Influence of the Computer-Aided Decision Support System Design on Ultrasound-Based Breast Cancer Classification

Automation of medical data analysis is an important topic in modern cancer diagnostics, aiming at robust and reproducible workflows. Therefore, we used a dataset of breast US images (252 malignant and 253 benign cases) to realize and compare different strategies for CAD support in lesion detection and classification. Eight different datasets (including pre-processed and spatially augmented images) were prepared, and machine learning algorithms (i.e., Viola-Jones; YOLOv3) were trained for lesion detection. The radiomics signature (RS) was derived from detection boxes and compared with RS derived from manually obtained segments. Finally, the classification model was established and evaluated concerning accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic curve. After training on a dataset including logarithmic derivatives of US images, we found that YOLOv3 obtains better results in breast lesion detection (IoU: 0.544 ± 0.081; LE: 0.171 ± 0.009) than the Viola-Jones framework (IoU: 0.399 ± 0.054; LE: 0.096 ± 0.016). Interestingly, our findings show that the classification model trained with RS derived from detection boxes and the model based on the RS derived from a gold standard manual segmentation are comparable (p-value = 0.071). Thus, deriving radiomics signatures from the detection box is a promising technique for building a breast lesion classification model, and may reduce the need for the lesion segmentation step in the future design of CAD systems.

Hybrid total-body pet scanners-current status and future perspectives

Purpose Since the 1990s, PET has been successfully combined with MR or CT systems. In the past years, especially PET systems have seen a trend towards an enlarged axial field of view (FOV), up to a factor of ten. Methods Conducting a thorough literature research, we summarize the status quo of contemporary total-body (TB) PET/CT scanners and give an outlook on possible future developments. Results Currently, three human TB PET/CT systems have been developed: The PennPET Explorer, the uExplorer, and the Biograph Vision Quadra realize aFOVs between 1 and 2 m and show a tremendous increase in system sensitivity related to their longer gantries. Conclusion The increased system sensitivity paves the way for short-term, low-dose, and dynamic TB imaging as well as new examination methods in almost all areas of imaging.

Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology

Deep learning is a powerful tool in computational pathology: it can be used for tumor detection and for predicting genetic alterations based on histopathology images alone. Conventionally, tumor detection and prediction of genetic alterations are two separate workflows. Newer methods have combined them, but require complex, manually engineered computational pipelines, restricting reproducibility and robustness. To address these issues, we present a new method for simultaneous tumor detection and prediction of genetic alterations: The Slide-Level Assessment Model (SLAM) uses a single off-the-shelf neural network to predict molecular alterations directly from routine pathology slides without any manual annotations, improving upon previous methods by automatically excluding normal and non-informative tissue regions. SLAM requires only standard programming libraries and is conceptually simpler than previous approaches. We have extensively validated SLAM for clinically relevant tasks using two large multicentric cohorts of colorectal cancer patients, Darmkrebs: Chancen der Verhütung durch Screening (DACHS) from Germany and Yorkshire Cancer Research Bowel Cancer Improvement Programme (YCR-BCIP) from the UK. We show that SLAM yields reliable slide-level classification of tumor presence with an area under the receiver operating curve (AUROC) of 0.980 (confidence interval 0.975, 0.984; n = 2,297 tumor and n = 1,281 normal slides). In addition, SLAM can detect microsatellite instability (MSI)/mismatch repair deficiency (dMMR) or microsatellite stability/mismatch repair proficiency with an AUROC of 0.909 (0.888, 0.929; n = 2,039 patients) and BRAF mutational status with an AUROC of 0.821 (0.786, 0.852; n = 2,075 patients). The improvement with respect to previous methods was validated in a large external testing cohort in which MSI/dMMR status was detected with an AUROC of 0.900 (0.864, 0.931; n = 805 patients). In addition, SLAM provides human-interpretable visualization maps, enabling the analysis of multiplexed network predictions by human experts. In summary, SLAM is a new simple and powerful method for computational pathology that could be applied to multiple disease contexts. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

High throughput software-based gradient tree boosting positioning for PET systems

The supervised machine learning technique Gradient Tree Boosting (GTB) has shown good accuracy for position estimation of gamma interaction in PET crystals for bench-top experiments while its computational requirements can easily be adjusted. Transitioning to preclinical and clinical applications requires near real-time processing in the scale of full PET systems. In this work, a high throughput GTB-based singles positioning C++ implementation is proposed and a series of optimizations are evaluated regarding their effect on the achievable processing throughput. Moreover, the crucial feature and parameter selection for GTB is investigated for the segmented detectors of the Hyperion II^DPET insert with two main models and a range of GTB hyperparameters. The proposed framework achieves singles positioning throughputs of more than 9.5 GB/s for smaller models and of 240 MB/s for more complex models on a recent Intel Skylake server. Detailed throughput analysis reveals the key performance limiting factors, and an empirical throughput model is derived to guide the GTB model selection process and scanner design decisions. The throughput model allows for throughput estimations with a mean absolute error (MAE) of 175.78 MB/s.

Study of flow effects on temperature-controlled radiofrequency ablation using phantom experiments and forward simulations

PURPOSE

Blood flow is known to add variability to hepatic radiofrequency ablation (RFA) treatment outcomes. However, few studies exist on its impact on temperature-controlled RFA. Hence, we investigate large-scale blood flow effects on temperature-controlled RFA in flow channel experiments and numerical simulations.

METHODS

Ablation zones were induced in tissue-mimicking, thermochromic phantoms with a single flow channel, using an RF generator with temperature-controlled power delivery and a monopolar needle electrode. Channels were generated by molding the phantom around a removable rod. Channel radius and saline flow rate were varied to study the impact of flow on (i) the ablated cross-sectional area, (ii) the delivered generator power, and (iii) the occurrence of directional effects on the thermal lesion. Finite volume simulations reproducing the experimental geometry, flow conditions, and generator power input were conducted and compared to the experimental ablation outcomes.

RESULTS

Vessels of different channel radii r affected the ablation outcome in different ways. For r = 0.275  mm, the ablated area decreased with increasing flow rate while the energy input was hardly affected. For r = 0.9  mm and r = 2.3  mm, the energy input increased toward larger flow rates; for these radii, the ablated area decreased and increased toward larger flow rates, respectively, while still being reduced overall as compared to the reference experiment without flow. Directional effects, that is, local shrinking of the lesion upstream of the needle and an extension thereof downstream, were observed only for the smallest radius. The simulations qualitatively confirmed these observations. As compared to performing the simulations without flow, including flow effects in the simulations reduced the mean absolute error between experimental and simulated ablated areas from 0.23 to 0.12.

CONCLUSION

While the temperature control mechanism did not detect the heat sink effect in the case of the smallest channel radius, it counteracted the heat sink effect in the case of the larger channel radii with an increased energy input; this explains the increase in ablated area toward high flow rates (for r = 2.3  mm). The experiments in a simple phantom setup, thus, contribute to a good understanding of the phenomenon and are suitable for model validation.

Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization

Unmasking the decision making process of machine learning models is essential for implementing diagnostic support systems in clinical practice. Here, we demonstrate that adversarially trained models can significantly enhance the usability of pathology detection as compared to their standard counterparts. We let six experienced radiologists rate the interpretability of saliency maps in datasets of X-rays, computed tomography, and magnetic resonance imaging scans. Significant improvements are found for our adversarial models, which are further improved by the application of dual-batch normalization. Contrary to previous research on adversarially trained models, we find that accuracy of such models is equal to standard models, when sufficiently large datasets and dual batch norm training are used. To ensure transferability, we additionally validate our results on an external test set of 22,433 X-rays. These findings elucidate that different paths for adversarial and real images are needed during training to achieve state of the art results with superior clinical interpretability.

Molecular magnetic resonance imaging of Alpha-v-Beta-3 integrin expression in tumors with ultrasound microbubbles

Microbubbles (MB) are used as ultrasound (US) contrast agents and can be efficiently targeted against markers of angiogenesis and inflammation. Due to their gas core, MB locally alter susceptibilities in magnetic resonance imaging (MRI), but unfortunately, the resulting contrast is low and not sufficient to generate powerful molecular MRI probes. Therefore, we investigated whether a potent molecular MR agent can be generated by encapsulating superparamagnetic iron oxide nanoparticles (SPION) in the polymeric shell of poly (n-butylcyanoacrylate) (PBCA) MB and targeted them against α_vβ₃ integrins on the angiogenic vasculature of 4T1 murine breast carcinomas. SPION-MB consist of an air core and a multi-layered polymeric shell enabling efficient entrapment of SPION. The mean size of SPION-MB was 1.61 ± 0.32 μm. Biotin-streptavidin coupling was employed to functionalize the SPION-MB with cyclic RGDfK (Arg-Gly-Asp) and RADfK (Arg-Ala-Asp) peptides. Cells incubated with RGD-SPION-MB showed enhanced transverse relaxation rates compared with SPION-MB and blocking α_vβ₃ integrin receptors with excess free cRGDfK significantly reduced RGD-SPION-MB binding. Due to the fast binding of RGD-SPION-MB in vivo, dynamic susceptibility contrast MRI was employed to track their retention in tumors in real-time. Higher retention of RGD-SPION-MB was observed compared with SPION-MB and RAD-SPION-MB. To corroborate our MRI results, molecular US was performed the following day using the destruction-replenishment method. Both imaging modalities consistently indicated higher retention of RGD-SPION-MB in angiogenic vessels compared with SPION-MB and RAD-SPION-MB. Competitive blocking experiments in mice further confirmed that the binding of RGD-SPION-MB to α_vβ₃ integrin receptors is specific. Overall, this study demonstrates that RGD-SPION-MB can be employed as molecular MR/US contrast agents and are capable of assessing the α_vβ₃ integrin expression in the neovasculature of malignant tumors.

RF shielding materials for highly-integrated PET/MRI systems

Integration of magnetic resonance imaging (MRI) and positron emission tomography (PET) into a simultaneous device calls for adaptations of the radio frequency (RF) shielding concept. Conventional PET module housings fully encase the entire PET detector to reduce mutual interference. Excluding passive components, i.e. scintillators, from the housings, offers integration advantages, e.g. by reducing the overall housing volume or utilizing bigger scintillators. However, locating the scintillator outside of the RF shielding requires an optically transparent RF shielding interface between the scintillators and the photodetector to close the aperture. Therefore, a careful evaluation and selection of RF materials is essential to ensure an excellent PET/MRI system performance. To this end, we examined 10 materials (coated glasses, coated foils, meshes). The shielding effectiveness (SE) was evaluated at 100 and 300 MHz. PET performance was tested for single event registration and coincident events by integrating the material into the PET detector stack between the digital silicon photomultiplier photodetector array and one-to-one coupled scintillator. We determined photon attenuation (PA), energy resolution (dE/E), and coincidence resolving time (CRT) and compared to reference measurements for each material group. MRI compatibility was assessed by analyzing the material influence on the main magnetic field (B₀) homogeneity. The coated glasses and foils exhibited SEs of up to 25 dB at 300 MHz. Both had a PA < 23% with dE/E and CRT comparable to the reference measurements, and no measurable impact on the B₀field was registered. The meshes exhibited higher SEs up to 56 dB, but also a PA > 58% with a higher impact on dE/E and CRT. Only one mesh affected B₀homogeneity. Overall, we recommend the coated foil HS 9400 for integration concepts as it exhibited a good performance with SE = 25 dB, PA = 22%, resulting in a PET performance of dE/E = 12% and CRT = 274 ps.

Image-derived mean velocity measurement for prediction of coronary flow reserve in a canonical stenosis phantom using magnetic particle imaging

INTRODUCTION

Aim of this study is to evaluate whether magnetic particle imaging (MPI) is capable of measuring velocities occurring in the coronary arteries and to compute coronary flow reserve (CFR) in a canonical phantom as a preliminary study.

METHODS

For basic velocity measurements, a circulation phantom was designed containing replaceable glass tubes with three varying inner diameters, matching coronary-vessel diameters. Standardised boluses of superparamagnetic-iron-oxide-nanoparticles were injected and visualised by MPI. Two image-based techniques were competitively applied to calibrate the respective glass tube and to compute the mean velocity: full-duration-at-half-maximum (FDHM) and tracer dilution (TD) method. For CFR-calculation, four necessary settings of the circulation model of a virtual vessel with an inner diameter of 4 mm were generated using differently sized glass tubes and a stenosis model. The respective velocities in stenotic glass tubes were computed without recalibration.

RESULTS

On velocity level, comparison showed a good agreement (rFDHM = 0.869, rTD = 0.796) between techniques, preferably better for 4 mm and 6 mm inner diameter glass tubes. On CFR level MPI-derived CFR-prediction performed considerably inferior with a relative error of 20-44%.

CONCLUSIONS

MPI has the ability to reliably measure coronary blood velocities at rest as well as under hyperaemia and therefore may be suitable for CFR calculation. Calibration-associated accuracy of CFR-measurements has to be improved substantially in further studies.

Evaluation of the PETsys TOFPET2 ASIC in multi-channel coincidence experiments

BACKGROUND

Aiming to measure the difference in arrival times of two coincident γ-photons with an accuracy in the order of 200ps, time-of-flight positron emission tomography systems commonly employ silicon photomultipliers (SiPMs) and high-resolution digitization electronics, application specific integrated circuits (ASICs). This work evaluates the performance of the TOFPET2 ASIC, released by PETsys Electronics S.A. in 2017, dependent on its configuration parameters in multi-channel coincidence measurements.

METHODS

SiPM arrays fabricated by different vendors (KETEK, SensL, Hamamatsu, Broadcom) were tested in combination with the ASIC. Scintillator arrays featuring different reflector designs and different configurations of the TOFPET2 ASIC software parameters were evaluated. The benchtop setup used is provided with the TOFPET2 ASIC evaluation kit by PETsys Electronics S.A.

RESULTS

Compared to existing studies featuring the TOFPET2 ASIC, multi-channel performance results dependent on a larger set of ASIC configuration parameters were obtained that have not been reported to this extend so far. The ASIC shows promising CRTs down to 219.9 ps in combination with two Hamamatsu S14161-3050-HS-08 SiPM arrays (128 channels read out, energy resolution 13.08%) and 216.1 ps in combination with two Broadcom AFBR-S4N44P643S SiPM arrays (32 channels read out, energy resolution 9.46%). The length of the trigger delay of the dark count suppression scheme has an impact on the ASIC performance and can be configured to further improve the coincidence resolution time. The integrator gain configuration has been investigated and allows an absolute improvement of the energy resolution by up to 1% at the cost of the linearity of the energy spectrum.

CONCLUSION

Measuring up to the time-of-flight performance of state-of-the-art positron emission tomography (ToF-PET) systems while providing a uniform and stable readout for multiple channels at the same time, the TOFPET2 ASIC is treated as promising candidate for the integration in future ToF-PET systems.

Evaluation of the radiofrequency performance of a wide-bore 1.5 T positron emission tomography/magnetic resonance imaging body coil for radiotherapy planning

Background and purpose

The restricted bore diameter of current simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) systems can be an impediment to achieving similar patient positioning during PET/MRI planning and radiotherapy. Our goal was to evaluate the B₁ transmit (B₁⁺) uniformity, B₁⁺ efficiency, and specific absorption rate (SAR) of a novel radiofrequency (RF) body coil design, in which RF shielded PET detectors were integrated with the specific aim of enabling a wide-bore PET/MRI system.

Materials and methods

We designed and constructed a wide-bore PET/MRI RF body coil to be integrated with a clinical MRI system. To increase its inner bore diameter, the PET detectors were positioned between the conductors and the RF shield of the RF body coil. Simulations and experiments with phantoms and human volunteers were performed to compare the B₁⁺ uniformity, B₁⁺ efficiency, and SAR between our design and the clinical body coil.

Results

In the simulations, our design achieved nearly the same B₁⁺ field uniformity as the clinical body coil and an almost identical SAR distribution. The uniformity findings were confirmed by the physical experiments. The B₁⁺ efficiency was 38% lower compared to the clinical body coil.

Conclusions

To achieve wide-bore PET/MRI, it is possible to integrate shielding for PET detectors between the body coil conductors and the RF shield without compromising MRI performance. Reduced B₁⁺ efficiency may be compensated by adding a second RF amplifier. This finding may facilitate the application of simultaneous whole-body PET/MRI in radiotherapy planning.

Hybrid MPI-MRI System for Dual-Modal In Situ Cardiovascular Assessments of Real-Time 3D Blood Flow Quantification-A Pre-Clinical In Vivo Feasibility Investigation

Non-invasive quantification of functional parameters of the cardiovascular system, in particular the heart, remains very challenging with current imaging techniques. This aspect is mainly due to the fact, that the spatio-temporal resolution of current imaging methods, such as Magnetic Resonance Imaging (MRI) or Positron Emission Tomography (PET), does not offer the desired data repetition rates in the context of real-time data acquisition and thus, can cause artifacts and misinterpretations in accelerated data acquisition approaches. We present a fast non-invasive and quantitative dual-modal in situ cardiovascular assessment using a hybrid imaging system which combines the new imaging modality Magnetic Particle Imaging (MPI) and MRI. This pre-clinical hybrid imaging system provides either a 0.5 T homogeneous B₀ field for MRI or a 2.2 T/m gradient field featuring a Field-Free-Point for MPI. A comprehensive coil system allows in both imaging modes for spatial encoding, signal excitation and reception. In this work, 3-dimensional anatomical information acquired with MRI is combined with in situ sequentially acquired time-resolved 3D (i.e. 3D + t) MPI bolus tracking of superparamagnetic iron oxide nanoparticles. MPI data were acquired during a 21 [Formula: see text] (40 μ mol(Fe)/kg_BW) bolus tail vein injection under free-breathing with an ungated and non-triggered MPI scan with a repetition rate of 46 volumes per seconds. We successfully determined quantitative hemodynamics as 3D + t velocity vector estimations of a beating rat's heart by analyzing 3 seconds of 3D + t MPI image data. The used hybrid system allows for MR-based MPI Field-of-View planning and cardiac cross-sectional anatomy analysis, precise co-registration of dual-modal datasets, as well as for MPI-based hemodynamic functional analysis using an optical flow technique. We present the first in-vivo results of a new methodology, allowing for fast, non-invasive, quantitative and in situ hybrid cardiovascular assessment, showing its potential for future clinical applications.

Breaking medical data sharing boundaries by using synthesized radiographs

Computer vision (CV) has the potential to change medicine fundamentally. Expert knowledge provided by CV can enhance diagnosis. Unfortunately, existing algorithms often remain below expectations, as databases used for training are usually too small, incomplete, and heterogeneous in quality. Moreover, data protection is a serious obstacle to the exchange of data. To overcome this limitation, we propose to use generative models (GMs) to produce high-resolution synthetic radiographs that do not contain any personal identification information. Blinded analyses by CV and radiology experts confirmed the high similarity of synthesized and real radiographs. The combination of pooled GM improves the performance of CV algorithms trained on smaller datasets, and the integration of synthesized data into patient data repositories can compensate for underrepresented disease entities. By integrating federated learning strategies, even hospitals with few datasets can contribute to and benefit from GM training.

Confounding factors in breast magnetic resonance fingerprinting: B 1 + , slice profile, and diffusion effects

PURPOSE

Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model-based reconstruction. This study characterizes the influence of in-plane B 1 + , slice profile and diffusion effects on T₁ and T₂ estimation in the female breast at 1.5T.

METHODS

Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE.

RESULTS

Theoretic analysis predicts T₁ under-/T₂ overestimation if the nominal flip angles are underestimated and inversely, T₁ under-/T₂ overestimation if omitting slice profile correction, and T₁ under-/T₂ underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in-plane B 1 + effects occurred in vivo, causing T₂ left-right inhomogeneity between both breasts. Their correction decreased the T₂ difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T₂ most strongly, resulting in -22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions.

CONCLUSION

Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.

Automation of data analysis in molecular cancer imaging and its potential impact on future clinical practice

Digitalization, especially the use of machine learning and computational intelligence, is considered to dramatically shape medical procedures in the near future. In the field of cancer diagnostics, radiomics, the extraction of multiple quantitative image features and their clustered analysis, is gaining increasing attention to obtain more detailed, reproducible, and meaningful information about the disease entity, its prognosis and the ideal therapeutic option. In this context, automation of diagnostic procedures can improve the entire pipeline, which comprises patient registration, planning and performing an imaging examination at the scanner, image reconstruction, image analysis, and feeding the diagnostic information from various sources into decision support systems. With a focus on cancer diagnostics, this review article reports and discusses how computer-assistance can be integrated into diagnostic procedures and which benefits and challenges arise from it. Besides a strong view on classical imaging modalities like x-ray, CT, MRI, ultrasound, PET, SPECT and hybrid imaging devices thereof, it is outlined how imaging data can be combined with data deriving from patient anamnesis, clinical chemistry, pathology, and different omics. In this context, the article also discusses IT infrastructures that are required to realize this integration in the clinical routine. Although there are still many challenges to comprehensively implement automated and integrated data analysis in molecular cancer imaging, the authors conclude that we are entering a new era of medical diagnostics and precision medicine.

Emerging methods in radiology

Imaging modalities have developed rapidly in recent decades. In addition to improved resolution as well as whole-body and faster image acquisition, the possibilities of functional and molecular examination of tissue pathophysiology have had a decisive influence on imaging diagnostics and provided ground-breaking knowledge. Many promising approaches are currently being pursued to increase the application area of devices and contrast media and to improve their sensitivity and quantitative informative value. These are complemented by new methods of data processing, multiparametric data analysis, and integrated diagnostics. The aim of this article is to provide an overview of technological innovations that will enrich clinical imaging in the future, and to highlight the resultant diagnostic options. These relate to the established imaging methods such as CT, MRI, ultrasound, PET, and SPECT but also to new methods such as magnetic particle imaging (MPI), optical imaging, and photoacoustics. In addition, approaches to radiomic image evaluation are explained and the chances and difficulties for their broad clinical introduction are discussed. The potential of imaging to describe pathophysiological relationships in ever increasing detail, both at whole-body and tissue level, can in future be used to better understand the mechanistic effect of drugs, to preselect patients to therapies, and to improve monitoring of therapy success. Consequently, the use of interdisciplinary integrated diagnostics will greatly change and enrich the profession of radiologists.

Comments on the NEMA NU 4-2008 Standard on Performance Measurement of Small Animal Positron Emission Tomographs

The National Electrical Manufacturers Association’s (NEMA) NU 4-2008 standard specifies methodology for evaluating the performance of small-animal PET scanners. The standard’s goal is to enable comparison of different PET scanners over a wide range of technologies and geometries used. In this work, we discuss if the NEMA standard meets these goals and we point out potential flaws and improvements to the standard.For the evaluation of spatial resolution, the NEMA standard mandates the use of filtered backprojection reconstruction. This reconstruction method can introduce star-like artifacts for detectors with an anisotropic spatial resolution, usually caused by parallax error. These artifacts can then cause a strong dependence of the resulting spatial resolution on the size of the projection window in image space, whose size is not fully specified in the NEMA standard. If the PET ring has detectors which are perpendicular to a Cartesian axis, then the resolution along this axis will typically improve with larger projection windows.We show that the standard’s equations for the estimation of the random rate for PET systems with intrinsic radioactivity are circular and not satisfiable. However, a modified version can still be used to determine an approximation of the random rates under the assumption of negligible random rates for small activities and a constant scatter fraction. We compare the resulting estimated random rates to random rates obtained using a delayed coincidence window and two methods based on the singles rates. While these methods give similar estimates, the estimation method based on the NEMA equations overestimates the random rates.In the NEMA standard’s protocol for the evaluation of the sensitivity, the standard specifies to axially step a point source through the scanner and to take a different scan for each source position. Later, in the data analysis section, the standard does not specify clearly how the different scans have to be incorporated into the analysis, which can lead to unclear interpretations of publicized results.The standard’s definition of the recovery coefficients in the image quality phantom includes the maximum activity in a region of interest, which causes a positive correlation of noise and recovery coefficients. This leads to an unintended trade-off between desired uniformity, which is negatively correlated with variance (i.e., noise), and recovery.With this work, we want to start a discussion on possible improvements in a next version of the NEMA NU-4 standard.

Size-isolation of superparamagnetic iron oxide nanoparticles improves MRI, MPI and hyperthermia performance

Superparamagnetic iron oxide nanoparticles (SPION) are extensively used for magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), as well as for magnetic fluid hyperthermia (MFH). We here describe a sequential centrifugation protocol to obtain SPION with well-defined sizes from a polydisperse SPION starting formulation, synthesized using the routinely employed co-precipitation technique. Transmission electron microscopy, dynamic light scattering and nanoparticle tracking analyses show that the SPION fractions obtained upon size-isolation are well-defined and almost monodisperse. MRI, MPI and MFH analyses demonstrate improved imaging and hyperthermia performance for size-isolated SPION as compared to the polydisperse starting mixture, as well as to commercial and clinically used iron oxide nanoparticle formulations, such as Resovist® and Sinerem®. The size-isolation protocol presented here may help to identify SPION with optimal properties for diagnostic, therapeutic and theranostic applications.

Complementary and alternative medicine and musculoskeletal pain in the first year of adjuvant aromatase inhibitor treatment in early breast cancer patients

Background

Patients with breast cancer (BC) show strong interest in complementary and alternative medicine (CAM), particularly for adverse effects of adjuvant endocrine treatment — e.g., with letrozole. Letrozole often induces myalgia/limb pain and arthralgia, with potential noncompliance and treatment termination. This analysis investigated whether CAM before aromatase inhibitor (AI) therapy is associated with pain development and the intensity of AI-induced musculoskeletal syndrome (AIMSS) during the first year of treatment.

Patients and methods

The multicenter phase IV PreFace study evaluated letrozole therapy in postmenopausal, hormone receptor–positive patients with early BC. Patients were asked about CAM use before, 6 months after, and 12 months after treatment started. They recorded pain every month for 1 year in a diary including questions about pain and numeric pain rating scales. Data were analyzed for patients who provided pain information for all time points.

Results

Of 1396 patients included, 901 (64.5%) had used CAM before AI treatment. Throughout the observation period, patients with CAM before AI treatment had higher pain values, for both myalgia/limb pain and arthralgia, than non-users. Pain increased significantly in both groups over time, with the largest increase during the first 6 months. No significant difference of pain increase was noted regarding CAM use.

Conclusions

CAM use does not prevent or improve the development of AIMSS. Pain intensity was generally greater in the CAM group. Therefore, because of the risk of non-compliance and treatment discontinuation due to the development of higher pain levels, special attention must be paid to patient education and aftercare in these patients.

•

Pain levels of myalgia/limb pain and arthralgia increase under letrozole intake.

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Within one year pain levels increase in both, CAM users as well as non-CAM users.

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In CAM users pain levels were higher at all time points than in non-CAM users.

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The greatest increase of pain levels was noted in the first six treatment months.

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CAM does not prevent or improve the development of myalgia/limb pain and arthralgia.

(Hybrid) SPECT and PET Technologies

SPECT and PET are nuclear tomographic imaging modalities that visualize functional information based on the accumulation of radioactive tracer molecules. However, SPECT and PET lack anatomical information, which has motivated their combination with an anatomical imaging modality such as CT or MRI. This chapter begins with an overview over the fundamental physics of SPECT and PET followed by a presentation of the respective detector technologies, including detection requirements, principles and different detector concepts. The reader is subsequently provided with an introduction into hybrid imaging concepts, before a dedicated section presents the challenges that arise when hybridizing SPECT or PET with MRI, namely, mutual distortions of the different electromagnetic fields in MRI on the nuclear imaging system and vice versa. The chapter closes with an overview about current hybrid imaging systems of both clinical and preclinical kind. Finally, future developments in hybrid SPECT and PET technology are discussed.

Algorithms for joint activity-attenuation estimation from positron emission tomography scatter

Background

Attenuation correction in positron emission tomography remains challenging in the absence of measured transmission data. Scattered emission data may contribute missing information, but quantitative scatter-to-attenuation (S2A) reconstruction needs to input the reconstructed activity image. Here, we study S2A reconstruction as a building block for joint estimation of activity and attenuation.

Methods

We study two S2A reconstruction algorithms, maximum-likelihood expectation maximization (MLEM) with one-step-late attenuation (MLEM-OSL) and a maximum-likelihood gradient ascent (MLGA). We study theoretical properties of these algorithms with a focus on convergence and convergence speed and compare convergence speeds and the impact of object size in simulations using different spatial scale factors. Then, we propose joint estimation of activity and attenuation from scattered and nonscattered (true) emission data, combining MLEM-OSL or MLGA with scatter-MLEM as well as trues-MLEM and the maximum-likelihood transmission (MLTR) algorithm.

Results

Shortcomings of MLEM-OSL inhibit convergence to the true solution with high attenuation; these shortcomings are related to the linearization of a nonlinear measurement equation and can be linked to a new numerical criterion allowing geometrical interpretations in terms of low and high attenuation. Comparisons using simulated data confirm that while MLGA converges largely independent of the attenuation scale, MLEM-OSL converges if low-attenuation data dominate, but not with high attenuation. Convergence of MLEM-OSL can be improved by isolating data satisfying the aforementioned low-attenuation criterion. In joint estimation of activity and attenuation, scattered data helps avoid local minima that nonscattered data alone cannot. Combining MLEM-OSL with trues-MLEM may be sufficient for low-attenuation objects, while MLGA, scatter-MLEM, and MLTR may additionally be needed with higher attenuation.

Conclusions

The performance of S2A algorithms depends on spatial scales. MLGA provides lower computational complexity and convergence in more diverse setups than MLEM-OSL. Finally, scattered data may provide additional information to joint estimation of activity and attenuation through S2A reconstruction.