Initial experience with dual-energy computed tomography-guided bone biopsies of bone lesions that are occult on monoenergetic CT

OBJECTIVE

Our purpose was to determine whether dual-energy CT (DECT), specifically the bone marrow setting of the virtual noncalcium (VNCa) algorithm, could be used to identify and accurately biopsy suspected bone malignancies that were visible on magnetic resonance imaging (MRI), nuclear bone scintigraphy, or positron-emission tomography/computed tomography (PET/CT), but occult on monoenergetic computed tomography (CT) by virtue of being either isodense or nearly isodense to surrounding normal bone.

MATERIALS AND METHODS

We present 4 cases in which DECT was used to detect various malignant bone lesions and was successfully used to direct percutaneous DECT-guided bone biopsies.

RESULTS

Two of the lesions were solid tumor metastases (breast and prostate carcinoma), whereas two others were hematological malignancies (leukemia and lymphoma). This technique enabled us to confidently and accurately direct the biopsy needle into the target lesion.

CONCLUSION

The authors demonstrate that the DECT VNCa bone marrow algorithm may be helpful in identifying isodense bone lesions of various histologies and may be used to guide percutaneous bone biopsies. This technique may help to maximize diagnostic yield, minimize the number of passes into the region of concern, and prevent patients from undergoing repeat biopsy.

The Differentiation of Soft Tissue Infiltration and Surrounding Edema in an Animal Model of Malignant Bone Tumor: Evaluation by Dual-Energy CT

To study the value of dual energy computed tomography in distinguishing soft tissue infiltration from surrounding soft tissue edema in rabbit malignant bone tumor, a malignant bone tumor model was established through implantation of VX2 tumor fragments into the tibiae of rabbits. Tumor adjacent soft tissues were divided into 3 areas according to pathology and computed tomography images. Computed tomography spectral curve slopes and iodine and water concentrations were assessed. Statistical analyses were performed using the Mann-Whitney U test and t test. The spectral curve of the soft tissue infiltration areas has a slope (1.30 ± 0.41) higher than that of the soft tissue edema areas (0.71 ± 0.23; P < .001). The iodine concentration in the soft tissue infiltration areas (8.56 ± 2.15) was higher than that in the in soft tissue edema areas (6.09 ± 1.02; P < .001). Water concentration was similar in the soft tissue infiltration areas (1033.86 ± 10.50) to that of the edema areas (1031.45 ± 12.83; P < .05). Spectral curve analysis and iodine-water concentration are helpful in the differentiation of bone tumor soft tissue infiltration and soft tissue edema.

Bone Subtraction Iodine Imaging Using Area Detector CT for Evaluation of Skull Base Invasion by Nasopharyngeal Carcinoma

BACKGROUND AND PURPOSE

Conventional CT has generally lower detectability of bone marrow invasion than MR imaging due to lower tissue contrast. The purpose of this study was to compare the diagnostic performance of conventional CT alone or in combination with bone subtraction iodine imaging using area detector CT for the evaluation of skull base invasion in patients with nasopharyngeal carcinoma.

MATERIALS AND METHODS

Forty-four consecutive patients who underwent contrast-enhanced CT using 320-row area detector CT and contrast-enhanced MR imaging for nasopharyngeal carcinoma staging between April 2012 and November 2017 were enrolled in this retrospective study. Bone subtraction iodine images were generated by subtracting pre- and postcontrast volume scans using a high-resolution deformable registration algorithm. Two blinded observers evaluated skull base invasion at multiple sites (sphenoid body, clivus, bilateral base of the pterygoid process, and petrous bone) using conventional CT images alone or in combination with bone subtraction iodine images. Examination of MR and CT images by an experienced neuroradiologist was the reference standard for evaluating sensitivity, specificity, and area under the receiver operating characteristic curve.

RESULTS

Twenty-six patients (59%) showed skull base invasion at 84 sites on the reference standard. Conventional CT plus bone subtraction iodine images showed higher sensitivity (92.9% versus 78.6%, P = .02) and specificity (95.6% versus 86.1%, P = .01) than conventional CT images alone for evaluating skull base invasion. The area under the receiver operating characteristic curve for conventional CT plus bone subtraction iodine (0.98) was significantly larger (P < .001) than the area under the receiver operating characteristic curve for conventional CT alone (0.90).

CONCLUSIONS

Conventional CT plus bone subtraction iodine performs more closely to the accuracy of combining CT and MR imaging compared with conventional CT alone.

Detection of Lumbar Spine Osseous Metastases Using Dual-Energy CT: Phantom Results and Preliminary Clinical Validation

OBJECTIVE

The purpose of this study was to evaluate the sensitivity, tumor conspicuity, and image quality of different material decomposition images of phantoms and patients with nearly isodense bone metastases using rapid-kilovoltage-switching dual-energy CT (DECT).

MATERIALS AND METHODS

Fifty-one semianthropomorphic lumbar spine phantoms embedded with 75 simulated tumors were scanned without and with outer torso-attenuating encasement under the same scan settings. Two radiologists independently reviewed the 70-keV virtual monochromatic and material decomposition images (hydroxyapatite-water, water-hydroxyapatite, cortical bone-water, water-cortical bone). The sensitivity of tumor detection, tumor conspicuity (on a 3-point scale), and image quality (on a 3-point scale) were recorded by two independent readers. McNemar and Wilcoxon signed rank tests were used to compare results between the image reconstructions. Six clinical abdominopelvic DECT scans (three men, three women; mean age, 52 years) with nine nearly isodense lumbar spine tumors missed in the clinical report but confirmed on other scans were also evaluated.

RESULTS

The hydroxyapatite-water material decomposition algorithm showed improved sensitivity for isodense lesion detection (without torso phantom encasement, 94% vs 82%, p = 0.031; with torso phantom encasement, 38% vs 18%, p = 0.013), and higher tumor conspicuity scores (p < 0.0001) compared with 70-keV virtual monoenergetic images. Artifacts were more prevalent with all material decomposition images than with 70-keV virtual monoenergetic images. Similar results were seen in the patient study.

CONCLUSION

Dual-energy CT with hydroxyapatite-water material decomposition may improve the detection of bone marrow metastases, especially for subtle isodense tumors. Further study in prospective clinical scans is warranted.

Axial Spondyloarthritis: Dual-Energy Virtual Noncalcium CT in the Detection of Bone Marrow Edema in the Sacroiliac Joints

Purpose To determine the diagnostic performance of dual-energy virtual noncalcium (VNCa) CT in the detection of bone marrow edema in study participants with sacroiliitis associated with axial spondyloarthritis. Materials and Methods In this prospective study, 47 consecutive participants (mean age, 27 years; age range, 14-41 years [28 male; mean age, 24 years; age range, 14-37 years] [19 female; mean age, 29 years; age range, 17-41 years]) underwent dual-energy CT and 3.0-T MRI between April 2016 and December 2017. Two independent readers visually evaluated all sacroiliac joints for the presence of abnormal marrow attenuation on dual-energy VNCa images using a four-point classification system (0, no edema; 1, mild edema; 2, moderate edema; 3, severe edema). CT numbers on VNCa images were determined with region-of-interest-based quantitative analysis. MRI was the reference standard for presence of bone marrow edema. Results Sensitivity, specificity, and accuracy of readers 1 and 2, respectively, in the identification of bone edema at CT were 87% and 93% (48 and 51 of 55), 94% and 91% (32 and 31 of 34), and 90% and 92% (80 and 82 of 89). Interobserver agreement was excellent (κ = 0.81). CT numbers from VNCa images increased from no edema to severe edema (P < .001). The area under the receiver operating characteristic curve was 0.93 for reader 1 and 0.91 for reader 2 in differentiation of the presence of bone marrow edema from no edema. A cutoff value of -33 HU derived from reader 1 yielded overall sensitivity, specificity, and accuracy of 90% (49 of 55), 83% (28 of 34), and 87% (77 of 89) in the detection of any extent of edema in the sacroiliac joints. Conclusion Dual-energy VNCa CT images had excellent diagnostic performance in evaluation of the extent of bone marrow edema in study participants with sacroiliitis associated with axial spondyloarthritis. © RSNA, 2018 See also the editorial by Guggenberger in this issue.

The Role of Dual-Energy Computed Tomography in Musculoskeletal Imaging

Dual-energy computed tomography (DECT) enables material decomposition and virtual monochromatic images by acquiring 2 different energy X-ray data sets. DECT can detect musculoskeletal pathologic conditions that CT alone cannot, and that would otherwise require MR imaging. In this review, the authors discuss several useful techniques and applications of DECT in musculoskeletal research: virtual monochromatic images, virtual noncalcium images, gout, iodine map, and tendons.

The Role of Dual-Energy Computed Tomography in Assessment of Abdominal Oncology and Beyond

The added value and strength of dual energy computed tomography for the evaluation of oncologic patients revolve around the use of lower energy reconstructed images and iodine material density images. Lower keV simulated monoenergetic images optimize soft tissue tumor to nontumoral attenuation differences and increase contrast to noise ratios to improve lesion detection. Iodine material density images or maps are helpful from a qualitative standpoint for image interpretation because they result in improved detection and characterization of tumors and lymph node involvement, and from a quantitative assessment by enabling interrogation of specific properties of tissues to predict and assess therapeutic response.

Dual-energy CT in patients with abdominal malignant lymphoma: impact of noise-optimised virtual monoenergetic imaging on objective and subjective image quality

AIM

To investigate the impact of noise-optimised virtual monoenergetic imaging (VMI+) reconstructions on quantitative and qualitative image parameters in patients with malignant lymphoma at dual-energy computed tomography (DECT) examinations of the abdomen.

MATERIALS AND METHODS

Thirty-five consecutive patients (mean age, 53.8±18.6 years; range, 21-82 years) with histologically proven malignant lymphoma of the abdomen were included retrospectively. Images were post-processed with standard linear blending (M_0.6), traditional VMI, and VMI+ technique at energy levels ranging from 40 to 100 keV in 10 keV increments. Signal-to-noise (SNR) and contrast-to-noise ratios (CNR) were objectively measured in lymphoma lesions. Image quality, lesion delineation, and image noise were rated subjectively by three blinded observers using five-point Likert scales.

RESULTS

Quantitative image quality parameters peaked at 40-keV VMI+ (SNR, 15.77±7.74; CNR, 18.27±8.04) with significant differences compared to standard linearly blended M_0.6 (SNR, 7.96±3.26; CNR, 13.55±3.47) and all traditional VMI series (p<0.001). Qualitative image quality assessment revealed significantly superior ratings for image quality at 60-keV VMI+ (median, 5) in comparison with all other image series (p<0.001). Assessment of lesion delineation showed the highest rating scores for 40-keV VMI+ series (median, 5), while lowest subjective image noise was found for 100-keV VMI+ reconstructions (median, 5).

CONCLUSION

Low-keV VMI+ reconstructions led to improved image quality and lesion delineation of malignant lymphoma lesions compared to standard image reconstruction and traditional VMI at abdominal DECT examinations.

Dual Energy Computed Tomography Applications for the Evaluation of the Spine

Capturing the energy-dependent x-ray attenuation of different tissues, dual-energy computed tomography offers multiple benefits in the imaging of the spine, such as bone and iodinated contrast removal, monosodium urate imaging, and robust reduction of beam-hardening artifacts. The emerging new applications of this technique include bone marrow imaging in acute trauma and myeloinfiltrative disorders, improved bone density determination, and noninvasive assessment of spinal gout.

Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on 68Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods

The identification of bone lesions is crucial in the diagnostic assessment of multiple myeloma (MM). 68Ga-Pentixafor PET/CT can capture the abnormal molecular expression of CXCR-4 in addition to anatomical changes. However, whole-body detection of dozens of lesions on hybrid imaging is tedious and error prone. It is even more difficult to identify lesions with a large heterogeneity. This study employed deep learning methods to automatically combine characteristics of PET and CT for whole-body MM bone lesion detection in a 3D manner. Two convolutional neural networks (CNNs), V-Net and W-Net, were adopted to segment and detect the lesions. The feasibility of deep learning for lesion detection on 68Ga-Pentixafor PET/CT was first verified on digital phantoms generated using realistic PET simulation methods. Then the proposed methods were evaluated on real 68Ga-Pentixafor PET/CT scans of MM patients. The preliminary results showed that deep learning method can leverage multimodal information for spatial feature representation, and W-Net obtained the best result for segmentation and lesion detection. It also outperformed traditional machine learning methods such as random forest classifier (RF), k-Nearest Neighbors (k-NN), and support vector machine (SVM). The proof-of-concept study encourages further development of deep learning approach for MM lesion detection in population study.

The Utility of Dual Energy Computed Tomography in Musculoskeletal Imaging

The objective of this article is to review the mechanisms, advantages and disadvantages of dual energy computed tomography (DECT) over conventional tomography (CT) in musculoskeletal imaging as DECT provides additional information about tissue composition and artifact reduction. This provides clinical utility in detection of urate crystals, bone marrow edema, reduction of beam hardening metallic artifact, and ligament and tendon analysis.

Multiple Myeloma and Dual-Energy CT: Diagnostic Accuracy of Virtual Noncalcium Technique for Detection of Bone Marrow Infiltration of the Spine and Pelvis

Purpose To determine the diagnostic performance of dual-energy computed tomography (CT) for detection of bone marrow (BM) infiltration in patients with multiple myeloma by using a virtual noncalcium (VNCa) technique. Materials and Methods In this prospective study, 34 consecutive patients with multiple myeloma or monoclonal gammopathy of unknown significance sequentially underwent dual-energy CT and magnetic resonance (MR) imaging of the axial skeleton. Two independent readers visually evaluated standard CT and color-coded VNCa images for the presence of BM involvement. MR imaging served as the reference standard. Analysis on the basis of the region of interest (ROI) of VNCa CT numbers of infiltrated (n = 75) and normal (n = 170) BM was performed and CT numbers were subjected to receiver operating characteristic analysis to calculate cutoff values. Results In the visual analysis, VNCa images had an overall sensitivity of 91.3% (21 of 23), specificity of 90.9% (10 of 11), accuracy of 91.2% (31 of 34), positive predictive value of 95.5% (21 of 22), and a negative predictive value of 83.3% (10 of 12). ROI-based analysis of VNCa CT numbers showed a significant difference between infiltrated and normal BM (P < .001). Receiver operating characteristic analysis revealed an area under the curve of 0.978. A cutoff of -44.9 HU provided a sensitivity of 93.3% (70 of 75), specificity of 92.4% (157 of 170), accuracy of 92.7% (227 of 245), positive predictive value of 84.3% (70 of 83), and negative predictive value of 96.9% (157 of 162) for the detection of BM infiltration. Conclusion Visual and ROI-based analyses of dual-energy VNCa images had excellent diagnostic performance for assessing BM infiltration in patients with multiple myeloma with precision comparable to that of MR imaging. ^© RSNA, 2017 Online supplemental material is available for this article.

Guidelines for the use of imaging in the management of patients with myeloma

The role of imaging in myeloma has gained increasing importance over the past few years. The recently revised definition of myeloma from the International Myeloma Working Group (IMWG) includes cross sectional imaging as a method to define bone disease and also incorporates its use in the disease definition for patients with suspected smouldering myeloma. The National Institute for Health and Care Excellence myeloma guidelines also recommend cross sectional imaging for patients with suspected myeloma. There is also increasing use of imaging in disease assessments and the International Myeloma Working Group has recently incorporated imaging in defining new response categories of minimal residual disease negativity, with or without imaging-based evidence of disease. Plain X-rays have previously been the standard imaging modality included in a myeloma work up at presentation but evidence is mounting for use of cross-sectional modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and 18 fluoro-deoxyglucose (18 F-FDG) positron emission tomography (PET)/CT. Funding and therefore availability of newer imaging techniques remains a barrier. Here, we propose an evidence-based approach to the use and technical application of the latest imaging modalities at diagnosis and in the follow-up of patients with myeloma and plasmacytoma.

Dual-energy CT virtual non-calcium technique for detection of bone marrow edema in patients with vertebral fractures: A prospective feasibility study on a single- source volume CT scanner

OBJECTIVES

Dual-energy computed tomography (DECT) is a recent development for detecting bone marrow edema (BME) in patients with vertebral compression fractures. The aim of this pilot study was to determine the reliability of single-source DECT in detecting vertebral BME using magnetic resonance imaging (MRI) as standard of reference.

MATERIALS AND METHODS

Nine patients with radiographic thoracic or lumbar vertebral compression fractures underwent both, DECT on a 320-row single-source scanner and 1.5T MRI. Virtual non-calcium (VNC) images were reconstructed from the DECT volume datasets. Three blinded readers independently scored images for the presence of BME. Only vertebrae with loss of height in radiography (target vertebrae) were included in the analysis. A vertebra was counted as positive if two readers agreed on the presence of BME. Cohen's kappa was calculated for interrater comparison. Intervertebral ratios of target and the reference vertebra were compared for CT attenuation and MR signal intensity in a reference vertebra using Spearman correlation. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated.

RESULTS

Fourteen target vertebrae with a radiographic height loss were identified; eight of them showed BME on MRI, while DECT identified BME in 7 instances. There were no false positive virtual non-calcium images, resulting in a sensitivity of 0.88 (0.75-1.0 among all readers) and specificity of 1.0 (0.81-1.0). Interrater agreement was inferior for DECT (κ=0.63-0.89) compared to MRI (κ=0.9-1.0). Intervertebral ratio in VNC images strongly correlated with short-tau inversion recovery (r=0.87) and inversely with T1 (-0.89). SNR (0.2+/- 0.2 in VNC and 16.7+/- 7.3 in STIR) and CNR (0.2+/- 0.3 and 7.1+/- 6.3) values were inferior in VNC.

CONCLUSIONS

Detecting BME with single-source DECT is feasible and allows detection of vertebral compression fractures with reasonably high sensitivity and specificity. However, image quality of VNC reconstructions has to be improved to achieve better interrater agreement. Nonetheless, DECT might accelerate the diagnostic work-flow in patients with vertebral compression fractures in the future and reduce the number of additional MRI examinations.

Water/cortical bone decomposition: A new approach in dual energy CT imaging for bone marrow oedema detection. A feasibility study

INTRODUCTION

Many studies aimed at validating the application of Dual Energy Computed Tomography (DECT) in clinical practice where conventional CT is not exhaustive. An example is given by bone marrow oedema detection, in which DECT based on water/calcium (W/Ca) decomposition was applied. In this paper a new DECT approach, based on water/cortical bone (W/CB) decomposition, was investigated.

MATERIALS AND METHODS

Eight patients suffering from marrow oedema were scanned with MRI and DECT. Two-materials density decomposition was performed in ROIs corresponding to normal bone marrow and oedema. These regions were drawn on DECT images using MRI informations. Both W/Ca and W/CB were considered as material basis. Scatter plots of W/Ca and W/CB concentrations were made for each ROI in order to evaluate if oedema could be distinguished from normal bone marrow. Thresholds were defined on the scatter plots in order to produce DECT images where oedema regions were highlighted through color maps. The agreement between these images and MR was scored by two expert radiologists.

RESULTS

For all the patients, the best scores were obtained using W/CB density decomposition.

CONCLUSIONS

In all cases, DECT color map images based on W/CB decomposition showed better agreement with MR in bone marrow oedema identification with respect to W/Ca decomposition. This result encourages further studies in order to evaluate if DECT based on W/CB decomposition could be an alternative technique to MR, which would be important when short scanning duration is relevant, as in the case of aged or traumatic patients.

Fully automated classification of bone marrow infiltration in low-dose CT of patients with multiple myeloma based on probabilistic density model and supervised learning

This paper presents a fully automated method for the identification of bone marrow infiltration in femurs in low-dose CT of patients with multiple myeloma. We automatically find the femurs and the bone marrow within them. In the next step, we create a probabilistic, spatially dependent density model of normal tissue. At test time, we detect unexpectedly high density voxels which may be related to bone marrow infiltration, as outliers to this model. Based on a set of global, aggregated features representing all detections from one femur, we classify the subjects as being either healthy or not. This method was validated on a dataset of 127 subjects with ground truth created from a consensus of two expert radiologists, obtaining an AUC of 0.996 for the task of distinguishing healthy controls and patients with bone marrow infiltration. To the best of our knowledge, no other automatic image-based method for this task has been published before.