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Bone imaging has undergone significant changes during the last decades. Ultrasounds, CT, MR imaging, and PET have been added to arteriography, scintigraphy, and radiographs. At the same time, survival of primary malignant tumors has improved with chemotherapy, and local results have improved with conservative surgery. Imaging plays a major role in diagnosis, local and general staging, monitoring the treatment, and detecting recurrences.

Background We investigated the clinical performance of a quantitative multi-modal SPECT/CT reconstruction platform for yielding radioactivity concentrations of bone imaging with 99mTc-methylene diphosphonate (MDP) or 99mTc-dicarboxypropane diphosphonate (DPD). The novel reconstruction incorporates CT-derived tissue information while preserving the delineation of tissue boundaries. We assessed image-based reader concordance and confidence, and determined lesion classification and SUV thresholds from ROC analysis. Methods Seventy-two cancer patients were scanned at three US and two German clinical sites, each contributing two experienced board-certified nuclear medicine physicians as readers. We compared four variants of the reconstructed data resulting from the Flash3D (F3D) and the xSPECT Bone™ (xB) iterative reconstruction methods and presented images to the readers with and without a fused CT, resulting in four combinations. We used an all-or-none approach for inclusion, compiling results only when a reader completed all reads in a subset. After the final read, we conducted a “surrogate truth” reading, presenting all data to each reader. For any remaining discordant lesions, we conducted a consensus read. We next undertook ROC analysis to determine SUV thresholds for differentiating benign and lesional uptake. Results On a five-point rating scale of image quality, xB was deemed better by almost two points in resolution and one point better in overall acceptance compared to F3D. The absolute agreement of the rendered decision between the nine readers was significantly higher with CT information either inside the reconstruction (xB, xBCT) or simply through image fusion (F3DCT): 0.70 (xBCT), 0.67 (F3DCT), 0.64 (xB), and 0.46 (F3D). The confidence level to characterize the lesion was significantly higher (3.03x w/o CT, 1.32x w/CT) for xB than for F3D. There was high correlation between xB and F3D scores for lesion detection and classification, but lesion detection confidence was 41% higher w/o CT, and 21% higher w/CT for xB compared to F3D. Without CT, xB had 6.6% higher sensitivity, 7.1% higher specificity, and 6.9% greater AUC compared to F3D, and similarly with CT-fusion. The overall SUV-criterion (SUVc) of xB (12) exceeded that for xSPECT Quant™ (xQ; 9), an approach not using the tissue delineation of xB. SUV critical numbers depended on lesion volume and location. For non-joint lesions > 6 ml, the AUC for xQ and xB was 94%, with SUVc > 9.28 (xQ) or > 9.68 (xB); for non-joint lesions ≤ 6 ml, AUCs were 81% (xQ) and 88% (xB), and SUVc > 8.2 (xQ) or > 9.1 (xB). For joint lesions, the AUC was 80% (xQ) and 83% (xB), with SUVc > 8.61 (xQ) or > 13.4 (xB). Conclusion The incorporation of high-resolution CT-based tissue delineation in SPECT reconstruction (xSPECT Bone) provides better resolution and detects smaller lesions (6 ml), and the CT component facilitates lesion characterization. Our approach increases confidence, concordance, and accuracy for readers with a wide range of experience. The xB method retained high reading accuracy, despite the unfamiliar image presentation, having greatest impact for smaller lesions, and better localization of foci relative to bone anatomy. The quantitative assessment yielded an SUV-threshold for sensitively distinguishing benign and malignant lesions. Ongoing efforts shall establish clinically usable protocols and SUV thresholds for decision-making based on quantitative SPECT.

Acquiring adequate ultrasound (US) image data is crucial for accurate diagnosis of developmental dysplasia of the hip (DDH), the most common pediatric hip disorder affecting on average one in every one thousand births. Presently, the acquisition of high quality US deemed adequate for diagnostic measurements requires thorough knowledge of infant hip anatomy as well as extensive experience in interpreting such scans. This work aims to provide rapid assurance to the operator, automatically at the time of acquisition, that the data acquired are suitable for accurate diagnosis. To this end, we propose a deep learning model for a fully automatic scan adequacy assessment of 3D US volumes. Our contributions include developing an effective criteria that defines the features required for DDH diagnosis in an adequate 3D US volume, proposing an efficient neural network architecture composed of convolutional layers and recurrent layers for robust classification, and validating our model’s agreement with classification labels from an expert radiologist on real pediatric clinical data. To the best of our knowledge, our work is the first to make use of inter-slice information within a 3D US volume for DDH scan adequacy. Using 200 3D US volumes from 25 pediatric patients, we demonstrate an accuracy of 82% with an area under receiver operating characteristic curve of 0.83 and a clinically suitable runtime of one second.

The ability to ‘see through’ the human body offered by modern medical imaging technologies greatly advanced medical diagnostics, as it is able to uncover abundant information from the hidden organs and tissues, which otherwise are not available to clinicians. Clinicians use medical images to identify abnormality in tissues to diagnose diseases such as tumor and cancer, and to monitor effectiveness of treatments. Medical imaging plays important role in making effective decisions by clinicians. Medical images also provide authentic information to construct accurate and reliable biomechanical models of human body [104, 105, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147]. The four imaging modalities that have been adopted to assess bone quantity and quality are dual energy X-ray absorptiometry (DXA), quantitative computed tomography (QCT), magnetic resonance imaging (MRI) and ultrasonography (US) [148, 149, 150, 151, 152]. Currently, DXA and QCT are the most commonly used ones in either clinic or research. The work principles of the two modalities are briefly introduced in the following sections. As the principles are quite complicated [153, 154], in the following introduction we mainly focus on how bone tissue mass and geometry information are captured by medical imaging and how they are used in assessment of bone quantity and quality, as these information are necessary to understand the biomechanical models described later in this book.

The imaging targets of bone scintigraphy are all changes of bone metabolism independent of its underlying pathology. The technical background of this imaging method will be explained briefly. The use of bone scintigraphy in connection with some selected but frequent clinical questions and entities will be outlined concerning the results of bone scintigraphy in each entity. In addition, limitations of bone scintigraphy with technetium-99m (Tc-99m)-labeled diphosphonates and a comparison to other imaging modalities will be presented.

Radionuclide bone imaging is a common investigation performed in most nuclear medicine departments. In early days, 87mSr was the bone agent used and interest in 99mTc for Nuclear Medicine imaging began in the early 1960’s. The first technetium labelled bone agent, 99mTc-polyphosphate, was described by Subramanian and McAfee in 1971. Recent years have seen a further change in the choice of optimum tracer as the wider availability of PET scanners has brought renewed interest in 18F-fluoride. The 99mTc-MDP bone scan is an old and trusted friend that continues to perform with some distinction, but it is apparent that we can do significantly better with 18F. This chapters summarises, the growth and expansion of Bone Radionuclide Imaging, Quantitation and Bone Densitometry in the UK.

This chapter concerns the experimental evaluations of our custom-built array when connected to and controlled by a SonixTablet system (Ultrasonix™ Analogic Ultrasound, Richmond, BC). The purpose of these evaluations was to demonstrate functionality under relatively ideal circumstances, representing a first step toward bone imaging with a low-frequency radial array. Following the fabrication of the radial array prototype, software was then developed to interface the prototype with an Ultrasonix™ system. This platform is one of the few that allows access to the data acquisition toolbox. Its research platform allows the user to store, modify, and conduct signal processing on the raw radio frequency (RF) data obtained by each element of the array.