox molecules, such as flavins and ubiquinones, which are mitochondrial electron carriers, as well as vitamin E and vitamin C (ascorbate). In addition, we describe the application of melanin free radicals for the in vivo visualisation of metabola without using probes via in vivo DNP-MRI.

Sarcoma treatment in the era of molecular medicine

Sarcomas are heterogeneous and clinically challenging soft tissue and bone cancers. Although constituting only 1% of all human malignancies, sarcomas represent the second most common type of solid tumors in children and adolescents and comprise an important group of secondary malignancies. More than 100 histological subtypes have been characterized to date, and many more are being discovered due to molecular profiling. Owing to their mostly aggressive biological behavior, relative rarity, and occurrence at virtually every anatomical site, many sarcoma subtypes are in particular difficult-to-treat categories. Current multimodal treatment concepts combine surgery, polychemotherapy (with/without local hyperthermia), irradiation, immunotherapy, and/or targeted therapeutics. Recent scientific advancements have enabled a more precise molecular characterization of sarcoma subtypes and revealed novel therapeutic targets and prognostic/predictive biomarkers. This review aims at providing a comprehensive overview of the latest advances in the molecular biology of sarcomas and their effects on clinical oncology; it is meant for a broad readership ranging from novices to experts in the field of sarcoma.

Diffusion-Weighted MRI to Assess Sacroiliitis: Improved Image Quality and Diagnostic Performance of Readout-Segmented Echo-Planar Imaging (EPI) Over Conventional Single-Shot EPI

BACKGROUND. DWI using single-shot echo-planar imaging (ss-EPI) is prone to artifacts, signal-intensity dropout, and T2* blurring. Readout-segmented echo-planar imaging (rs-EPI) may improve image quality in DWI of the sacroiliac joints. OBJECTIVE. The purposes of this study were, first, to qualitatively and quantitatively compare image quality between ss-EPI and rs-EPI DWI of the sacroiliac joints; and, second, to evaluate whether ADC values derived from ss-EPI and rs-EPI can differentiate disease activity in patients with axial spondyloarthritis (axSpA). METHODS. This retrospective study included 75 patients who underwent ss-EPI and rs-EPI DWI of the sacroiliac joints. Patients were classified into axSpA (n = 50) and no-ax-SpA (n = 25) groups on the basis of Assessment of SpondyloArthritis International Society (ASAS) criteria. Patients in the axSpA group were assigned to one of four disease activity states using the Ankylosing Spondylitis Disease Activity Score-C-reactive protein (ASDAS-CRP). Two radiologists independently assessed qualitative (overall image quality and diagnostic confidence) and quantitative (ADC, signal-to-noise ratio [SNR], and contrast-to-noise ratio [CNR]) imaging parameters. RESULTS. Readout-segmented EPI provided significantly better overall image quality, diagnostic confidence, SNR, and CNR than ss-EPI (both readers, p < .001). In patients with axSpA, the correlation coefficients (r) of ADC values and ASDAS-CRP values were 0.456 and 0.458 for ss-EPI and 0.537 and 0.558 for rs-EPI. ADCs showed progressive increases with increasing activity state for both sequences, although these increases were more substantial for rs-EPI than for ss-EPI. Across readers, median ADCs for ss-EPI were 0.243 and 0.234 × 10^-3 mm²/s for inactive disease, 0.411 and 0.412 × 10^-3 mm²/s for moderate disease activity, 0.499 and 0.447 × 10^-3 mm²/s for high activity, and 0.671 and 0.575 × 10^-3 mm²/s for very high activity (reader 1, p = .011; reader 2, p = .010). Across readers, ADCs for rs-EPI were 0.236 and 0.236 × 10^-3 mm²/s for inactive disease, 0.483 and 0.477 × 10^-3 mm²/s for moderate disease activity, 0.727 and 0.692 × 10^-3 mm²/s for high activity, and 0.902 and 0.803 × 10^-3 mm²/s for very high activity (reader 1, p = .002; reader 2, p = .001). ADC values for ss-EPI were significantly different only between the inactive and very high disease activity groups (p < .0083, Bonferroni-corrected threshold). ADC values for rs-EPI were significantly different between the inactive and high, inactive and very high, as well as the moderate and very high disease activity groups (p < .0083, Bonferroni-corrected threshold). CONCLUSION. Readout-segmented EPI significantly improves the image quality of DWI in imaging the sacroiliac joints. In patients with axSpA, activity states are better differentiated by rs-EPI than by ss-EPI. CLINICAL IMPACT. Readout-segmented EPI is a more robust tool than ss-EPI for imaging of axSpA and should be included in routine clinical protocols for MRI of the sacroiliac joints.

Diffusion-Weighted Imaging in Oncology: An Update

To date, diffusion weighted imaging (DWI) is included in routine magnetic resonance imaging (MRI) protocols for several cancers. The real additive role of DWI lies in the "functional" information obtained by probing the free diffusivity of water molecules into intra and inter-cellular spaces that in tumors mainly depend on cellularity. Although DWI has not gained much space in some oncologic scenarios, this non-invasive tool is routinely used in clinical practice and still remains a hot research topic: it has been tested in almost all cancers to differentiate malignant from benign lesions, to distinguish different malignant histotypes or tumor grades, to predict and/or assess treatment responses, and to identify residual or recurrent tumors in follow-up examinations. In this review, we provide an up-to-date overview on the application of DWI in oncology.