Surfactant-induced gradients in the three-dimensional Belousov-Zhabotinsky reaction

Scroll waves are prominent patterns formed in three-dimensional excitable media, and they are frequently considered highly relevant for some types of cardiac arrhythmias. Experimentally, scroll wave dynamics is often studied by optical tomography in the Belousov-Zhabotinsky reaction, which produces CO2 as an undesired product. Addition of small concentrations of a surfactant to the reaction medium is a popular method to suppress or retard CO2 bubble formation. We show that in closed reactors even these low concentrations of surfactants are sufficient to generate vertical gradients of excitability which are due to gradients in CO2 concentration. In reactors open to the atmosphere such gradients can be avoided. The gradients induce a twist on vertically oriented scroll waves, while a twist is absent in scroll waves in a gradient-free medium. The effects of the CO2 gradients are reproduced by a numerical study, where we extend the Oregonator model to account for the production of CO2 and for its advection against the direction of gravity. The numerical simulations confirm the role of solubilized CO2 as the source of the vertical gradient of excitability in reactors closed to the atmosphere.Peer ReviewedPostprint (published version

Optimization of SPECT/CT imaging protocols for quantitative and qualitative 99mTc SPECT

Background!#!The introduction of hybrid SPECT/CT devices enables quantitative imaging in SPECT, providing a methodological setup for quantitation using SPECT tracers comparable to PET/CT. We evaluated a specific quantitative reconstruction algorithm for SPECT data using a !##!Results!#!The reconstructed activity concentration (AC!##!Conclusion!#!Quantitative SPECT imaging is feasible with the used reconstruction algorithm and hybrid SPECT/CT, and its consistent implementation in diagnostics may provide perspectives for quantification in routine clinical practice (e.g., assessment of bone metabolism). When combining quantitative analysis and diagnostic imaging, we recommend using two different reconstruction protocols with task-specific optimized setups (quantitative vs. qualitative reconstruction). Furthermore, individual scatter correction significantly improves both quantitative and qualitative results

Analysis of Bone Scans in Various Tumor Entities Using a Deep-Learning-Based Artificial Neural Network Algorithm—Evaluation of Diagnostic Performance

The bone scan index (BSI), initially introduced for metastatic prostate cancer, quantifies the osseous tumor load from planar bone scans. Following the basic idea of radiomics, this method incorporates specific deep-learning techniques (artificial neural network) in its development to provide automatic calculation, feature extraction, and diagnostic support. As its performance in tumor entities, not including prostate cancer, remains unclear, our aim was to obtain more data about this aspect. The results of BSI evaluation of bone scans from 951 consecutive patients with different tumors were retrospectively compared to clinical reports (bone metastases, yes/no). Statistical analysis included entity-specific receiver operating characteristics to determine optimized BSI cut-off values. In addition to prostate cancer (cut-off = 0.27%, sensitivity (SN) = 87%, specificity (SP) = 99%), the algorithm used provided comparable results for breast cancer (cut-off 0.18%, SN = 83%, SP = 87%) and colorectal cancer (cut-off = 0.10%, SN = 100%, SP = 90%). Worse performance was observed for lung cancer (cut-off = 0.06%, SN = 63%, SP = 70%) and renal cell carcinoma (cut-off = 0.30%, SN = 75%, SP = 84%). The algorithm did not perform satisfactorily in melanoma (SN = 60%). For most entities, a high negative predictive value (NPV ≥ 87.5%, melanoma 80%) was determined, whereas positive predictive value (PPV) was clinically not applicable. Automatically determined BSI showed good sensitivity and specificity in prostate cancer and various other entities. Particularly, the high NPV encourages applying BSI as a tool for computer-aided diagnostic in various tumor entities

Improvement of image quality and dose management in CT fluoroscopy by iterative 3D image reconstruction

The objective of this study was to assess the influence of an iterative CT reconstruction algorithm (IA), newly available for CT-fluoroscopy (CTF), on image noise, readers' confidence and effective dose compared to filtered back projection (FBP). Data from 165 patients (FBP/IA = 82/74) with CTF in the thorax, abdomen and pelvis were included. Noise was analysed in a large-diameter vessel. The impact of reconstruction and variables (e.g. X-ray tube current I) influencing noise and effective dose were analysed by ANOVA and a pairwise t-test with Bonferroni-Holm correction. Noise and readers' confidence were evaluated by three readers. Noise was significantly influenced by reconstruction, I, body region and circumference (all p ae currency 0.0002). IA reduced the noise significantly compared to FBP (p = 0.02). The effect varied for body regions and circumferences (p aecurrency 0.001). The effective dose was influenced by the reconstruction, body region, interventional procedure and I (all p ae currency 0.02). The inter-rater reliability for noise and readers' confidence was good (W ae yen 0.75, p 0.03). Generally, IA yielded a significant reduction of the median effective dose. The CTF reconstruction by IA showed a significant reduction in noise and effective dose while readers' confidence increased. aEuro cent CTF is performed for image guidance in interventional radiology. aEuro cent Patient exposure was estimated from DLP documented by the CT. aEuro cent Iterative CT reconstruction is appropriate to reduce image noise in CTF. aEuro cent Using iterative CT reconstruction, the effective dose was significantly reduced in abdominal interventions

Iterative CT reconstruction in abdominal low-dose CT used for hybrid SPECT-CT applications: effect on image quality, image noise, detectability, and reader's confidence

Background Iterative computed tomography (CT) image reconstruction shows high potential for the preservation of image quality in diagnostic CT while reducing patients' exposure;it has become available for low-dose CT (LD-CT) in high-end hybrid imaging systems (e.g. single-photon emission computed tomography [SPECT]-CT). Purpose To examine the effect of an iterative CT reconstruction algorithm on image quality, image noise, detectability, and the reader's confidence for LD-CT data by a subjective assessment. Material and Methods The LD-CT data were validated for 40 patients examined by an abdominal hybrid SPECT-CT (U = 120 kV, I = 40 mA, pitch = 1.375). LD-CT was reconstructed using either filtered back projection (FBP) or an iterative image reconstruction algorithm (Adaptive Statistical Iterative Reconstruction [ASIR](R)) with different parameters (ASIR levels 50% and 100%). The data were validated by two independent blinded readers using a scoring system for image quality, image noise, detectability, and reader confidence, for a predefined set of 16 anatomic substructures. Results The image quality was significantly improved by iterative reconstruction of the LD-CT data compared with FBP (P <= 0.0001). While detectability increased in only 2/16 structures (P <= 0.03), the reader's confidence increased significantly due to iterative reconstruction (P <= 0.002). Meanwhile, at the ASIR level of 100%, the detectability in bone structure was highly reduced (P = 0.003). Conclusion An ASIR level of 50% represents a good compromise in abdominal LD-CT image reconstruction. The specific ASIR level improved image quality (reduced image noise) and reader confidence, while preserving detectability of bone structure

Quantitative imaging of bone remodeling in patients with a unicompartmental joint unloading knee implant (ATLAS Knee System)—effect of metal artifacts on a SPECT-CT-based quantification

Background!#!SPECT-CT using radiolabeled phosphonates is considered a standard for assessing bone metabolism (e.g., in patients with osteoarthritis of knee joints). However, SPECT can be influenced by metal artifacts in CT caused by endoprostheses affecting attenuation correction. The current study examined the effects of metal artifacts in CT of a specific endoprosthesis design on quantitative hybrid SPECT-CT imaging. The implant was positioned inside a phantom homogenously filled with activity (955 MBq !##!Results!#!Significant effects caused by CT metal artifacts on attenuation-corrected SPECT were observed for the different slice positions, reconstructed slice thicknesses of CT data, and pitch and CT-reconstruction kernels used (all, p &amp;lt; 0.0001). Based on the optimization, a set of three protocols was identified minimizing the effect of CT metal artifacts on SPECT data. Regarding the reference region, the activity concentration in the anatomically correlated volume was underestimated by 8.9-10.1%. A slight inhomogeneity of the reconstructed activity concentration was detected inside the regions with a median up to 0.81% (p &amp;lt; 0.0001). Using an X-ray tube current of 40 mA showed the best result, balancing quantification and CT exposure.!##!Conclusion!#!The results of this study demonstrate the need for the evaluation of SPECT-CT protocols in prosthesis imaging. Phantom experiments demonstrated the possibility for quantitative SPECT-CT of bone turnover in a specific prosthesis design. Meanwhile, a systematic bias caused by metal implants on quantitative SPECT data has to be considered

Software-assisted dosimetry in peptide receptor radionuclide therapy with ¹⁷⁷Lutetium-DOTATATE for various imaging scenarios

<div><p>In peptide receptor radionuclide therapy (PRRT) of patients with neuroendocrine neoplasias (NENs), intratherapeutic dosimetry is mandatory for organs at risk (e.g. kidneys) and tumours. We evaluated commercial dosimetry software (Dosimetry Toolkit) using varying imaging scenarios, based on planar and/or tomographic data, regarding the differences in calculated organ/tumour doses and the use for clinical routines. A total of 16 consecutive patients with NENs treated by PRRT with ¹⁷⁷Lu-DOTATATE were retrospectively analysed. Single-photon emission computed tomography (SPECT)/low-dose computed tomography (CT) of the thorax and abdomen and whole body (WB) scintigraphy were acquired up to 7 days p.i. (at a maximum of five imaging time points). Different dosimetric scenarios were evaluated: (1) a multi-SPECT-CT scenario using SPECT/CT only; (2) a planar scenario using WB scintigraphy only; and (3) a hybrid scenario using WB scintigraphy in combination with a single SPECT/low-dose CT. Absorbed doses for the kidneys, liver, spleen, lungs, bladder wall and tumours were calculated and compared for the three different scenarios. The mean absorbed dose for the kidneys estimated by the multi-SPECT-CT, the planar and the hybrid scenario was 0.5 ± 0.2 Sv GBq^-1, 0.8 ± 0.4 Sv GBq^-1 and 0.6 ± 0.3 Sv GBq^-1, respectively. The absorbed dose for the residual organs was estimated higher by the planar scenario compared to the multi-SPECT-CT or hybrid scenario. The mean absorbed tumour doses were 2.6 ± 1.5 Gy GBq^-1 for the multi-SPECT-CT, 3.1 ± 2.2 Gy GBq^-1 for the hybrid scenario and 5.3 ± 6.3 Gy GBq^-1 for the planar scenario. SPECT-based dosimetry methods determined significantly lower kidney doses than the WB scintigraphy-based method. Dosimetry based completely on SPECT data is time-consuming and tedious. Approaches combining SPECT/CT and WB scintigraphy have the potential to ensure compromise between accuracy and user-friendliness.</p></div

Patient whole body (WB) weight and determined organ masses.

<p>The individual masses estimated with low-dose CT volumetry were used for weight adjustments in OLINDA/EXM software.</p

Residence times for the first therapy cycle (n = 16 patients) estimated by DTK using different imaging scenarios.

<p>Residence times for the first therapy cycle (n = 16 patients) estimated by DTK using different imaging scenarios.</p

A representative final report of the Dosimetry Toolkit.

<p>(A) Illustration of the serial images of a patient with all regions of interest 4 h, 24 h, 48 h, 72 h and 168h p.i. (B) Normalised time-activity curves for all regions of interest. (C) Calculated residence times of all regions of interest.</p