Radiotherapy Response Assessment of Multiple Myeloma: A Dual-Energy CT Approach With Virtual Non-Calcium Images

Diagnostic accuracy of virtual non-calcium dual-energy computed tomography in the detection of acute occult ankle and calcaneus fractures

Background

Individuals with acute occult ankle and calcaneus fractures usually need to undergo additional magnetic resonance imaging (MRI) to confirm the diagnosis. In some cases, dual-energy computed tomography (DECT) is more convenient and efficient than MRI. This study aimed to assess the diagnostic accuracy of virtual non-calcium (VNCa) DECT in detecting acute occult ankle and calcaneus fractures.

Methods

From January 2022 to February 2024, adult patients presenting with ankle and calcaneal trauma but showing negative or inconclusive results on radiographs were enrolled in this prospective study. Ankle and calcaneus imaging was performed using DECT and MRI. Bone marrow edema (BME) was assessed by consolidating the MRI scan readings. Concurrently, the identification of fractures was conducted by consolidating the DECT and MRI scan readings. The computed tomography (CT) numbers corresponding to BME, fractures, and normal bone marrow in the VNCa images were compared. To determine the optimal cut-off CT number for ascertaining the presence or absence of BME and fractures, a receiver operating characteristic (ROC) curve analysis was conducted.

Results

The cohort comprised 180 participants (average age: 43±14 years; 92 male). In terms of BME detection, DECT had a sensitivity of 92% (96/104) and a specificity of 88% (67/76). In terms of fracture detection, DECT and MRI had a sensitivity of 95% (110/116) and 93% (108/116), respectively, and a specificity of 91% (58/64) and 92% (59/64), respectively. The optimal cut-off CT number for differentiating fractures from normal bone was 26.7 Hounsfield units (HU), which had a sensitivity of 97.3% (144/148) and a specificity of 100% (572/572).

Conclusions

Compared with MRI, VNCa imaging was found to be exceptionally accurate in diagnosing acute occult ankle and calcaneus fractures.

Diagnostic Innovations: Advances in imaging techniques for diagnosis and follow-up of multiple myeloma

Introduction

The International Myeloma Working Group (IMWG) defines myeloma related bone disease (MBD) as a diagnostic criterion for symptomatic multiple myeloma (MM) as the presence of osteolytic lesions ≥ 5 mm or more than one focal lesion (FL) ≥ 5 mm by magnetic resonance imaging (MRI). Whole-body low-dose CT (WBLDCT) is recommended as the first-choice imaging technique for the diagnosis of MBD with 18F-fluorodeoxyglucose-positron emission tomography/CT (18F-FDG-PET/CT) being considered a possible alternative at staging, whereas use of MRI studies is recommended in cases without myeloma-defining events (MDEs) in order to exclude the presence of FLs. Furthermore, use of 18F-FDG-PET/CT is recommended in response assessment, to be integrated with hematologic response and bone marrow minimal residual disease (MRD).

Areas covered

In this paper, we review novel functional imaging techniques in MM, particularly focusing on their advantages, limits, applications and comparisons with 18F-FDG-PET/CT or other standardized imaging techniques.

Conclusions

Combining both morphological and functional imaging, 18F-FDG-PET/CT is currently considered a standard imaging technique in MM for staging (despite false positive or negative results) and response assessment. The introduction of novel functional imaging techniques, as whole-body diffusion-weighted magnetic resonance imaging (WB-DWI-MRI), or novel PET tracers might be useful in overcoming these limits. Future studies will give more information on the complementarity of these imaging techniques or whether one of them might become a new gold standard in MM.

Quantitative multi-energy CT in oncology: State of the art and future directions

Multi-energy computed tomography (CT) involves acquisition of two or more CT measurements with distinct energy spectra. Using the differential attenuation of tissues and materials at different X-ray energies, multi-energy CT allows distinction of tissues and materials. Multi-energy technology encompasses different types of CT systems, such as dual-energy CT and photon-counting CT, that can use information from the energy and type of material present in acquired images to create multiple datasets. These scanners have overcome many of the limitations of conventional CT, making it possible to improve the diagnostic performance of CT and expand its use to new applications through better tissue characterization and multiple quantitative parameters. Quantitative imaging biomarkers based on multi-energy CT have enormous potential in oncologic imaging, from the diagnosis and characterization of tumor phenotypes to the evaluation of the response to treatment. Nevertheless, implementing these techniques in clinical practice remains challenging. This article reviews the basic principles underlying multi-energy CT and the most recent technical developments in these systems together with their advantages and limitations to establish the value of quantitative imaging derived from multi-energy CT in the field of oncology.

Role of Imaging in Multiple Myeloma: A Potential Opportunity for Quantitative Imaging and Radiomics?

Multiple myeloma (MM) is the second most prevalent hematologic malignancy, particularly affecting the elderly. The disease often begins with a premalignant phase known as monoclonal gammopathy of undetermined significance (MGUS), solitary plasmacytoma (SP) and smoldering multiple myeloma (SMM). Multiple imaging modalities are employed throughout the disease continuum to assess bone lesions, prevent complications, detect intra- and extramedullary disease, and evaluate the risk of neurological complications. The implementation of advanced imaging analysis techniques, including artificial intelligence (AI) and radiomics, holds great promise for enhancing our understanding of MM. The integration of advanced image analysis techniques which extract features from magnetic resonance imaging (MRI), computed tomography (CT), or positron emission tomography (PET) images has the potential to enhance the diagnostic accuracy for MM. This innovative approach may lead to the identification of imaging biomarkers that can predict disease prognosis and treatment outcomes. Further research and standardized evaluations are needed to define the role of radiomics in everyday clinical practice for patients with MM.

Dual-Energy CT in Oncologic Imaging

Dual-energy CT (DECT) is an innovative technology that is increasingly widespread in clinical practice. DECT allows for tissue characterization beyond that of conventional CT as imaging is performed using different energy spectra that can help differentiate tissues based on their specific attenuation properties at different X-ray energies. The most employed post-processing applications of DECT include virtual monoenergetic images (VMIs), iodine density maps, virtual non-contrast images (VNC), and virtual non-calcium (VNCa) for bone marrow edema (BME) detection. The diverse array of images obtained through DECT acquisitions offers numerous benefits, including enhanced lesion detection and characterization, precise determination of material composition, decreased iodine dose, and reduced artifacts. These versatile applications play an increasingly significant role in tumor assessment and oncologic imaging, encompassing the diagnosis of primary tumors, local and metastatic staging, post-therapy evaluation, and complication management. This article provides a comprehensive review of the principal applications and post-processing techniques of DECT, with a specific focus on its utility in managing oncologic patients.

Imaging of Multiple Myeloma: Present and Future

Multiple myeloma (MM) is the second most common adult hematologic malignancy, and early intervention increases survival in asymptomatic high-risk patients. Imaging is crucial for the diagnosis and follow-up of MM, as the detection of bone and bone marrow lesions often dictates the decision to start treatment. Low-dose whole-body computed tomography (CT) is the modality of choice for the initial assessment, and dual-energy CT is a developing technique with the potential for detecting non-lytic marrow infiltration and evaluating the response to treatment. Magnetic resonance imaging (MRI) is more sensitive and specific than 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) for the detection of small focal lesions and diffuse marrow infiltration. However, FDG-PET/CT is recommended as the modality of choice for follow-up. Recently, diffusion-weighted MRI has become a new technique for the quantitative assessment of disease burden and therapy response. Although not widespread, we address current proposals for structured reporting to promote standardization and diminish variations. This review provides an up-to-date overview of MM imaging, indications, advantages, limitations, and recommended reporting of each technique. We also cover the main differential diagnosis and pitfalls and discuss the ongoing controversies and future directions, such as PET-MRI and artificial intelligence.

XGBoost-based multiparameters from dual-energy computed tomography for the differentiation of multiple myeloma of the spine from vertebral osteolytic metastases

OBJECTIVES

To evaluate the performance of extreme gradient boosting (XGBoost) combined with multiparameters from dual-energy computed tomography (mpDECT) to differentiate between multiple myeloma (MM) of the spine and vertebral osteolytic metastases (VOM).

METHODS

For this retrospective study, 28 patients (83 lesions) with MM of the spine and 23 patients (54 lesions) with VOM who underwent DECT were included. The mpDECT for each lesion, including normalized effective atomic number, slope of the spectral Hounsfield unit curve, CT attenuation, and virtual noncalcium (VNCa), was obtained. Boruta was used to select the key parameters, and then subsequently merged with XGBoost to yield a prediction model. The lesions were divided into the training and testing group in a 3:1 ratio. The highest performance of the univariate analysis was compared with XGBoost using the Delong test.

RESULTS

The mpDECT of MM was significantly lower than that of VOM (all p < 0.05). In univariate analysis, VNCa had the highest area under the receiver operating characteristic curve (AUC) in the training group (0.81) and testing group (0.87). Based on Boruta, 6 parameters of DECT were selected for XGBoost model construction. The XGBoost model achieved an excellent and stable diagnostic performance, as shown in the training group (AUC of 1.0) and testing group (AUC of 0.97), with a sensitivity of 80%, a specificity of 95%, and an accuracy of 88%, which was superior to VNCa (p < 0.05).

CONCLUSIONS

XGBoost combined with mpDECT yielded promising performance in differentiating between MM of the spine and VOM.

KEY POINTS

• The multiparameters obtained from dual-energy CT of multiple myeloma differed significantly from those of vertebral osteolytic metastases. • The virtual noncalcium offered the highest AUC in the univariate analysis to distinguish multiple myeloma from vertebral osteolytic metastases. • Extreme gradient boosting combined with multiparameters from dual-energy CT had a promising performance to distinguish multiple myeloma from vertebral osteolytic metastases.

Dual-Energy CT, Virtual Non-Calcium Bone Marrow Imaging of the Spine: An AI-Assisted, Volumetric Evaluation of a Reference Cohort with 500 CT Scans

Virtual non-calcium (VNCa) images from dual-energy computed tomography (DECT) have shown high potential to diagnose bone marrow disease of the spine, which is frequently disguised by dense trabecular bone on conventional CT. In this study, we aimed to define reference values for VNCa bone marrow images of the spine in a large-scale cohort of healthy individuals. DECT was performed after resection of a malignant skin tumor without evidence of metastatic disease. Image analysis was fully automated and did not require specific user interaction. The thoracolumbar spine was segmented by a pretrained convolutional neuronal network. Volumetric VNCa data of the spine’s bone marrow space were processed using the maximum, medium, and low calcium suppression indices. Histograms of VNCa attenuation were created for each exam and suppression setting. We included 500 exams of 168 individuals (88 female, patient age 61.0 ± 15.9). A total of 8298 vertebrae were segmented. The attenuation histograms’ overlap of two consecutive exams, as a measure for intraindividual consistency, yielded a median of 0.93 (IQR: 0.88–0.96). As our main result, we provide the age- and sex-specific bone marrow attenuation profiles of a large-scale cohort of individuals with healthy trabecular bone structure as a reference for future studies. We conclude that artificial-intelligence-supported, fully automated volumetric assessment is an intraindividually robust method to image the spine’s bone marrow using VNCa data from DECT.