The application of nanotechnology concepts to medicine joins two large cross-disciplinary fields with an unprecedented societal and economical potential arising from the natural combination of specific achievements in the respective fields. The common basis evolves from the molecular-scale properties relevant to the two fields. Local probes and molecular imaging techniques allow surface and interface properties to be characterized on a nanometer scale at predefined locations, while chemical approaches offer the opportunity to elaborate and address surfaces, for example, for targeted drug delivery, enhanced biocompatibility, and neuroprosthetic purposes. However, concerns arise in this cross-disciplinary area about toxicological aspects and ethical implications. This Review gives an overview of selected recent developments and applications of nanomedicine.

Nanomedicine--challenge and perspectives.

Expert landmark correspondences are widely reported for evaluating deformable image registration (DIR) spatial accuracy. In this report, we present a framework for objective evaluation of DIR spatial accuracy using large sets of expert-determined landmark point pairs. Large samples (>1100) of pulmonary landmark point pairs were manually generated for five cases. Estimates of inter- and intra-observer variation were determined from repeated registration. Comparative evaluation of DIR spatial accuracy was performed for two algorithms, a gradient-based optical flow algorithm and a landmark-based moving least-squares algorithm. The uncertainty of spatial error estimates was found to be inversely proportional to the square root of the number of landmark point pairs and directly proportional to the standard deviation of the spatial errors. Using the statistical properties of this data, we performed sample size calculations to estimate the average spatial accuracy of each algorithm with 95% confidence intervals within a 0.5 mm range. For the optical flow and moving least-squares algorithms, the required sample sizes were 1050 and 36, respectively. Comparative evaluation based on fewer than the required validation landmarks results in misrepresentation of the relative spatial accuracy. This study demonstrates that landmark pairs can be used to assess DIR spatial accuracy within a narrow uncertainty range.

https://iopscience.iop.org/article/10.1088/0031-9155/54/7/001/pdf

A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets.

Historically, anatomical CT and MR images were used to delineate the gross tumour volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern radiation therapy units and the widespread availability of combined PET/CT scanners stimulated the development of biological PET imaging-guided radiation therapy treatment planning with the aim to produce highly conformal radiation dose distribution to the tumour. One of the most difficult issues facing PET-based treatment planning is the accurate delineation of target regions from typical blurred and noisy functional images. The major problems encountered are image segmentation and imperfect system response function. Image segmentation is defined as the process of classifying the voxels of an image into a set of distinct classes. The difficulty in PET image segmentation is compounded by the low spatial resolution and high noise characteristics of PET images. Despite the difficulties and known limitations, several image segmentation approaches have been proposed and used in the clinical setting including thresholding, edge detection, region growing, clustering, stochastic models, deformable models, classifiers and several other approaches. A detailed description of the various approaches proposed in the literature is reviewed. Moreover, we also briefly discuss some important considerations and limitations of the widely used techniques to guide practitioners in the field of radiation oncology. The strategies followed for validation and comparative assessment of various PET segmentation approaches are described. Future opportunities and the current challenges facing the adoption of PET-guided delineation of target volumes and its role in basic and clinical research are also addressed.

/pdf/pet-guided-delineation-of-radiation-therapy-treatment-3ypvotnulc.pdf

PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques

Respiratory Motion in Positron Emission Tomography/Computed Tomography: A Review

PET imaging of atherosclerosis can quantify several in vivo pathological processes occurring within the arterial system. (18)F-fluorodeoxyglucose (FDG) is the most-commonly used PET tracer, with well-established roles in atherosclerosis imaging. In this context, the (18)F-FDG signal largely reflects tracer uptake by plaque macrophages and, therefore, inflammation with smaller contributions from other resident cell types. As a marker of plaque vulnerability, the (18)F-FDG PET signal can be used to help to identify patients at the highest risk of clinical events. (18)F-FDG PET has also been used successfully as a surrogate end point in clinical trials of antiatherosclerotic therapies. Nonetheless, imaging atherosclerosis with (18)F-FDG has several limitations. Most importantly, coronary artery imaging is problematic because (18)F-FDG accumulates in all cells that metabolize glucose, and background myocardial uptake is generally greater than any signal originating from a plaque. To help to overcome these limitations, several novel PET tracers, which might be more-specifically targeted than (18)F-FDG, have been tested in atherosclerosis imaging. These tracers are designed to track inflammation, hypoxia, neoangiogenesis, or active calcification, which are all precursors to plaque rupture and its clinical sequelae.

PET imaging of inflammation in atherosclerosis

Respiratory gating is used for reducing the effects of breathing motion in a wide range of applications from radiotherapy treatment to diagnostical imaging. Different methods are feasible for respiratory gating. In this study seven gating methods were developed and tested on positron emission tomography (PET) listmode data. The results of seven patient studies were compared quantitatively with respect to motion and noise. (1) Equal and (2) variable time-based gating methods use only the time information of the breathing cycle to define respiratory gates. (3) Equal and (4) variable amplitude-based gating approaches utilize the amplitude of the respiratory signal. (5) Cycle-based amplitude gating is a combination of time and amplitude-based techniques. A baseline correction was applied to methods (3) and (4) resulting in two new approaches: Baseline corrected (6) equal and (7) variable amplitude-based gating. Listmode PET data from seven patients were acquired together with a respiratory signal. Images were reconstructed applying the seven gating methods. Two parameters were used to quantify the results: Motion was measured as the displacement of the heart due to respiration and noise was defined as the standard deviation of pixel intensities in a background region. The amplitude-based approaches (3) and (4) were superior to the time-based methods (1) and (2). The improvement in capturing the motion was more than 30% (up to 130%) in all subjects. The variable time (2) and amplitude (4) methods had a more uniform noise distribution among all respiratory gates compared to equal time (1) and amplitude (3) methods. Baseline correction did not improve the results. Out of seven different respiratory gating approaches, the variable amplitude method (4) captures the respiratory motion best while keeping a constant noise level among all respiratory phases.

Respiratory gating in positron emission tomography: a quantitative comparison of different gating schemes.

Gating methods acquiring biosignals (such as electrocardiography [ECG] and respiration) during PET enable one to reduce motion effects that potentially lead to image blurring and artifacts. This study evaluated different cardiac and respiratory gating methods: one based on ECG signals for cardiac gating and video signals for respiratory gating; 2 others based on measured inherent list mode events. Methods: Twenty-nine patients with coronary artery disease underwent a 20-min ECG-gated single-bed list mode PET scan of the heart. Of these, 17 were monitored by a video camera registering a marker on the patient9s abdomen, thus capturing the respiratory motion for PET gating (video method). Additionally, respiratory and cardiac gating information was deduced without auxiliary measurements by dividing the list mode stream in 50-ms frames and then either determining the number of coincidences (sensitivity method) or computing the axial center of mass and SD of the measured counting rates in the same frames (center-of-mass method). The gated datasets (respiratory and cardiac gating) were reconstructed without attenuation correction. Measured wall thicknesses, maximum displacement of the left ventricular wall, and ejection fraction served as measures of the exactness of gating. Results: All methods successfully captured respiratory motion and significantly decreased motion-induced blurring in the gated images. The center-of-mass method resulted in significantly larger left ventricular wall displacements than did the sensitivity method (P

https://jnm.snmjournals.org/content/jnumed/50/5/674.full.pdf

List Mode–Driven Cardiac and Respiratory Gating in PET

Motion is a source of degradation in positron emission tomography (PET)/computed tomography (CT) images. As the PET images represent the sum of information over the whole respiratory cycle, attenuation correction with the help of CT images may lead to false staging or quantification of the radioactive uptake especially in the case of small tumors. We present an approach avoiding these difficulties by respiratory-gating the PET data and correcting it for motion with optical flow algorithms. The resulting dataset contains all the PET information and minimal motion and, thus, allows more accurate attenuation correction and quantification.

Lung motion correction on respiratory gated 3-D PET/CT images

The problem of motion is well known in positron emission tomography (PET) studies. The PET images are formed over an elongated period of time. As the patients cannot hold breath during the PET acquisition, spatial blurring and motion artifacts are the natural result. These may lead to wrong quantification of the radioactive uptake. We present a solution to this problem by respiratory-gating the PET data and correcting the PET images for motion with optical flow algorithms. The algorithm is based on the combined local and global optical flow algorithm with modifications to allow for discontinuity preservation across organ boundaries and for application to 3-D volume sets. The superiority of the algorithm over previous work is demonstrated on software phantom and real patient data.

Respiratory Motion Correction in 3-D PET Data With Advanced Optical Flow Algorithms

Respiratory gating is the method of dividing the data from a tomographic scan with respect to the respiratory phase of the patient It enables more accurate images by reducing the effects of motion blur and attenuation artifacts due to motion However, it induces image degradation due to higher noise levels as the number of events per gate is reduced Due to lack of systematic studies in this regard, different numbers of gates are being used in the scientific and clinical practice The present study aims at examining the relationship between the respiratory signal, the number of gates required for accurate motion detection, and the level of noise with two different methods of gating: (1) Amplitude-based gating and (2) time-based gating Patient data with a wide range of motion are used for the study The results show that time-based gating underestimates the real respiratory displacement by up to 50% The optimal number of gates is 8 for amplitude- and 6 for time-based gatings The noise properties remain the same with either method but noise increases with increasing number of gates

Mohammad Dawood

Papers

Respiratory gating in positron emission tomography: a quantitative comparison of different gating schemes.

List Mode–Driven Cardiac and Respiratory Gating in PET

Lung motion correction on respiratory gated 3-D PET/CT images

Respiratory Motion Correction in 3-D PET Data With Advanced Optical Flow Algorithms

Optimal number of respiratory gates in positron emission tomography: a cardiac patient study.