Correlation between the maximum standard uptake value and mean Hounsfield unit on single-photon emission computed tomography-computed tomography to discriminate benign and metastatic lesions among patients with breast cancer

STUDY DESIGN

Retrospective study.

PURPOSE

To compare and correlate technetium-99m methylene diphosphonate uptake between benign and metastatic bone lesions using semiquantitative analysis of maximum standard uptake value (SUVmax) and mean Hounsfield unit (HU) in single-photon emission computed tomography-computed tomography (SPECT-CT).

OVERVIEW OF LITERATURE

Qualitative interpretation of metastatic bone lesions in breast cancer on bone scintigraphy is often complicated by coexisting benign lesions.

METHODS

In total, 185 lesions were identified on bone and SPECT-CT scans from 32 patients. Lesions were classified as metastatic (109 sclerotic lesions) and benign (76 lesions) morphologically on low-dose CT. Semiquantitative analysis using SUVmax and mean HU was performed on the lesions and compared. To discriminate benign and metastatic lesions, the correlation between SUVmax and mean HU was determined using the intraclass correlation coefficients.

RESULTS

The SUVmax was higher in metastatic lesions (20.66±14.36) but lower in benign lesions (10.18±12.79) (p<0.001). The mean HU was lower in metastatic lesions (166.62±202.02) but higher in benign lesions (517.65±192.8) (p<0.001). A weak negative correlation was found between the SUVmax and the mean HU for benign lesions, and a weak positive correlation was noted between the SUVmax and the mean HU on malignant lesions with no statistical significance (p=0.394 and 0.312, respectively). The cutoff values obtained were 10.8 for SUVmax (82.6% sensitivity and 84.2% specificity) and 240.86 for the mean HU (98.7% sensitivity and 88.1% specificity) in differentiating benign from malignant bone lesions.

CONCLUSIONS

Semiquantitative assessment using SUVmax and HU can complement qualitative analysis. Metastatic lesions had higher SUVmax but lower mean HU than benign lesions, whereas benign lesions demonstrated higher mean HU but lower SUVmax. A weak correlation was found between the SUVmax and the mean HU on malignant and benign lesions. Cutoff values of 10.8 for the SUVmax and 240.86 for the mean HU may differentiate bone metastases from benign lesions.

Histograms of computed tomography values in differential diagnosis of benign and malignant osteogenic lesions

BACKGROUND

The use of histogram analysis of computed tomography (CT) values is a potential method for differentiating between benign osteoblastic lesions (BOLs) and malignant osteoblastic lesions (MOLs).

PURPOSE

To explore the diagnostic efficacy of histogram analysis in accurately distinguishing between BOLs and MOLs based on CT values.

MATERIAL AND METHODS

A total of 25 BOLs and 25 MOLs, which were confirmed through pathology or imaging follow-up, were included in this study. FireVoxel software was used to process the lesions and obtain various histogram parameters, including mean value, standard deviation, variance, coefficient of variation, skewness, kurtosis, entropy value, and percentiles ranging from 1st to 99th. Statistical tests, such as two independent-sample t-tests and the Mann-Whitney U test with Bonferroni correction, were employed to compare the differences in histogram parameters between BOLs and MOLs. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of each parameter.

RESULTS

Significant differences were observed in several histogram parameters between BOLs and MOLs, including the mean value, coefficient of variation, skewness, and various percentiles. Notably, the 25th percentile demonstrated the highest diagnostic efficacy, as indicated by the largest area under the curve in the ROC curve analysis.

CONCLUSION

Histogram analysis of CT values provides valuable diagnostic information for accurately differentiating between BOLs and MOLs. Among the different parameters, the 25th percentile parameter proves to be the most effective in this discrimination process.

Quantitative Bone SPECT/CT of Central Cartilaginous Bone Tumors: Relationship between SUVmax and Radiodensity in Hounsfield Unit

(1) Background: it is challenging to determine the accurate grades of cartilaginous bone tumors. Using bone single photon emission computed tomography (SPECT)/computed tomography (CT), maximum standardized uptake value (SUVmax) was found to be significantly associated with different grades of cartilaginous bone tumor. The inquiry focused on the effect of the tumor matrix on SUVmax. (2) Methods: a total of 65 patients from 2017 to 2022 with central cartilaginous bone tumors, including enchondromas and low-to-intermediate grade chondrosarcomas, who had undergone bone SPECT/CT were retrospectively enrolled. The SUVmax was recorded and any aggressive CT findings of cartilaginous bone tumor and Hounsfield units (HU) of the chondroid matrix as mean, minimum, maximum, and standard deviation (SD) were reviewed on CT scans. Pearson's correlation analysis was performed to determine the relationship between CT features and SUVmax. Subgroup analysis was also performed between the benign group (enchondroma) and the malignant group (grade 1 and 2 chondrosarcoma) for comparison of HU values and SUVmax. (3) Results: a significant negative correlation between SUVmax and HU measurements, including HUmax, HUmean, and HUSD, was found. The subgroup analysis showed significantly higher SUVmax in the malignant group, with more frequent CT aggressive features, and significantly lower HUSD in the malignant group than in the benign group. (4) Conclusions: it was observed that higher SUVmax and lower HUSD were associated with a higher probability of having a low-to-intermediate chondrosarcoma with aggressive features and a less calcified tumor matrix.

Vertebral Venous Congestion That May Mimic Vertebral Metastasis on Contrast-Enhanced Chest Computed Tomography in Chemoport Inserted Patients

OBJECTIVE

This study aimed to determine the prevalence of vertebral venous congestion (VVC) in patients with chemoport insertion, evaluate the imaging characteristics of nodular VVC, and identify the factors associated with VVC.

MATERIALS AND METHODS

This retrospective single-center study was based on follow-up contrast-enhanced chest computed tomography (CT) of 1412 adult patients who underwent chemoport insertion between January 2016 and December 2016. The prevalence of venous stenosis, reflux, and VVC were evaluated. The imaging features of nodular VVC, including specific locations within the vertebral body, were analyzed. To identify the factors associated with VVC, patients with VVC were compared with a subset of patients without VVC who had been followed up for > 3 years without developing VVC after chemoport insertion. Toward this, a multivariable logistic regression analysis was performed.

RESULTS

After excluding 333 patients, 1079 were analyzed (mean age ± standard deviation, 62.3 ± 11.6 years; 540 females). The prevalence of VVC was 5.8% (63/1079), with all patients (63/63) demonstrating vertebral venous reflux and 67% (42/63) with innominate vein stenosis. The median interval between chemoport insertion and VVC was 515 days (interquartile range, 204-881 days). The prevalence of nodular VVC was 1.5% (16/1079), with a mean size of 5.9 ± 3.1 mm and attenuation of 784 ± 162 HU. Nodular VVC tended to be located subcortically. Forty-four patients with VVC underwent CT examinations with contrast injections in both arms; the VVC disappeared in 70% (31/44) when the contrast was injected in the arm contralateral to the chemoport site. Bevacizumab use was independently associated with VVC (odds ratio, 3.45; P < 0.001).

CONCLUSION

The prevalence of VVC and nodular VVC was low in patients who underwent chemoport insertion. Nodular VVC was always accompanied by vertebral venous reflux and tended to be located subcortically. To avoid VVC, contrast injection in the arm contralateral to the chemoport site is preferred.

Spectral CT assists differentiation of osteoblastic bone metastasis from bone island in newly diagnosed cancer patients

OBJECTIVES

To investigate measurements derived from plain and enhanced spectral CT in differentiating osteoblastic bone metastasis (OBM) from bone island (BI).

MATERIALS AND METHODS

From January to November 2020, 73 newly diagnosed cancer patients with 201 bone lesions (OBM = 92, BI = 109) having received spectral CT were retrospectively enrolled. Measurements including CT values of 40-140 keV, slope of the spectral curve, effective atomic number (Zeff), water (calcium) density, calcium (water) density, and Iodine (calcium) density were derived from manually segmented lesions on plain and enhanced spectral CT, and then analyzed using Student t-test and Pearson's correlation. Multivariate analysis was performed to build models (plain spectral model, enhanced spectral CT model, and combined model) for the discrimination of OBM and BI with performance evaluated using receiver operator characteristics curve and DeLong test.

RESULTS

All features were significantly different between the BI group and OBM group (all p < 0.05), highly correlated with the corresponding features between plain and enhanced spectral CT both in OBM (r: 0.392-0.763) and BI (r: 0.430-0.544). As for the model performance, the combined model achieved the best performance (AUC = 0.925, 95% CI: 0.879 to 0.957), which significantly outperformed the plain spectral CT model (AUC = 0.815, 95% CI: 0.754 to 0.866, p < 0.001) and enhanced spectral CT model (AUC = 0.901, 95% CI: 0.852 to 0.939, p = 0.024) in differentiating OBM and BI.

CONCLUSION

In addition to plain spectral CT measurements, enhanced spectral CT measurements would further significantly benefit the differential diagnosis.

CLINICAL RELEVANCE STATEMENT

Measurements derived either from plain or enhanced spectral CT could provide additional valuable information to improve the differential diagnosis between OBM and BI in newly diagnosed cancer patients.

KEY POINTS

• We intend to investigate plain and enhanced spectral CT measurements in differentiating OBM from BI. • Both plain and enhanced spectral CT help in discriminating OBM and BI in newly diagnosed cancer patients. • Enhanced spectral CT measurements further improve plain spectral CT measurements-based differential diagnosis.

[Imaging Findings of Spinal Metastases with Differential Diagnosis: Focusing on Solitary Spinal Lesion in Older Patients]

If a solitary spinal lesion is found in an older patient, bone metastasis can be primarily considered as the diagnosis. Bone metastasis can occur anywhere, but it mostly occurs in the vertebral body and may sometimes show typical imaging findings, presenting as a single lesion. Therefore, differentiating it from other lesions that mimic bone metastases can be challenging, potentially leading to delayed diagnosis and initiation of primary cancer treatment. This review provides an overview of imaging findings and clinical guidelines for bone metastases and discusses its differences from other diseases that can occur as solitary spinal lesions in older patients.

Imaging diagnosis of vertebral metastasis

The spine is the third most frequent location for metastatic disease, after the lung and liver. On the other hand, the most frequent bone tumors are metastases and the spine is the main location. A review of the different imaging techniques available, both radiological and nuclear medicine, and the morphological appearance of spinal metastases in each of them is performed. Magnetic resonance imaging is the best imaging modality for detection of spinal metastases. It is important to make the differential diagnosis between vertebral fracture of osteoporotic and pathological cause. Spinal cord compression is a serious complication of metastatic disease and its assessment by imaging through objective scales is decisive for estimating spinal stability and therefore establishing treatment. Lastly, percutaneous intervention techniques are briefly discussed.

[Translated article] Imaging diagnosis of vertebral metastasis

The spine is the third most frequent location for metastatic disease, after the lung and liver. On the other hand, the most frequent bone tumours are metastases and the spine is the main location. A review of the different imaging techniques available, both radiological and nuclear medicine, and the morphological appearance of spinal metastases in each of them is performed. Magnetic resonance imaging is the best imaging modality for detection of spinal metastases. It is important to make the differential diagnosis between vertebral fracture of osteoporotic and pathological cause. Spinal cord compression is a serious complication of metastatic disease and its assessment by imaging through objective scales is decisive for estimating spinal stability and therefore establishing treatment. Lastly, percutaneous intervention techniques are briefly discussed.

Effect of Gaussian Smoothing Filter Size for CT-Based Attenuation Correction on Quantitative Assessment of Bone SPECT/CT: A Phantom Study

This study aims to determine the effect of Gaussian filter size for CT-based attenuation correction (CTAC) on the quantitative assessment of bone SPECT. An experiment was performed using a cylindrical phantom containing six rods, of which one was filled with water and five were filled with various concentrations of K2HPO4 solution (120-960 mg/cm3) to simulate different bone densities. 99mTc-solution of 207 kBq/ml was also included within the rods. SPECT data were acquired at 120 views for 30 s/view. CT for attenuation correction were obtained at 120 kVp and 100 mA. Sixteen different CTAC maps processed with different Gaussian filter sizes (ranging from 0 to 30 mm in 2 mm increments) were generated. SPECT images were reconstructed for each of the 16 CTAC maps. Attenuation coefficients and radioactivity concentrations in the rods were compared with those in the water-filled rod without K2HPO4 solution as a reference. Gaussian filter sizes below 14-16 mm resulted in an overestimation of radioactivity concentrations for rods with high concentrations of K2HPO4 (≥ 666 mg/cm3). The overestimation of radioactivity concentration measurement was 3.8% and 5.5% for 666 mg/cm3 and 960 mg/cm3 K2HPO4 solutions, respectively. The difference in radioactivity concentration between the water rod and the K2HPO4 rods was minimal at 18-22 mm. The use of Gaussian filter sizes smaller than 14-16 mm caused an overestimation of radioactivity concentration in regions of high CT values. Setting the Gaussian filter size to 18-22 mm enables radioactivity concentration to be measured with the least influence on bone density.

Deep learning-based diagnosis of osteoblastic bone metastases and bone islands in computed tomograph images: a multicenter diagnostic study

OBJECTIVE

To develop and validate a deep learning (DL) model based on CT for differentiating bone islands and osteoblastic bone metastases.

MATERIALS AND METHODS

The patients with sclerosing bone lesions (SBLs) were retrospectively included in three hospitals. The images from site 1 were randomly assigned to the training (70%) and intrinsic verification (10%) datasets for developing the two-dimensional (2D) DL model (single-slice input) and "2.5-dimensional" (2.5D) DL model (three-slice input) and to the internal validation dataset (20%) for evaluating the performance of both models. The diagnostic performance was evaluated using the internal validation set from site 1 and additional external validation datasets from site 2 and site 3. And statistically analyze the performance of 2D and 2.5D DL models.

RESULTS

In total, 1918 SBLs in 728 patients in site 1, 122 SBLs in 71 patients in site 2, and 71 SBLs in 47 patients in site 3 were used to develop and test the 2D and 2.5D DL models. The best performance was obtained using the 2.5D DL model, which achieved an AUC of 0.996 (95% confidence interval [CI], 0.995-0.996), 0.958 (95% CI, 0.958-0.960), and 0.952 (95% CI, 0.951-0.953) and accuracies of 0.950, 0.902, and 0.863 for the internal validation set, the external validation set from site 2 and site 3, respectively.

CONCLUSION

A DL model based on a three-slice CT image input (2.5D DL model) can improve the prediction of osteoblastic bone metastases, which can facilitate clinical decision-making.

KEY POINTS

• This study investigated the value of deep learning models in identifying bone islands and osteoblastic bone metastases. • Three-slice CT image input (2.5D DL model) outweighed the 2D model in the classification of sclerosing bone lesions. • The 2.5D deep learning model showed excellent performance using the internal (AUC, 0.996) and two external (AUC, 0.958; AUC, 0.952) validation sets.

Recommendations for the Management of Incidental Musculoskeletal Findings on MRI and CT

The Canadian Association of Radiologists (CAR) Incidental Findings Working Group consists of both academic subspeciality and general radiologists tasked with either adapting American College of Radiology (ACR) guidelines to meet the needs of Canadian radiologists or authoring new guidelines where appropriate. In this case, entirely new guidelines to deal with incidental musculoskeletal findings that may be encountered on thoracoabdominal computed tomography or magnetic resonance imaging were drafted, focussing on which findings should prompt recommendations for further workup. These recommendations discuss how to deal with incidental marrow changes, focal bone lesions, abnormalities of the pubic symphysis and sacroiliac joints, fatty soft tissue masses, manifestations of renal osteodystrophy and finally discuss opportunistic osteoporosis evaluation.

Primary Benign Neoplasms of the Spine

Benign tumours comprise the majority of primary vertebral tumours, and these are often found incidentally on imaging. Nonetheless, accurate diagnosis of these benign lesions is crucial, in order to avoid misdiagnosis as more ominous malignant lesions or infection. Furthermore, some of these tumours, despite their benign nature, can have localised effects on the spine including neural compromise, or can be locally aggressive, thus necessitating active management. Haemangiomas and osteomas (enostosis) are the commonest benign tumours encountered. Others include osteoid osteoma, osteoblastoma, fibrous dysplasia, osteochondroma, chondroblastoma, haemangioma, simple bone cysts, aneurysmal bone cysts, giant cell tumours, eosinophilic granuloma and notochordal rests. The majority of lesions are asymptomatic; however, locally aggressive lesions (such as aneurysmal bone cysts or giant cell tumours) can present with nonspecific symptoms, such as back pain, neurological deficits and spinal instability, which may be indistinguishable from more commonly encountered mechanical back pain or malignant lesions including metastases. Hence, imaging, including radiography, computed tomography (CT) and magnetic resonance imaging (MRI), plays a critical role in diagnosis. Generally, most incidental or asymptomatic regions are conservatively managed or may not require any follow-up, while symptomatic or locally aggressive lesions warrant active interventions, which include surgical resection or percutaneous treatment techniques. Due to advances in interventional radiology techniques in recent years, percutaneous minimally invasive techniques such as radiofrequency ablation, sclerotherapy and cryoablation have played an increasing role in the management of these tumours with favourable outcomes. The different types of primary benign vertebral tumours will be discussed in this article with an emphasis on pertinent imaging features.

A Scalable Radiomics- and Natural Language Processing-Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study

BACKGROUND

The identification of objective pain biomarkers can contribute to an improved understanding of pain, as well as its prognosis and better management. Hence, it has the potential to improve the quality of life of patients with cancer. Artificial intelligence can aid in the extraction of objective pain biomarkers for patients with cancer with bone metastases (BMs).

OBJECTIVE

This study aimed to develop and evaluate a scalable natural language processing (NLP)- and radiomics-based machine learning pipeline to differentiate between painless and painful BM lesions in simulation computed tomography (CT) images using imaging features (biomarkers) extracted from lesion center point-based regions of interest (ROIs).

METHODS

Patients treated at our comprehensive cancer center who received palliative radiotherapy for thoracic spine BM between January 2016 and September 2019 were included in this retrospective study. Physician-reported pain scores were extracted automatically from radiation oncology consultation notes using an NLP pipeline. BM center points were manually pinpointed on CT images by radiation oncologists. Nested ROIs with various diameters were automatically delineated around these expert-identified BM center points, and radiomics features were extracted from each ROI. Synthetic Minority Oversampling Technique resampling, the Least Absolute Shrinkage And Selection Operator feature selection method, and various machine learning classifiers were evaluated using precision, recall, F1-score, and area under the receiver operating characteristic curve.

RESULTS

Radiation therapy consultation notes and simulation CT images of 176 patients (mean age 66, SD 14 years; 95 males) with thoracic spine BM were included in this study. After BM center point identification, 107 radiomics features were extracted from each spherical ROI using pyradiomics. Data were divided into 70% and 30% training and hold-out test sets, respectively. In the test set, the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of our best performing model (neural network classifier on an ensemble ROI) were 0.82 (132/163), 0.59 (16/27), 0.85 (116/136), and 0.83, respectively.

CONCLUSIONS

Our NLP- and radiomics-based machine learning pipeline was successful in differentiating between painful and painless BM lesions. It is intrinsically scalable by using NLP to extract pain scores from clinical notes and by requiring only center points to identify BM lesions in CT images.

Primary Osseous Malignancies of the Spine

Malignant primary vertebral tumours comprise an uncommon group of primary bone malignancies that can pose a diagnostic and therapeutic challenge. The most frequently encountered malignant primary vertebral tumours include chordoma, chondrosarcoma, Ewing sarcoma and osteosarcoma. These tumours often present with nonspecific symptoms, such as back pain, neurologic deficits and spinal instability, which can be confused for the more commonly encountered mechanical back pain and may delay their diagnosis and treatment. Imaging, including radiography, computed tomography (CT) and magnetic resonance imaging (MRI) is crucial for diagnosis, staging, treatment planning and follow-up. Surgical resection remains the mainstay of treatment for malignant primary vertebral tumours, but adjuvant radiotherapy and chemotherapy may be necessary for achieving complete tumour control depending on the type of tumour. In recent years, advances in imaging techniques and surgical approaches, such as en-bloc resection and spinal reconstruction, have improved the outcomes for patients with malignant primary vertebral tumours. However, the management can be complex due to the anatomy involved and the high morbidity and mortality associated with surgery. The different types of malignant primary vertebral lesions will be discussed in this article with an emphasis on the imaging features.

Application of Machine Learning for Differentiating Bone Malignancy on Imaging: A Systematic Review

An accurate diagnosis of bone tumours on imaging is crucial for appropriate and successful treatment. The advent of Artificial intelligence (AI) and machine learning methods to characterize and assess bone tumours on various imaging modalities may assist in the diagnostic workflow. The purpose of this review article is to summarise the most recent evidence for AI techniques using imaging for differentiating benign from malignant lesions, the characterization of various malignant bone lesions, and their potential clinical application. A systematic search through electronic databases (PubMed, MEDLINE, Web of Science, and clinicaltrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 34 articles were retrieved from the databases and the key findings were compiled and summarised. A total of 34 articles reported the use of AI techniques to distinguish between benign vs. malignant bone lesions, of which 12 (35.3%) focused on radiographs, 12 (35.3%) on MRI, 5 (14.7%) on CT and 5 (14.7%) on PET/CT. The overall reported accuracy, sensitivity, and specificity of AI in distinguishing between benign vs. malignant bone lesions ranges from 0.44–0.99, 0.63–1.00, and 0.73–0.96, respectively, with AUCs of 0.73–0.96. In conclusion, the use of AI to discriminate bone lesions on imaging has achieved a relatively good performance in various imaging modalities, with high sensitivity, specificity, and accuracy for distinguishing between benign vs. malignant lesions in several cohort studies. However, further research is necessary to test the clinical performance of these algorithms before they can be facilitated and integrated into routine clinical practice.

Bone and soft tissue tumors at the borderlands of malignancy

This review examines findings of musculoskeletal neoplasms whose equivocal imaging and/or histopathologic features make it difficult to determine if they will show aggressive behavior. We include both intermediate tumors as defined by the World Health Organization (WHO), and a single low-grade malignancy, low-grade central osteosarcoma, which mimics a benign lesion on imaging and histology. Intermediate tumors are a broad category and are subdivided into tumors that have risk of local recurrence only, and ones that have a risk of distant limb and pulmonary metastases. Difficult intermediate musculoskeletal lesions include atypical cartilaginous tumor/grade 1 chondrosarcoma, atypical lipomatous tumor/grade 1 liposarcoma, and solitary fibrous tumor. We review diagnostic criteria, differential diagnosis, and recommendations for surveillance.

Benign incidental do-not-touch bone lesions

Benign bone lesions may occasionally be incidentally detected on radiographs and are also increasingly found on CT or MRI performed for other clinical indications. Although mostly asymptomatic or associated with minor symptoms, these lesions may simulate true pathological lesions, causing problems in diagnosis. For instance, asymptomatic benign bone lesions can be misinterpreted as metastasis when incidentally encountered in a patient with known cancer. Recognising these entities as "do-not-touch" lesions helps avoid unnecessary further investigation or harmful intervention. In this review, we highlight three groups of bone incidentalomas found in adults, namely: osteolytic lesions, osteoblastic lesions, and bone protuberances. We aim to review the key imaging features of selected common and less common conditions in these three groups, so as to help radiologists confidently identify these benign do-not-touch lesions and to distinguish them from more sinister pathological lesions.

Contribution of an artificial intelligence deep-learning reconstruction algorithm for dose optimization in lumbar spine CT examination: A phantom study

PURPOSE

The purpose of this study was to assess the impact of the new artificial intelligence deep-learning reconstruction (AI-DLR) algorithm on image quality and radiation dose compared with iterative reconstruction algorithm in lumbar spine computed tomography (CT) examination.

MATERIALS AND METHODS

Acquisitions on phantoms were performed using a tube current modulation system for four DoseRight Indexes (DRI) (i.e., 26/23/20/15). Raw data were reconstructed using the Level 4 of iDose⁴ (i4) and three levels of AI-DLR (Smoother/Smooth/Standard) with a bone reconstruction kernel. The Noise power spectrum (NPS), task-based transfer function (TTF) and detectability index (d') were computed (d' modeled detection of a lytic and a sclerotic bone lesions). Image quality was subjectively assessed on an anthropomorphic phantom by two radiologists.

RESULTS

The Noise magnitude was lower with AI-DLR than i4 and decreased from Standard to Smooth (-31 ± 0.1 [SD]%) and Smooth to Smoother (-48 ± 0.1 [SD]%). The average NPS spatial frequency was similar with i4 (0.43 ± 0.01 [SD] mm^-1) and Standard (0.42 ± 0.01 [SD] mm^-1) but decreased from Standard to Smoother (0.36 ± 0.01 [SD] mm^-1). TTF values at 50% decreased as the dose decreased but were similar with i4 and all AI-DLR levels. For both simulated lesions, d' values increased from Standard to Smoother levels. Higher detectabilities were found with a DRI at 15 and Smooth and Smoother levels than with a DRI at 26 and i4. The images obtained with these dose and AI-DLR levels were rated satisfactory for clinical use by the radiologists.

CONCLUSION

Using Smooth and Smoother levels with CT allows a significant dose reduction (up to 72%) with a high detectability of lytic and sclerotic bone lesions and a clinical overall image quality.

Original research: utilization of a convolutional neural network for automated detection of lytic spinal lesions on body CTs

OBJECTIVE

To develop, train, and test a convolutional neural network (CNN) for detection of spinal lytic lesions in chest, abdomen, and pelvis CT scans.

MATERIALS AND METHODS

Cases of malignant spinal lytic lesions in CT scans were identified. Images were manually segmented for the following classes: (i) lesion, (ii) normal bone, (iii) background. If more than one lesion was on a single slice, all lesions were segmented. Images were stored as 128×128 pixel grayscale, with 10% segregated for testing. The training pipeline of the dataset included histogram equalization and data augmentation. A model was trained on Keras/Tensorflow using an 80/20 training/validation split, based on U-Net architecture. Additional testing of the model was performed on 1106 images of healthy controls. Global sensitivity measured detection of any lesion on a single image. Local sensitivity and positive predictive value (PPV) measured detection of all lesions on an image. Global specificity measured false positive rate in non-pathologic bone.

RESULTS

Six hundred images were obtained for model creation. The training set consisted of 540 images, which was augmented to 20,000. The test set consisted of 60 images. Model training was performed in triplicate. Mean Dice scores were 0.61 for lytic lesion, 0.95 for normal bone, and 0.99 for background. Mean global sensitivity was 90.6%, local sensitivity was 74.0%, local PPV was 78.3%, and global specificity was 63.3%. At least one false positive lesion was noted in 28.8-44.9% of control images.

CONCLUSION

A task-trained CNN showed good sensitivity in detecting spinal lytic lesions in axial CT images.

EANM practice guideline for quantitative SPECT-CT

PURPOSE

Quantitative SPECT-CT is a modality of growing importance with initial developments in post radionuclide therapy dosimetry, and more recent expansion into bone, cardiac and brain imaging together with the concept of theranostics more generally. The aim of this document is to provide guidelines for nuclear medicine departments setting up and developing their quantitative SPECT-CT service with guidance on protocols, harmonisation and clinical use cases.

METHODS

These practice guidelines were written by members of the European Association of Nuclear Medicine Physics, Dosimetry, Oncology and Bone committees representing the current major stakeholders in Quantitative SPECT-CT. The guidelines have also been reviewed and approved by all EANM committees and have been endorsed by the European Association of Nuclear Medicine.

CONCLUSION

The present practice guidelines will help practitioners, scientists and researchers perform high-quality quantitative SPECT-CT and will provide a framework for the continuing development of quantitative SPECT-CT as an established modality.

Common incidental findings on sacroiliac joint MRI: Added value of MRI-based synthetic CT

PURPOSE

To determine the prevalence of incidental findings on sacroiliac joint MRI and to determine the added value of MRI-based synthetic CT in the detection and evaluation of these incidental findings.

METHOD

In this retrospective study 210 patients clinically suspected of spondyloarthritis who underwent MRI of the sacroiliac joint with synthetic CT sequence were included. The images were reviewed by two radiologists in consensus for the prevalence of sacroiliitis, incidental findings, and the ability of synthetic CT and the conventional MRI to detect and diagnose these findings.

RESULTS

In 44.7% of patients sacroiliitis was present. In 89.0% of patients MRI showed at least one incidental finding other than sacroiliitis. Degeneration of the sacroiliac joint was the most prevalent finding (140 patients, 66.6%). The most frequent incidental findings outside the sacroiliac joint were facet joint degeneration (29.0%), disc degeneration (25.2%), enostosis (19.5%) and lumbosacral transitional vertebrae (14.3%). A total of 788 lesions was recorded and synthetic CT was found to be problem solving or necessary for diagnosis in 543 (68.9%) of these lesions. 42.1% of lesions were not visible on conventional MRI (T1 TSE and STIR), most often degenerative osteophytes in the sacroiliac joint or lower lumbar spine.

CONCLUSION

Incidental findings are seen more frequently on sacroiliac joint MRI than sacroiliitis, which is relevant as some will have clinical significance or require treatment. Nearly half of these incidental lesions were only visible on synthetic CT, which additionally has been shown to be problem solving for diagnosis in many other cases.

Initial Characterization of Focal Bone Lesions with Conventional Radiographs or Computed Tomography: Diagnostic Performance and Interobserver Agreement Assessment

Objectives: To ascertain the role of CT and conventional radiographs for the initial characterization of focal bone lesions.Methods: Images from 184 patients with confirmed bone tumors included in an ethics committee-approved study were retrospectively evaluated. The reference for benign-malignant distribution was based on histological analysis and long-term follow-up. Radiographs and CT features were analyzed by 2 independent musculoskeletal radiologists blinded to the final diagnosis. Lesion margins, periosteal reaction, cortical lysis, endosteal scalloping, presence of pathologic fracture, and lesion mineralization were evaluated. Results: The benign-malignant distribution in the study population was 68.5-31.5% (126 benign and 58 malignant). In the lesions that could be seen in both radiographs and CT, the performance of these methods for the benign-malignant differentiation was similar (accuracy varying from 72.8% to 76.5%). The interobserver agreement for the overall evaluation of lesion aggressiveness was considerably increased on CT compared to radiographs (Kappa of .63 vs .22). With conventional radiographs, 18 (9.7%) and 20 (10.8%) of the lesions evaluated were not seen respectively by readers 1 and 2. Among these unseen lesions, 50%-61.1% were located in the axial skeleton. Compared to radiographs, the number of lesions with cortical lysis and endosteal scalloping was 26-34% higher with CT. Conclusion: Although radiographs remain the primary imaging tool for lesions in the peripheral skeleton, CT should be performed for axial lesions. CT imaging can assess the extent of perilesional bone lysis more precisely than radiographs with a better evaluation of lesion fracture risk.

Utility of dual energy computed tomography in the evaluation of infiltrative skeletal lesions and metastasis: a literature review

Computed tomography (CT) is routinely used to diagnose and evaluate metastatic lesions in oncology. CT alone suffers from lack of sensitivity, especially for skeletal lesions in the bone marrow and lesions that have similar attenuation profiles to surrounding bone. Magnetic resonance imaging and nuclear medicine imaging remain the gold standard in evaluating skeletal lesions. However, compared to CT, these modalities are not as widely available or suitable for all patients. Dual energy computed tomography (DECT) exploits variations in linear attenuation coefficient of materials at different photon energy levels to reconstruct images based on material composition. DECT in musculoskeletal imaging is used in the imaging of crystal arthropathy and detecting subtle fractures, but it is not broadly utilized in evaluating infiltrative skeletal lesions. Malignant skeletal lesions have different tissue and molecular compositions compared to normal bone. DECT may exploit these physical differences to delineate infiltrative skeletal lesions from surrounding bone better than conventional monoenergetic CT. Studies so far have examined the utility of DECT in evaluating skeletal metastases, multiple myeloma lesions, pathologic fractures, and performing image-guided biopsies with promising results. These studies were mostly retrospective analyses and case reports containing small samples sizes. As DECT becomes more widely used clinically and more scientific studies evaluating the performance of DECT are published, DECT may eventually become an important modality in the work-up of infiltrative skeletal lesions. It may even challenge MRI and nuclear medicine because of relatively faster scanning times and ease of access.

Dual-Energy Computed Tomography For Differentiation Between Osteoblastic Metastases and Bone Islands

Objective

The objective of our study was to evaluate the utility of Rho/Z on dual-energy computed tomography (DECT) for the differentiation of osteoblastic metastases (OBMs) from bone islands (BIs).

Methods

DECT images of 110 patients with malignancies were collected. The effective atomic number (Z), electron density (Rho), dual energy index (DEI), and regular CT (rCT) values were measured by two observers. Independent-sample t-test was used to compare these values between OBMs and BIs. The diagnostic performance was assessed by receiver operating characteristic (ROC) analysis and the cutoff values were evaluated according to ROC curves.

Results

A total of 205 OBMs and 120 BIs were included. The mean values of Z, Rho, DEI, and rCT of OBMs were significantly lower than those of BIs, whereas the standard deviation values were higher than those of BIs (all p ≤ 0.05). ROC analysis showed that 11.86 was the optimal cutoff value for Z, rendering an area under the ROC curve (AUC) of 0.91, with a sensitivity of 91.2% and a specificity of 82.5%.

Conclusion

DECT can provide quantitative values of Z, Rho, and DEI and has good performance in differentiating between OBMs and BIs.

Subchondral bone attenuation coefficient utility of the sacroiliac margins to differentiate spondyloarthritis and osteitis condensans ilii

Introduction

Differentiating ankylosing spondylitis (AS) from osteitis condensans ilii (OCI) remains challenging for clinicians. The aim of this study was to determine whether Subchondral Bone Attenuation Coefficient of the SacroIliac margins (SBAC-SI) is different in AS, OCI and diffuse idiopathic skeletal hyperostosis (DISH).

Methods

A monocentric retrospective observational study was performed at the University Hospital of Besançon. Patients included were followed for AS, DISH or OCI and underwent CT scan including sacroiliac joint. Patients with tumour lesion of bone or a history of pelvic radiotherapy were excluded. AS and OCI patients were matched with a control of the same age and sex. SBAC-SI was evaluated by the sum of 24 identical circular regions of interest, 8 per slice (anterior, middle and posterior).

Results

Thirty AS and AS controls, 31 DISH, 29 OCI and OCI controls were included. SBAC-SI score was 9727 (±2430) in the OCI group (p<0.001), 3563 (±1860) in the AS group, 3899 (±1937) in the DISH group, 4224 (±1693) in the AS control group and 5445 (±1205) in the OCI control group. A threshold of 7500 HU had the best discriminative value between OCI and AS (youden index: 0.89). In AS, disease duration is negatively associated with SBAC-SI (r: −0.623; p<0.01) and HLA B27 is associated with lower SBAC-SI (6523 (5198; 7137) vs 2809 (1568; 3371); p<0.001).

Conclusion

SBAC-SI is significatively different between AS and OCI and could help to distinguish these two diseases.

Osteolytic vs. Osteoblastic Metastatic Lesion: Computational Modeling of the Mechanical Behavior in the Human Vertebra after Screws Fixation Procedure

Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screw fixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing surgical treatment. This work proposes an image-based finite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type, and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response and suggest a better way to account for these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for the irregular shape of the overall metastatic tissue does not significantly affect the vertebra fracture load. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining fracture risk. The proposed computational approach moves toward defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk.

Society of Skeletal Radiology- white paper. Guidelines for the diagnostic management of incidental solitary bone lesions on CT and MRI in adults: bone reporting and data system (Bone-RADS)

The purpose of this article is to present algorithms for the diagnostic management of solitary bone lesions incidentally encountered on computed tomography (CT) and magnetic resonance (MRI) in adults. Based on review of the current literature and expert opinion, the Practice Guidelines and Technical Standards Committee of the Society of Skeletal Radiology (SSR) proposes a bone reporting and data system (Bone-RADS) for incidentally encountered solitary bone lesions on CT and MRI with four possible diagnostic management recommendations (Bone-RADS1, leave alone; Bone-RADS2, perform different imaging modality; Bone-RADS3, perform follow-up imaging; Bone-RADS4, biopsy and/or oncologic referral). Two algorithms for CT based on lesion density (lucent or sclerotic/mixed) and two for MRI allow the user to arrive at a specific Bone-RADS management recommendation. Representative cases are provided to illustrate the usability of the algorithms.

MR Imaging of the Pelvic Bones: The Current and Cutting-Edge Techniques

This review presents an overview of the spectrum of the current and cutting-edge MRI techniques for pelvic bone imaging in clinical practice. The current MRI sequences and their advantages, disadvantages and usefullness in the imaging of this complex anatomical region are addressed. Finally, cutting-edge techniques are discussed, including susceptibility weighted MRI, ultrashort echo time MRI, zero echo time MRI and a deep learning-based multiparametric MRI technique named 'synthetic CT,' creating CT-like images without ionizing radiaton.

MAIN POINTS

GRE, SWI, UTE, ZTE MRI and synthetic CT sequences depict the cortical outline of the bones better in comparison to conventional MR images.MRI-based synthetic CT can create HU maps and allows for automated segmentation of pelvic bones.The current and cutting-edge MR techniques for bone imaging are complementary in the characterization of a variety of musculoskeletal disorders.

"Do-not-touch" lesions of bone revisited

Incidental bone lesions are encountered frequently in day-to-day practice. Many of these lesions are indeterminate requiring referral to specialist centres for further characterisation with or without biopsy; however, as biopsy has its own drawbacks, not all lesions can be subjected to biopsy. The primary role of a radiologist in these situations is to characterise these lesions based on their imaging appearances into aggressive lesions requiring biopsy and non-aggressive lesions that do not require a biopsy. The term "do-not-touch lesion" is used to describe a lesion with typical radiographic appearances that can be characterised based on radiographic appearances alone without needing a biopsy. With recent advances in imaging, many incidental lesions can be characterised into do-not-touch lesions based on their imaging appearances alone using a single imaging technique or using a combination of imaging techniques and, less frequently, with the additional help of serological investigations, without the need for biopsy. Hence, the definition of do-not-touch lesions of bone needs a revisit. In this article, we attempt to redefine do-not-touch lesions of bone and propose an imaging-based classification for characterisation of these lesions.

Common Skeletal Neoplasms and Nonneoplastic Lesions at 18F-FDG PET/CT

Numerous primary and metastatic osseous lesions and incidental osseous findings are encountered at fluorine 18 (¹⁸F) fluorodeoxyglucose (FDG) PET/CT. These lesions show varying degrees of FDG uptake. Malignancies are generally more FDG avid than are benign lesions, but many exceptions exist. Although aggressive lesions tend to be more FDG avid than nonaggressive lesions, this concept holds true particularly for lesions of the same histologic subtype. In addition, some benign osseous processes such as Paget disease have variable degrees of FDG avidity on the basis of disease metabolic activity. This creates a diagnostic dilemma for radiologists and clinicians, especially in patients with known malignancies, and can result in unnecessary diagnostic imaging or interventions for incidental osseous lesions. Evaluation of morphologic CT characteristics of osseous lesions at FDG PET/CT can be a valuable adjunct to metabolic analysis to further characterize lesions, enhance diagnostic and staging accuracy, and avoid unnecessary invasive biopsy procedures. The authors review the common primary and metastatic bone lesions at FDG PET/CT, with an emphasis on morphologic CT assessment of lesions to help narrow the differential diagnosis. Imaging manifestations of common incidental nonneoplastic bone lesions at FDG PET/CT are discussed to provide information on differentiation of these lesions from osseous neoplasms. The guidelines of the National Comprehensive Cancer Network (NCCN) for common primary osseous malignancies are also summarized. Online supplemental material is available for this article. ^©RSNA, 2021.

Benign Bone-Forming Tumors

Benign bone-forming tumors comprise osteomas, osteoid osteomas, and osteoblastomas. Osteomas affect a wide age range and are usually discovered incidentally. They occur predominantly in the craniofacial skeleton and are classically composed of compact bone. Osteoid osteomas and osteoblastomas are painful lesions occurring in young patients. They are morphologically similar and characterized by FOS gene rearrangement and c-FOS expression at a protein level. Osteoid osteomas are usually smaller than 2 cm in maximum dimension with limited growth potential; osteoblastomas are larger than 2 cm and may be locally aggressive. Histologically both are composed of anastomosing trabeculae of woven bone.

[Skeletal changes due to bone metastases : Morphology and selected differential diagnoses]

BACKGROUND

The detection or exclusion of bone metastases is one of the most frequent tasks faced by the radiologist. The decision has significant and long-term consequences for the patient, therapeutic decisions and prognosis. For these reasons, specialized knowledge of the morphology, diagnostics and differential diagnoses of skeletal metastases is essential for the radiologist.

OBJECTIVE

The various manifestations of skeletal metastases are elaborated and some representative nonmetastatic differential diagnoses are presented.

IMAGING

The way in which metastases are radiologically depicted depends on the primary tumor, the localization of a metastasis, the interaction between metastasis and host bone, concomitant diseases, already initiated treatment and the individual circumstances of the patient. The basis of radiological diagnostics is still projection radiography, albeit with limitations. Computed tomography (CT) and magnetic resonance imaging (MRI) are firmly established methods in diagnostic imaging. Invasive diagnostics, preferably a CT-guided biopsy, are frequently unavoidable.

CONCLUSION

Various radiological procedures form the basis of the diagnostics of bone metastases. In many cases a definite diagnosis, i.e. presence or absence of bone metastases, is possible. In cases in which a suspected diagnosis with justified differential diagnoses arises, the radiologist, referring physician and other specialists to be consulted should advise on the benefits, risks and therapeutic consequences of an invasive procedure, usually by CT-guided biopsy.

Imaging Review of Pediatric Benign Osteocytic Tumors and Latest Updates on Management

Pediatric benign osteocytic tumors include osteoma, enostosis, osteoid osteoma, and osteoblastoma. In pediatric populations, benign bone tumors are more common than malignancies. Benign osteocytic tumors may have a unique clinical presentation that helps narrow the differential diagnosis. A systemic imaging approach should be utilized to reach the diagnosis and guide clinicians in management. Radiographs are the most prevalent and cost-effective imaging modality. Cross-sectional imaging can be utilized for tissue characterization and for evaluation of lesions involving complex anatomical areas such as the pelvis and spine. Computed Tomography (CT) is the modality of choice for diagnosis of osteoid osteoma. CT scan can also be utilized to guide radiofrequency ablation, which has been found to be highly effective in treating osteoid osteoma and osteoblastoma. Enostosis is a no-touch lesion. Osteoma is commonly located in the paranasal sinuses. Osteoma needs an excision if it causes complications due to a mass effect.

Practical Approach to Radiopaque Jaw Lesions

Radiopaque lesions of the jaw are myriad in type and occasionally protean in appearance. In turn, the radiologic analysis of these lesions requires a systematic approach and a broad consideration of clinical and imaging characteristics to enable reliable radiologic diagnosis. Initially categorizing lesions by attenuation pattern provides a practical framework for organizing radiopaque jaw lesions that also reflects important tissue characteristics. Specifically, the appearance of radiopaque lesions can be described as (a) densely sclerotic, (b) ground glass, or (c) mixed lytic-sclerotic, with each category representing a distinct although occasionally overlapping differential diagnosis. After characterizing attenuation pattern, the appreciation of other radiologic features, such as margin characteristics or relationship to teeth, as well as clinical features including demographics and symptoms, can aid in further narrowing the differential diagnosis and lend confidence to clinical decision making. The authors review the potential causes of a radiopaque jaw lesion, including pertinent clinical and radiologic features, and outline a simplified approach to its radiologic diagnosis, with a focus on cross-sectional CT. An invited commentary by Buch is available online. ^©RSNA, 2021.

Enostosis-related epilepsy

Unexpected bone lesions of the skull present a common dilemma, where radiological appearance and patient’s clinical background are crucial to avoid misdiagnosis.

Enostosis are benign sclerotic bone lesions; its aetiology is still unknown and its management is usually conservative, with good prognosis. Most of these lesions are asymptomatic and neurological involvement is rare. We present the first report of enostosis-related epilepsy.

Osteoid Tumors of Bone

We present a review of several bone (osteoid)-forming tumors including enostosis, osteoid osteoma, osteoblastoma, and osteosarcoma. These entities were chosen because they are reasonably common-neither seen every day nor rare. When applicable, recent information about the lesions is included.

Development and Validation of a Radiomics Model for Differentiating Bone Islands and Osteoblastic Bone Metastases at Abdominal CT

Background It is important to diagnose sclerotic bone lesions in order to determine treatment strategy. Purpose To evaluate the diagnostic performance of a CT radiomics-based machine learning model for differentiating bone islands and osteoblastic bone metastases. Materials and Methods In this retrospective study, patients who underwent contrast-enhanced abdominal CT and were diagnosed with a bone island or osteoblastic metastasis between 2015 to 2019 at either of two different institutions were included: institution 1 for the training set and institution 2 for the external test set. Radiomics features were extracted. The random forest (RF) model was built using 10 selected features, and subsequent 10-fold cross-validation was performed. In the test phase, the RF model was tested with an external test set. Three radiologists reviewed the CT images for the test set. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated for the models and each of the three radiologists. The AUCs of the radiomics model and radiologists were compared. Results A total of 177 patients (89 with a bone island and 88 with metastasis; mean age, 66 years ± 12 [standard deviation]; 111 men) were in the training set, and 64 (23 with a bone island and 41 with metastasis; mean age, 69 years ± 14; 59 men) were in the test set. Radiomics features (n = 1218) were extracted. The average AUC of the RF model from 10-fold cross-validation was 0.89 (sensitivity, 85% [75 of 88 patients]; specificity, 82% [73 of 89 patients]; and accuracy, 84% [148 of 177 patients]). In the test set, the AUC of the trained RF model was 0.96 (sensitivity, 80% [33 of 41 patients]; specificity, 96% [22 of 23 patients]; and accuracy, 86% [55 of 64 patients]). The AUCs for the three readers were 0.95 (95% CI: 0.90, 1.00), 0.96 (95% CI: 0.90, 1.00), and 0.88 (95% CI: 0.80, 0.96). The AUC of radiomics model was higher than that of only reader 3 (0.96 vs 0.88, respectively; P = .03). Conclusion A CT radiomics-based random forest model was proven useful for differentiating bone islands from osteoblastic metastases and showed better diagnostic performance compared with an inexperienced radiologist. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Vannier in this issue.

Solitary bone tumor imaging reporting and data system (BTI-RADS): initial assessment of a systematic imaging evaluation and comprehensive reporting method

OBJECTIVES

Identify the most pertinent imaging features for solitary bone tumor characterization using a multimodality approach and propose a systematic evaluation system.

METHODS

Data from a prospective trial, including 230 participants with histologically confirmed bone tumors, typical "do not touch" lesions, and stable chondral lesions, were retrospectively evaluated. Clinical data, CT, and MR imaging features were analyzed by a musculoskeletal radiologist blinded to the diagnosis using a structured report. The benign-malignant distribution of lesions bearing each image feature evaluated was compared to the benign-malignant distribution in the study sample. Benign and malignant indicators were identified. Two additional readers with different expertise levels independently evaluated the study sample.

RESULTS

The sample included 140 men and 90 women (mean age 40.7 ± 18.3 years). The global benign-malignant distribution was 67-33%. Seven imaging features reached the criteria for benign indicators with a mean frequency of benignancy of 94%. Six minor malignant indicators were identified with a mean frequency of malignancy of 60.5%. Finally, three major malignant indicators were identified (Lodwick-Madewell grade III, aggressive periosteal reaction, and suspected metastatic disease) with a mean frequency of malignancy of 82.4%. A bone tumor imaging reporting and data system (BTI-RADS) was proposed. The reproducibility of the BTI-RADS was considered fair (kappa = 0.67) with a mean frequency of malignancy in classes I, II, III, and IV of 0%, 2.2%, 20.1%, and 71%, respectively.

CONCLUSION

BTI-RADS is an evidence-based systematic approach to solitary bone tumor characterization with a fair reproducibility, allowing lesion stratification in classes of increasing malignancy frequency.

TRIAL REGISTRATION

Clinical trial number NCT02895633 .

KEY POINTS

• The most pertinent CT and MRI criteria allowing bone tumor characterization were defined and presented. • Lodwick-Madewell grade III, aggressive periosteal reaction, and suspected metastatic disease should be considered major malignant indicators associated with a frequency of malignancy over 75%. • The proposed evidence-based multimodality reporting system stratifies solitary bone tumors in classes with increasing frequencies of malignancy.

The utility of 2-[18F]FDG-PET/CT maximum SUV versus CT attenuation for directing bone biopsies

OBJECTIVES

This study aimed to compare the accuracy of PET/CT parameters with CT parameters for directing bone biopsies.

METHODS

The study was an IRB-approved retrospective study of 388 patients who underwent both 2-[¹⁸F] FDG PET/CT and CT within 6 weeks before a bone biopsy. Age, sex, cancer type, lesion length, SUV_max, tumor to liver (T/L) ratio, CT attenuation, difference in CT attenuation between the lesion and normal bone (delta CT attenuation), and the absolute delta CT attenuation were used as predictors. T tests and chi-squared tests were used to compare variables. DeLong's test was used to compare receiver operator characteristic (ROC) curves.

RESULTS

We reviewed the data from 388 patients. Of these, 295 patients had bone lesion biopsies, and 93 patients had bone marrow aspirations/biopsies. Biopsies of larger bone lesions (p = 0.033) and bone lesions with higher SUV_max (p = 0.005) were more likely to show malignancy. For bone lesions, the ROC curve for the SUV_max (AUC = 0.6827) was better than the ROC curves for delta CT attenuation (AUC = 0.5766, p = 0.032) and absolute delta CT attenuation (AUC = 0.5491, p = 0.006), but not significantly better than the ROC curves for CT attenuation (AUC = 0.5894, p = 0.061) and T/L ratio (AUC = 0.6778, p = 0.774). A threshold SUV_max of 5.25 had an accuracy of 0.713, sensitivity of 0.766, and specificity of 0.549 to predict malignancy in bone lesion biopsies. None of these variables predicted malignancy in bone marrow biopsies (p > 0.05 for all).

CONCLUSIONS

Metabolic 2-[¹⁸F]FDG PET/CT parameters have more clinical impact for planning bone biopsies as compared to CT parameters.

KEY POINTS

• The 2-[¹⁸F]FDG PET/CT measurement (SUVmax) has more clinical impact for planning bone biopsies as compared to CT measurements. • Neither the change in CT attenuation of the lesion relative to normal bone nor the absolute value of this change was a significant predictor of malignancy. • 2-[¹⁸F]FDG PET/CT may have clinical benefit and an additional role in directing bone biopsies.

CT Attenuation Values Do Not Reliably Distinguish Benign Sclerotic Lesions From Osteoblastic Metastases in Patients Undergoing Bone Biopsy

BACKGROUND. CT attenuation thresholds that accurately distinguish enostoses from untreated osteoblastic metastases have been published. In the Mayo Clinic practices, these thresholds have been applied more broadly to distinguish benign sclerotic bone lesions other than enostoses from osteoblastic metastases. OBJECTIVE. The purpose of this article is to determine if CT attenuation thresholds allow the distinguishing of benign sclerotic bone lesions from osteoblastic metastases in patients undergoing bone biopsy. METHODS. A retrospective search was conducted to identify sclerotic lesions described on CT between October 7, 1998, and July 15, 2018, that underwent subsequent biopsy. Two musculoskeletal radiologists recorded lesions' maximum and mean attenuation. Using previously published attenuation thresholds, sensitivity and specificity for differentiating benign sclerotic lesions from osteoblastic metastases were calculated. ROC curve analysis was performed to determine if more appropriate attenuation thresholds exist. Intraclass correlation coefficients (ICCs) were computed. RESULTS. A total of 280 patients met inclusion criteria. Of those, 162 had malignant biopsy results and 118 had benign biopsy results. Of the 162 malignant lesions, 81 had received prior treatment. Maximum and mean attenuation were not significantly different between benign and malignant lesions for either reader (all p > .05). For reader 1, to distinguish benign from malignant lesions, a maximum attenuation threshold of more than 1060 HU resulted in sensitivity of 23.7%, specificity of 87.0%, and accuracy of 60.6%. A mean attenuation threshold of greater than 885 HU resulted in sensitivity of 19.5%, specificity of 90.7%, and accuracy 60.7%. ROC curve analysis showed AUCs for mean and maximum attenuation thresholds of 51.8% and 54.6%, respectively. Subgroup analyses of benign versus malignant and treated versus untreated lesions had similar results. Similar findings were obtained for reader 2. The two readers' ICC was 0.946 for maximum attenuation and 0.918 for mean attenuation. CONCLUSION. Published attenuation thresholds for distinguishing enostoses from osteoblastic metastases had slightly decreased specificity and markedly decreased sensitivity when applied to the differentiation of benign sclerotic lesions from osteoblastic metastases in our sample of biopsy-proven lesions. ROC analysis showed no high-performing attenuation threshold alternative. CLINICAL IMPACT. Published CT attenuation thresholds intended for distinguishing enostoses from osteoblastic metastases should not be used more broadly. More accurate alternative thresholds could not be derived.

Attenuation correction for human PET/MRI studies

Attenuation correction has been one of the main methodological challenges in the integrated positron emission tomography and magnetic resonance imaging (PET/MRI) field. As standard transmission or computed tomography approaches are not available in integrated PET/MRI scanners, MR-based attenuation correction approaches had to be developed. Aspects that have to be considered for implementing accurate methods include the need to account for attenuation in bone tissue, normal and pathological lung and the MR hardware present in the PET field-of-view, to reduce the impact of subject motion, to minimize truncation and susceptibility artifacts, and to address issues related to the data acquisition and processing both on the PET and MRI sides. The standard MR-based attenuation correction techniques implemented by the PET/MRI equipment manufacturers and their impact on clinical and research PET data interpretation and quantification are first discussed. Next, the more advanced methods, including the latest generation deep learning-based approaches that have been proposed for further minimizing the attenuation correction related bias are described. Finally, a future perspective focused on the needed developments in the field is given.

Atypical Enostoses-Series of Ten Cases and Literature Review

Bone islands (BI; enostoses) may be solitary or occur in the setting of osteopoikilosis (multiple bone islands) and are sometimes associated with Gardner’s Syndrome (osteopoikilosis and colonic polyposis). Characteristic features of bone islands are (1) absence of pain or local tenderness, (2) typical radio dense central appearance with peripheral radiating spicules (rose thorn), (3) Mean CT (computerized tomography) attenuation values above 885 Hounsfield units (HU) (4) absence of uptake on bone scan and (5) radiographic stability over time. However, when enostoses display atypical features of pain, unusual radiographic appearance, aberrant HU, increased radiotracer uptake, and/or enlargement, they can be difficult to differentiate from more sinister bony lesions such as osteoblastic metastasis, low grade central osteosarcoma, osteoid osteoma and osteoblastoma. In this retrospective case series, the demographic, clinical, radiographic, treatment and outcome for ten patients with eleven atypical bone islands (ABI) are presented, some showing associated pain (5), some with atypical radiographic appearance (3), some with increased activity on BS (4), some with documented enlargement over time (7), one with abnormal CT attenuation value, some in the setting of osteopoikilosis (2), one in the setting of Gardner’s Syndrome and one osteoid osteoma simulating a bone island. This series represents the spectrum of presentations of ABI. Comprehensive review of the literature reveals that the previous largest series of ABI showing enlargement as the atypical feature was in younger patients with jaw BI. Hence, this represents one of the largest series reported of ABI of all types in adults.

Advanced Quantitative Spine Imaging

Although advanced quantitative imaging may not be currently used to any degree in the routine reporting of spinal examinations, this situation will change in the not too distant future. Advanced quantitative imaging has already allowed us to understand a great deal more regarding spinal development, marrow physiology, and disease pathogenesis. Radiologists are ideally suited to drive this research forward. To speed up this process and optimize the impact of studies reporting spine quantitative data, we should work toward universal standards on the acquisition of spine data that will allow quantitative studies to be more easily compared, contrasted, and amalgamated.

Subchondroplasty of the Ankle and Hindfoot for Treatment of Osteochondral Lesions and Stress Fractures: Initial Imaging Experience

Objective:To describe the imaging findings of patients treated with subchondroplasty (SCP) of the ankle and hindfoot. Materials and Methods: Eighteen patients (10 men, 8 women; age mean 43.1 years [range 20.1-67.7 years]) underwent ankle and hindfoot SCP at a single center over a 14-month period. Imaging data were reviewed retrospectively by 2 radiologists by consensus interpretation, including preoperative radiography (18), computed tomography (CT) (11), and magnetic resonance imaging (MRI) (13) and postoperative radiography (10), CT (4), and MRI (6). Follow-up imaging was acquired 1 month to 1.6 years following SCP. Results: Indications for SCP included symptomatic bone marrow lesions (BMLs) secondary to an osteochondral lesion (OCL) (16/18) or stress fracture (2/18). While focal radiodensity related to the SCP procedure was retrospectively identifiable on postoperative radiography in all except 1 case (10/11), postprocedural findings were not described by the interpreting radiologist in 6/11 cases. On CT, the average injected synthetic calcium phosphate (CaP) volume was 1.15 cm³ (SD = 0.33 cm³); mean CT attenuation of the injectate was 1220 HU (range 1058-1465 HU). In all patients who had pre- and postoperative MRI (5/18), BML size decreased on follow-up MRI. Extra-osseous extrusion of CaP was not seen on postoperative radiography, CT, or MRI. Conclusion: Physicians should be aware of the expanding preoperative indications and postoperative imaging findings of SCP, which is being performed with increasing frequency in the ankle and hindfoot.Levels of Evidence: Diagnostic, Level III: Retrospective cohort study.

The Spectrum of Rib Neoplasms in Adults: A Practical Approach and Multimodal Imaging Review

OBJECTIVE. Adult neoplasms of the ribs are a heterogeneous group consisting of both benign and aggressive entities. Rib neoplasms have a variety of overlapping imaging features, with much of the imaging data disjointed across the musculoskeletal, thoracic, and oncologic imaging literature. Arrival at accurate diagnosis can therefore be quite challenging. This article consolidates this information and introduces the reader to an algorithmic approach to rib lesion evaluation based on imaging. CONCLUSION. Rib neoplasms are a diverse group of benign and malignant entities, which often makes determining an accurate diagnosis challenging. Evaluation requires a multipronged approach that incorporates radiographic imaging features, nonradiographic imaging findings, lesion location, and clinical data.

Glossary of terms for musculoskeletal radiology

Members of the International Skeletal Society compiled a glossary of terms for musculoskeletal radiology. The authors also represent national radiology or pathology societies in Asia, Australia, Europe, and the USA. We provide brief descriptions of musculoskeletal structures, disease processes, and syndromes and address their imaging features. Given the abundance of musculoskeletal disorders and derangements, we chose to omit most terms relating to neoplasm, spine, intervention, and pediatrics. Consensus agreement was obtained from 19 musculoskeletal radiology societies worldwide.