Diagnosis of non-osseous spinal metastatic disease: the role of PET/CT and PET/MRI

Retroperitoneal alveolar rhabdomyosarcoma intruding into spinal canal: A case report and literature review

Background

Rhabdomyosarcoma (RMS) is the most frequent soft sarcoma in children and adolescents. Alveolar rhabdomyosarcoma (ARMS) is a relatively rare subtype that is characterized by aggressive behavior and an unsatisfactory prognosis. An ARMS can arise anywhere but most commonly occurs at extremity sites with a very small fraction in the retroperitoneum. The utility of 2-Deoxy-2-[fluorine-18]-fluoro-D-glucose (18F-FDG) positron emission tomography combined with computed tomography (PET/CT) remains to be established in ARMS.

Case Report

A 3-year-old female child was accidentally found with a large left upper abdominal mass for a day. CT examination indicated a huge soft tissue mass in the left retroperitoneum extending superiorly to the level of the left hilus renalis and inferiorly to the left acetabulum in the pelvic cavity, with intrusion into the lumbar foramens. 18F-FDG PET/CT found a mass in the left retroperitoneum from the level of T12 to the left acetabulum, with the maximum standardized uptake value (SUVmax) of about 7.0, and a CT value of about 39 HU, invading the left L3-5 intervertebral foramina and protruding into the spinal canal, with unclear boundary with the spinal cord. Retroperitoneal tumor resection and the repair operation of vascular exploration were performed. An ARMS was confirmed by postoperative biopsy, immunohistochemical staining, and genetic detection with the rupture of the fork head in rhabdomyosarcoma (FKHR). The patient received chemotherapy and was in a good condition with no recurrence and obvious complications.

Conclusion

Retroperitoneal ARMS is rare and indicates a poor outcome with the potential to involve vital organs and intrude into the spinal canal. Accurate diagnosis and staging using PET/CT would contribute to better risk stratifications and appropriate treatment individually.

State-of-the-Art Imaging Techniques in Metastatic Spinal Cord Compression

Metastatic Spinal Cord Compression (MSCC) is a debilitating complication in oncology patients. This narrative review discusses the strengths and limitations of various imaging modalities in diagnosing MSCC, the role of imaging in stereotactic body radiotherapy (SBRT) for MSCC treatment, and recent advances in deep learning (DL) tools for MSCC diagnosis. PubMed and Google Scholar databases were searched using targeted keywords. Studies were reviewed in consensus among the co-authors for their suitability before inclusion. MRI is the gold standard of imaging to diagnose MSCC with reported sensitivity and specificity of 93% and 97% respectively. CT Myelogram appears to have comparable sensitivity and specificity to contrast-enhanced MRI. Conventional CT has a lower diagnostic accuracy than MRI in MSCC diagnosis, but is helpful in emergent situations with limited access to MRI. Metal artifact reduction techniques for MRI and CT are continually being researched for patients with spinal implants. Imaging is crucial for SBRT treatment planning and three-dimensional positional verification of the treatment isocentre prior to SBRT delivery. Structural and functional MRI may be helpful in post-treatment surveillance. DL tools may improve detection of vertebral metastasis and reduce time to MSCC diagnosis. This enables earlier institution of definitive therapy for better outcomes.

[18F]FDG-PET Evaluation of Spinal Pathology in Patients in Oncology: Pearls and Pitfalls for the Neuroradiologist

[¹⁸F]FDG-PET is a widely used technique for specific evaluation of disease and treatment response in oncology. However, the principles behind [¹⁸F]FDG-PET imaging allow a wide-ranging array of benign and malignant pathologies to be identified on both initial and routine surveillance imaging. This is important for clinicians and radiologists, alike, in that effective and accurate evaluation of malignancy and metastatic disease, specifically involving the spine and central nervous system, is crucial. In this article, we review the normal and posttherapy appearance of the spine on [¹⁸F]FDG-PET, the various types and patterns of metastatic disease that involve the spine and spinal cord, and, finally, important spinal pathologies that may mimic malignancy on [¹⁸F]FDG-PET.

Advancements in Positron Emission Tomography/Magnetic Resonance Imaging and Applications to Diagnostic Challenges in Neuroradiology

Since the clinical adoption of magnetic resonance (MR) in medical imaging, MR has proven to be a workhorse in diagnostic neuroradiology, with the ability to provide superb anatomic detail as well as additional functional and physiologic data, depending on the techniques utilized. Positron emission tomography/computed tomography has also shown irreplaceable diagnostic value in certain disease processes of the central nervous system by providing molecular and metabolic information through the development of numerous disease-specific PET tracers, many of which can be utilized as a diagnostic technique in and of themselves or can provide a valuable adjunct to information derived from MR. Despite these advances, many challenges still remain in neuroradiology, particularly in malignancy, neurodegenerative disease, epilepsy, and cerebrovascular disease. Through improvements in attenuation correction, motion correction, and PET detectors, combining the 2 modalities of PET and MR through simultaneous imaging has proven feasible and allows for improved spatial and temporal resolution without compromising either of the 2 individual modalities. The complementary information offered by both technologies has provided increased diagnostic accuracy in both research and many clinical applications in neuroradiology.

Magnetic Resonance Image under Variable Model Algorithm in Diagnosis of Patients with Spinal Metastatic Tumors

The aim of this study was to explore the adoption of the variable model algorithm in magnetic resonance imaging (MRI) image analysis and evaluate the effect of the algorithm-based MRI in the diagnosis of spinal metastatic tumor diseases. 100 patients with spinal metastatic tumors who were treated in hospital were recruited as the research objects. All patients were randomly divided into the experimental group (MRI image analysis based on variable model) and the control group (conventional MRI image diagnosis), and the MRI of the experimental group was segmented using the conventional algorithm with variable model and the improved algorithm with GVF force field. The accuracy index (Dice coefficient D) values were used to evaluate the vertebral segmentation effect of the improved variable model algorithm with the introduction of GVF force field, and the recognition rate, sensitivity, and specificity indexes were used to evaluate the effects of the two algorithms on the recognition of MRI image features of spinal metastatic tumors. The results showed that the mean D value of the variable model improvement algorithm for the segmentation of five vertebrae of spinal metastatic tumors was significantly improved relative to the conventional variable model algorithm, and the difference was statistically significant (P < 0.05). At the number of 80 iterations, the recognition rate, sensitivity, and specificity of MRI image segmentation of the traditional variable model algorithm processing group were 89.32%, 74.88%, and 86.27%, respectively, while the recognition rate, sensitivity, and specificity of MRI image segmentation of the variable model improvement algorithm processing group were 97.89%, 96.75%, and 96.45%, respectively. The results of the latter were significantly better than those of the former, and the differences were statistically significant (P < 0.05); and the comparison of MRI images showed that the variable model improvement algorithm was more rapid and accurate in identifying the focal sites of patients with spinal metastases. The accuracy of MRI images based on the variable model algorithm increased from 69.5% to 92%, and the difference was statistically significant (P < 0.05). In short, MRI image analysis based on the variable model algorithm had great adoption potential in the clinical diagnosis of spinal metastatic tumors and was worthy of clinical promotion.

Total-Body PET Imaging of Musculoskeletal Disorders

Imaging of musculoskeletal disorders, including arthritis, infection, osteoporosis, sarcopenia, and malignancies, is often limited when using conventional modalities such as radiography, computed tomography (CT), and MR imaging. As a result of recent advances in Positron Emission Tomography (PET) instrumentation, total-body PET/CT offers a longer axial field-of-view, higher geometric sensitivity, and higher spatial resolution compared with standard PET systems. This article discusses the potential applications of total-body PET/CT imaging in the assessment of musculoskeletal disorders.

Nuclear Medicine in the diagnosis of pathologies of the spine: role of hybrid imaging

Clinical problems in the human spine are still common in our society, often causing pain and can also limit movement. Back pain is a very common clinical entity, although difficult to diagnose due to its multifactorial nature. There are multiple processes that can alter the structure of the spine, injure vertebrae and/or the surrounding tissue. For the study of the spine, image diagnosis is essential, and within this, molecular hybrid techniques play an important role by providing us with an image of functional and morphological fusion. Among these, SPECT/CT is key in the diagnosis of traumatic and stress pathology, allowing us to locate hidden vertebral fractures, and is also very useful in degenerative and post-surgical pathology. On the other hand, PET/CT with 18F-FDG also plays an important role in the management and monitoring of infectious and oncological processes. This review describes the application of these hybrid techniques in the different pathologies of the spine and the findings of their images, being very useful for the diagnostic assessment and therapeutic management of the patient.

Distribution and predictive value of initial presenting symptoms in spinal metastases from primary cancer patients

PURPOSE

Primary cancer patients may have some symptoms and develop spinal metastases in their disease progression. This study was to report the distribution and predictive value of specific initial presenting symptoms in patients with spine metastatic disease.

METHODS

The clinical information about patients with primary cancers was retrospectively collected and analyzed at their initial diagnosis from January 2008 to December 2017. The distribution and specific value of initial presenting symptoms were analyzed in predicting spinal metastases.

RESULTS

A total of 14,603 cancer patients were finally included, of whom 1665 (11.4%) cases were confirmed with spinal metastases. 41.55% (6067/14,603) patients had initial presenting symptoms, while 92.19% (1535/1665) patients with spinal metastases presented at least one initial presenting symptoms. Among 6269 patients with symptoms, 1535 (24.49%) were diagnosed with spinal metastases. Factors including primary tumor type, local pain, night-aggravating pain, limb numbness, limb weakness, unstable gait, claudication, loss of sphincter control, and weight loss are associated with the distribution of spinal metastases. The pooled sensitivity, specificity, positive predictive value, and negative predictive value were 90.9% (89.4-92.2%), 64.9% (64.0-65.7%), 24.99% (23.91-26.11%), and 98.23% (97.92-98.50%), respectively. Positive likelihood ratio of "night-aggravating pain" was 33.25 (12.65-87.36) and 17.26 (12.25-24.32) in patients < 45 and 45-64 years old, respectively.

CONCLUSIONS

The distribution of spinal metastases is associated with primary tumor type and initial presenting symptoms. The predictive value of initial presenting symptoms differs in age groups, but resembles in cancer types. The presence of night-aggravating pain had relative high value in predicting metastases in cancer patients under 65 years old.

Multimodal Molecular Imaging: Current Status and Future Directions

Molecular imaging has emerged at the end of the last century as an interdisciplinary method involving in vivo imaging and molecular biology aiming at identifying living biological processes at a cellular and molecular level in a noninvasive manner. It has a profound role in determining disease changes and facilitating drug research and development, thus creating new medical modalities to monitor human health. At present, a variety of different molecular imaging techniques have their advantages, disadvantages, and limitations. In order to overcome these shortcomings, researchers combine two or more detection techniques to create a new imaging mode, such as multimodal molecular imaging, to obtain a better result and more information regarding monitoring, diagnosis, and treatment. In this review, we first describe the classic molecular imaging technology and its key advantages, and then, we offer some of the latest multimodal molecular imaging modes. Finally, we summarize the great challenges, the future development, and the great potential in this field.