A deep neural network to recover missing data in small animal pet imaging:Comparison between sinogram-and image-domain implementations

Missing areas in PET sinograms and severe image artifacts as a consequence thereof, still gain prominence not only in sparse-ring detector configurations but also in full-ring PET scanners in case of faulty detectors. Empty bins in the projection domain, caused by inter-block gap regions or any failure in the detector blocks may lead to unacceptable image distortions and inaccuracies in quantitative analysis. Deep neural networks have recently attracted enormous attention within the imaging community and are being deployed for various applications, including handling impaired sinograms and removing the streaking artifacts generated by incomplete projection views. Despite the promising results in sparse-view CT reconstruction, the utility of deep-learning-based methods in synthesizing artifact-free PET images in the sparse-crystal setting is poorly explored. Herein, we investigated the feasibility of a modified U-Net to generate artifact-free PET scans in the presence of severe dead regions between adjacent detector blocks on a dedicated high-resolution preclinical PET scanner. The performance of the model was assessed in both projection and image-space. The visual inspection and quantitative analysis seem to indicate that the proposed method is well suited for application on partial-ring PET scanners

Implementation of absolute quantification in small-animal SPECT imaging: Phantom and animal studies

Purpose: Presence of photon attenuation severely challenges quantitative accuracy in single-photon emission computed tomography (SPECT) imaging. Subsequently, various attenuation correction methods have been developed to compensate for this degradation. The present study aims to implement an attenuation correction method and then to evaluate quantification accuracy of attenuation correction in small-animal SPECT imaging. Methods: Images were reconstructed using an iterative reconstruction method based on the maximum-likelihood expectation maximization (MLEM) algorithm including resolution recovery. This was implemented in our designed dedicated small-animal SPECT (HiReSPECT) system. For accurate quantification, the voxel values were converted to activity concentration via a calculated calibration factor. An attenuation correction algorithm was developed based on the first-order Chang’s method. Both phantom study and experimental measurements with four rats were used in order to validate the proposed method. Results: The phantom experiments showed that the error of �15.5% in the estimation of activity concentration in a uniform region was reduced to +5.1% when attenuation correction was applied. For in vivo studies, the average quantitative error of �22.8 � 6.3% (ranging from �31.2% to �14.8%) in the uncorrected images was reduced to +3.5 � 6.7% (ranging from �6.7 to +9.8%) after applying attenuation correction. Conclusion: The results indicate that the proposed attenuation correction algorithm based on the first-order Chang’s method, as implemented in our dedicated small-animal SPECT system, significantly improves accuracy of the quantitative analysis as well as the absolute quantification

Synergistic impact of motion and acquisition/reconstruction parameters on F-18-FDG PET radiomic features in non-small cell lung cancer:Phantom and clinical studies

Objectives: This study is aimed at examining the synergistic impact of motion and acquisition/reconstruction parameters on 18 F-FDG PET image radiomic features in non-small cell lung cancer (NSCLC) patients, and investigating the robustness of features performance in differentiating NSCLC histopathology subtypes. Methods: An in-house developed thoracic phantom incorporating lesions with different sizes was used with different reconstruction settings, including various reconstruction algorithms, number of subsets and iterations, full-width at half-maximum of post-reconstruction smoothing filter and acquisition parameters, including injected activity and test-retest with and without motion simulation. To simulate motion, a special motor was manufactured to simulate respiratory motion based on a normal patient in two directions. The lesions were delineated semi-automatically to extract 174 radiomic features. All radiomic features were categorized according to the coefficient of variation (COV) to select robust features. A cohort consisting of 40 NSCLC patients with adenocarcinoma (n = 20) and squamous cell carcinoma (n = 20) was retrospectively analyzed. Statistical analysis was performed to discriminate robust features in differentiating histopathology subtypes of NSCLC lesions. Results: Overall, 29% of radiomic features showed a COV ≤5% against motion. Forty-five percent and 76% of the features showed a COV ≤ 5% against the test-retest with and without motion in large lesions, respectively. Thirty-three percent and 45% of the features showed a COV ≤ 5% against different reconstruction parameters with and without motion, respectively. For NSCLC histopathological subtype differentiation, statistical analysis showed that 31 features were significant (p-value &lt; 0.05). Two out of the 31 significant features, namely, the joint entropy of GLCM (AUC = 0.71, COV = 0.019) and median absolute deviation of intensity histogram (AUC = 0.7, COV = 0.046), were robust against the motion (same reconstruction setting). Conclusions: Motion, acquisition, and reconstruction parameters significantly impact radiomic features, just as their synergies. Radiomic features with high predictive performance (statistically significant) in differentiating histopathological subtype of NSCLC may be eliminated due to non-reproducibility.</p

Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytren’s Disease

Dupuytren´s disease, a fibromatosis of the connective tissue in the palm, is a common complex disease with a strong genetic component. Up to date nine genetic loci have been found to be associated with the disease. Six of these loci contain genes that code for Wnt signalling proteins. In spite of this striking first insight into the genetic factors in Dupuytren´s disease, much of the inherited risk in Dupuytren´s disease still needs to be discovered. The already identified loci jointly explain ~1% of the heritability in this disease. To further elucidate the genetic basis of Dupuytren´s disease, we performed a genome-wide meta-analysis combining three genome-wide association study (GWAS) data sets, comprising 1,580 cases and 4,480 controls. We corroborated all nine previously identified loci, six of these with genome-wide significance (p-value < 5x10-8). In addition, we identified 14 new suggestive loci (p-value < 10−5). Intriguingly, several of these new loci contain genes associated with Wnt signalling and therefore represent excellent candidates for replication. Next, we compared whole-transcriptome data between patient- and control-derived tissue samples and found the Wnt/β-catenin pathway to be the top deregulated pathway in patient samples. We then conducted network and pathway analyses in order to identify protein networks that are enriched for genes highlighted in the GWAS meta-analysis and expression data sets. We found further evidence that the Wnt signalling pathways in conjunction with other pathways may play a critical role in Dupuytren´s disease

Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy

Background The World Health Organization (WHO) Surgical Safety Checklist has fostered safe practice for 10 years, yet its place in emergency surgery has not been assessed on a global scale. The aim of this study was to evaluate reported checklist use in emergency settings and examine the relationship with perioperative mortality in patients who had emergency laparotomy. Methods In two multinational cohort studies, adults undergoing emergency laparotomy were compared with those having elective gastrointestinal surgery. Relationships between reported checklist use and mortality were determined using multivariable logistic regression and bootstrapped simulation. Results Of 12 296 patients included from 76 countries, 4843 underwent emergency laparotomy. After adjusting for patient and disease factors, checklist use before emergency laparotomy was more common in countries with a high Human Development Index (HDI) (2455 of 2741, 89.6 per cent) compared with that in countries with a middle (753 of 1242, 60.6 per cent; odds ratio (OR) 0.17, 95 per cent c.i. 0.14 to 0.21, P <0001) or low (363 of 860, 422 per cent; OR 008, 007 to 010, P <0.001) HDI. Checklist use was less common in elective surgery than for emergency laparotomy in high-HDI countries (risk difference -94 (95 per cent c.i. -11.9 to -6.9) per cent; P <0001), but the relationship was reversed in low-HDI countries (+121 (+7.0 to +173) per cent; P <0001). In multivariable models, checklist use was associated with a lower 30-day perioperative mortality (OR 0.60, 0.50 to 073; P <0.001). The greatest absolute benefit was seen for emergency surgery in low- and middle-HDI countries. Conclusion Checklist use in emergency laparotomy was associated with a significantly lower perioperative mortality rate. Checklist use in low-HDI countries was half that in high-HDI countries.Peer reviewe

Global variation in anastomosis and end colostomy formation following left-sided colorectal resection

Background End colostomy rates following colorectal resection vary across institutions in high-income settings, being influenced by patient, disease, surgeon and system factors. This study aimed to assess global variation in end colostomy rates after left-sided colorectal resection. Methods This study comprised an analysis of GlobalSurg-1 and -2 international, prospective, observational cohort studies (2014, 2016), including consecutive adult patients undergoing elective or emergency left-sided colorectal resection within discrete 2-week windows. Countries were grouped into high-, middle- and low-income tertiles according to the United Nations Human Development Index (HDI). Factors associated with colostomy formation versus primary anastomosis were explored using a multilevel, multivariable logistic regression model. Results In total, 1635 patients from 242 hospitals in 57 countries undergoing left-sided colorectal resection were included: 113 (6·9 per cent) from low-HDI, 254 (15·5 per cent) from middle-HDI and 1268 (77·6 per cent) from high-HDI countries. There was a higher proportion of patients with perforated disease (57·5, 40·9 and 35·4 per cent; P < 0·001) and subsequent use of end colostomy (52·2, 24·8 and 18·9 per cent; P < 0·001) in low- compared with middle- and high-HDI settings. The association with colostomy use in low-HDI settings persisted (odds ratio (OR) 3·20, 95 per cent c.i. 1·35 to 7·57; P = 0·008) after risk adjustment for malignant disease (OR 2·34, 1·65 to 3·32; P < 0·001), emergency surgery (OR 4·08, 2·73 to 6·10; P < 0·001), time to operation at least 48 h (OR 1·99, 1·28 to 3·09; P = 0·002) and disease perforation (OR 4·00, 2·81 to 5·69; P < 0·001). Conclusion Global differences existed in the proportion of patients receiving end stomas after left-sided colorectal resection based on income, which went beyond case mix alone

A Novel Dual Energy CT-Based Attenuation Correction Method in PET/CT Systems: A Phantom Study A Novel DECT Attenuation Correction Method in PET/CT Teimourian et al

ABSTRACT In present PET/CT scanners, PET attenuation correction is performed by relying on the information given by CT scan. In the CT-based attenuation correction methods, dual-energy technique (DECT) is the most accurate approach, which has been limited due to the increasing patient dose. In this feasibility study, we have introduced a new method that can implement dual-energy technique with only a single energy CT scan. The implementation was done by CT scans of RANDO phantom at tube voltages of 80 kV P and 140 kV P . The acquired data was used to obtain conversion curves (which scale CT numbers at different kV P to each other), in three regions including lung tissue (HU&lt;-100), soft tissue (-100&lt;HU&lt;200) and bone tissue (HU&gt;200) for the combination of 80 kV P /140 kV P . Therefore, with having the CT image in one energy, we generate the CT image at the second energy (from now we call it virtual dual-energy technique) using these kV P conversion curves. The attenuation map at 511 keV was generated using bilinear (the most commonly used method in commercially available PET/CT scanners), real dual-energy and virtual dual-energy technique in a polyethylene phantom. In the phantom study, the created attenuation map using mentioned methods are compared to the theoretical values calculated using XCOM cross section library. The results in the phantom data show 10.1 %, 4.2 % and 4.3 % errors for bilinear, dual-energy and virtual dual-energy techniques respectively. Further evaluation using a larger patient data is underway to evaluate the potential of the technique in a clinical setting

Advances in Preclinical PET Instrumentation

In the light of ever-increasing demands for PET scanner with better resolvability, higher sensitivity and wide accessibility for noninvasive screening of small structures and physiological processes in laboratory rodents, several dedicated PET scanners were developed and evaluated. Understanding conceptual design constraints pros and cons of different configurations and impact of the major components will be helpful to further establish the crucial role of these miniaturized systems in a broad spectrum of modern research. Hence, a comprehensive review of preclinical PET scanners developed till early 2020 with particular emphasis on innovations in instrumentation and geometrical designs is provided

Towards quantitative small-animal imaging on hybrid PET/CT and PET/MRI systems

Over the past two decades, innovations in small-animal positron emission tomography (PET) have reached an impressive level, which has brought countless opportunities to explore the major puzzles in biomedical research. It is a given that pairing information coming from different imaging modalities renders unprecedented knowledge and provides a great insight into various facets of biological systems, such as anatomy, function, physiology, and metabolism in animal models of human diseases, which are difficult to be beaten by standalone PET scanners. The development of bimodal and tri-modal imaging platforms with advanced software solutions dedicated for quantitative studies in small-animals has spurred academic and industrial interest. However, it is undisputed that the potential success of these scanners in filling the translational gap between human and animal findings, hinges to a great extent upon optimization and standardization of relevant parameters and acquisition protocols, which is often overlooked