The anti-hyperplasia effect of polysaccharide from Prunella vulgaris L. on mammary gland hyperplasia in rats through regulation of the AKT-FOXO3a signaling pathway and intestinal flora.

BACKGROUND: Prunella vulgaris L., a medicinal and edible homologous plant, is often used to treat conditions such as breast hyperplasia, thyroid enlargement and lymphatic tuberculosis. Research has demonstrated that it is particularly effective in the treatment of mammary gland hyperplasia (MGH). However, the material basis and mechanism of its efficacy are still unclear. RESULTS: Our results showed that in rats with MGH, polysaccharide from Prunella vulgaris L. (PVP) led to a reduction in the levels of estradiol, prolactin and malondialdehyde, while simultaneously increasing the concentrations of progesterone (P), superoxide dismutase (SOD), manganese superoxide dismutase (MnSOD) and catalase (CAT) in the serum. In addition, results obtained from 16S rRNA sequencing demonstrated that PVP had the capacity to increase the richness and diversity of the intestinal microbiota in MGH rats, as well as modify the structure of the microbiota. Correlation analysis revealed that the levels of P, SOD, MnSOD and CAT were positively associated with Allobaculum, Romboutsia, Faecalibaculum and Clostridium, while negatively correlated with Turicibacter. CONCLUSIONS: The mechanism of PVP in treating MGH might be through inhibiting the phosphorylation of the AKT-FOXO3a signaling pathway and then activating the expression of downstream antioxidant enzymes, such as MnSOD and CAT. At the same time, PVP could restore intestinal flora homeostasis in rats with MGH by regulating the flora changes of Allobaculum, Romboutsia, Clostridium and Faecalibaculum, thereby reducing oxidative stress in rats with MGH. © 2024 Society of Chemical Industry.

Observer studies of image quality of denoising reduced-count cardiac single photon emission computed tomography myocardial perfusion imaging by three-dimensional Gaussian post-reconstruction filtering and deep learning.

BACKGROUND: The aim of this research was to asses perfusion-defect detection-accuracy by human observers as a function of reduced-counts for 3D Gaussian post-reconstruction filtering vs deep learning (DL) denoising to determine if there was improved performance with DL. METHODS: SPECT projection data of 156 normally interpreted patients were used for these studies. Half were altered to include hybrid perfusion defects with defect presence and location known. Ordered-subset expectation-maximization (OSEM) reconstruction was employed with the optional correction of attenuation (AC) and scatter (SC) in addition to distance-dependent resolution (RC). Count levels varied from full-counts (100%) to 6.25% of full-counts. The denoising strategies were previously optimized for defect detection using total perfusion deficit (TPD). Four medical physicist (PhD) and six physician (MD) observers rated the slices using a graphical user interface. Observer ratings were analyzed using the LABMRMC multi-reader, multi-case receiver-operating-characteristic (ROC) software to calculate and compare statistically the area-under-the-ROC-curves (AUCs). RESULTS: For the same count-level no statistically significant increase in AUCs for DL over Gaussian denoising was determined when counts were reduced to either the 25% or 12.5% of full-counts. The average AUC for full-count OSEM with solely RC and Gaussian filtering was lower than for the strategies with AC and SC, except for a reduction to 6.25% of full-counts, thus verifying the utility of employing AC and SC with RC. CONCLUSION: We did not find any indication that at the dose levels investigated and with the DL network employed, that DL denoising was superior in AUC to optimized 3D post-reconstruction Gaussian filtering.

Improving detection accuracy of perfusion defect in standard dose SPECT-myocardial perfusion imaging by deep-learning denoising.

BACKGROUND: We previously developed a deep-learning (DL) network for image denoising in SPECT-myocardial perfusion imaging (MPI). Here we investigate whether this DL network can be utilized for improving detection of perfusion defects in standard-dose clinical acquisitions. METHODS: To quantify perfusion-defect detection accuracy, we conducted a receiver-operating characteristic (ROC) analysis on reconstructed images with and without processing by the DL network using a set of clinical SPECT-MPI data from 190 subjects. For perfusion-defect detection hybrid studies were used as ground truth, which were created from clinically normal studies with simulated realistic lesions inserted. We considered ordered-subset expectation-maximization (OSEM) reconstruction with corrections for attenuation, resolution, and scatter and with 3D Gaussian post-filtering. Total perfusion deficit (TPD) scores, computed by Quantitative Perfusion SPECT (QPS) software, were used to evaluate the reconstructed images. RESULTS: Compared to reconstruction with optimal Gaussian post-filtering (sigma = 1.2 voxels), further DL denoising increased the area under the ROC curve (AUC) from 0.80 to 0.88 (P-value < 10-4). For reconstruction with less Gaussian post-filtering (sigma = 0.8 voxels), thus better spatial resolution, DL denoising increased the AUC value from 0.78 to 0.86 (P-value < 10-4) and achieved better spatial resolution in reconstruction. CONCLUSIONS: DL denoising can effectively improve the detection of abnormal defects in standard-dose SPECT-MPI images over conventional reconstruction.

Development and evaluation of a high performance T1-weighted brain template for use in studies on older adults.

Τhe accuracy of template-based neuroimaging investigations depends on the template's image quality and representativeness of the individuals under study. Yet a thorough, quantitative investigation of how available standardized and study-specific T1-weighted templates perform in studies on older adults has not been conducted. The purpose of this work was to construct a high-quality standardized T1-weighted template specifically designed for the older adult brain, and systematically compare the new template to several other standardized and study-specific templates in terms of image quality, performance in spatial normalization of older adult data and detection of small inter-group morphometric differences, and representativeness of the older adult brain. The new template was constructed with state-of-the-art spatial normalization of high-quality data from 222 older adults. It was shown that the new template (a) exhibited high image sharpness, (b) provided higher inter-subject spatial normalization accuracy and (c) allowed detection of smaller inter-group morphometric differences compared to other standardized templates, (d) had similar performance to that of study-specific templates constructed with the same methodology, and (e) was highly representative of the older adult brain.

Retrospective fractional dose reduction in Tc-99m cardiac perfusion SPECT/CT patients: A human and model observer study.

BACKGROUND: In the ongoing efforts to reduce cardiac perfusion dose (injected radioactivity) for conventional SPECT/CT systems, we performed a human observer study to confirm our clinical model observer findings that iterative reconstruction employing OSEM (ordered-subset expectation-maximization) at 25% of the full dose (quarter-dose) has a similar performance for detection of hybrid cardiac perfusion defects as FBP at full dose. METHODS: One hundred and sixty-six patients, who underwent routine rest-stress Tc-99m sestamibi cardiac perfusion SPECT/CT imaging and clinically read as normally perfused, were included in the study. Ground truth was established by the normal read and the insertion of hybrid defects. In addition to the reconstruction of the 25% of full-dose data using OSEM with attenuation (AC), scatter (SC), and spatial resolution correction (RC), FBP and OSEM (with AC, SC, and RC) both at full dose (100%) were done. Both human observer and clinical model observer confidence scores were obtained to generate receiver operating characteristics (ROC) curves in a task-based image quality assessment. RESULTS: Average human observer AUC (area under the ROC curve) values of 0.725, 0.876, and 0.890 were obtained for FBP at full dose, OSEM at 25% of full dose, and OSEM at full dose, respectively. Both OSEM strategies were significantly better than FBP with P values of 0.003 and 0.01 respectively, while no significant difference was recorded between OSEM methods (P = 0.48). The clinical model observer results were 0.791, 0.822, and 0.879, respectively, for the same patient cases and processing strategies used in the human observer study. CONCLUSIONS: Cardiac perfusion SPECT/CT using OSEM reconstruction at 25% of full dose has AUCs larger than FBP and closer to those of full-dose OSEM when read by human observers, potentially replacing the higher dose studies during clinical reading.

Evaluation of the effect of reducing administered activity on assessment of function in cardiac gated SPECT.

BACKGROUND: We previously optimized several reconstruction strategies in SPECT myocardial perfusion imaging (MPI) with low dose for perfusion-defect detection. Here we investigate whether reducing the administered activity can also maintain the diagnostic accuracy in evaluating cardiac function. METHODS: We quantified the myocardial motion in cardiac-gated stress 99m-Tc-sestamibi SPECT studies from 163 subjects acquired with full dose (29.8 ± 3.6 mCi), and evaluated the agreement of the obtained motion/thickening and ejection fraction (EF) measures at various reduced dose levels (uniform reduction or personalized dose) with that at full dose. We also quantified the detectability of abnormal motion via a receiver-operating characteristics (ROC) study. For reconstruction we considered both filtered backprojection (FBP) without correction for degradations, and iterative ordered-subsets expectation-maximization (OS-EM) with resolution, attenuation and scatter corrections. RESULTS: With dose level lowered to 25% of full dose, the obtained results on motion/thickening, EF and abnormal motion detection were statistically comparable to full dose in both reconstruction strategies, with Pearson's r > 0.9 for global motion measures between low dose and full dose. CONCLUSIONS: The administered activity could be reduced to 25% of full dose without degrading the function assessment performance. Low dose reconstruction optimized for perfusion-defect detection can be reasonable for function assessment in gated SPECT.

Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR). We demonstrated an approach to visually convey the reasoning behind a patient's risk to provide insight to clinicians beyond that of a "black box." METHODS: We trained multiple models using 122 potential clinical predictors (features) for 8321 patients, including 551 cases of subsequent cardiac death. Accuracy was measured by area under the ROC curve (AUC), computed within a cross-validation framework. We developed a method to display the model's rationale to facilitate clinical interpretation. RESULTS: The baseline LR (AUC = 0.76; 14 features) was outperformed by all other methods. A least absolute shrinkage and selection operator (LASSO) model (AUC = 0.77; p = .045; 6 features) required the fewest features. A support vector machine (SVM) model (AUC = 0.83; p < .0001; 49 features) provided the highest accuracy. CONCLUSIONS: LASSO outperformed LR in both accuracy and simplicity (number of features), with SVM yielding best AUC for prediction of cardiac death in patients undergoing MPS. Combined with presenting the reasoning behind the risk scores, our results suggest that ML can be more effective than LR for this application.

Improving perfusion defect detection with respiratory motion correction in cardiac SPECT at standard and reduced doses.

BACKGROUND: In cardiac SPECT perfusion imaging, respiratory motion can cause non-uniform blurring in the reconstructed myocardium. We investigate the potential benefit of respiratory correction with respiratory-binned acquisitions, both at standard dose and at reduced dose, for defect detection and for left ventricular (LV) wall resolution. METHODS: We applied two reconstruction methods for respiratory motion correction: post-reconstruction motion correction (PMC) and motion-compensated reconstruction (MCR), and compared with reconstruction without motion correction (Non-MC). We quantified the presence of perfusion defects in reconstructed images by using the total perfusion deficit (TPD) scores and conducted receiver-operating-characteristic (ROC) studies using TPD. We quantified the LV spatial resolution by using the FWHM of its cross-sectional intensity profile. RESULTS: The values in the area-under-the-ROC-curve (AUC) achieved by MCR, PMC, and Non-MC at standard dose were 0.835, 0.830, and 0.798, respectively. Similar AUC improvements were also obtained by MCR and PMC over Non-MC at 50%, 25%, and 12.5% of full dose. Improvements in LV resolution were also observed with motion correction. CONCLUSIONS: Respiratory-binned acquisitions can improve perfusion-defect detection accuracy over traditional reconstruction both at standard dose and at reduced dose. Motion correction may contribute to achieving further dose reduction while maintaining the diagnostic accuracy of traditional acquisitions.

Investigation of dose reduction in cardiac perfusion SPECT via optimization and choice of the image reconstruction strategy.

BACKGROUND: We investigated the extent to which the administered dose (activity) level can be reduced without sacrificing diagnostic accuracy for three reconstruction strategies for SPECT-myocardial perfusion imaging (MPI). METHODS: We optimized the parameters of the three reconstruction strategies for perfusion-defect detection over a range of simulated administered dose levels using a set of hybrid studies (derived from 190 subjects) consisting of clinical SPECT-MPI data modified to contain realistic simulated lesions. The optimized strategies we considered are filtered backprojection (FBP) with no correction for degradations, ordered-subsets expectation-maximization (OS-EM) with attenuation correction (AC), scatter correction (SC), and resolution correction (RC), and OS-EM with scatter and resolution correction only. Each study was evaluated using a total perfusion deficit (TPD) score computed by the Quantitative Perfusion SPECT (QPS) software package. We conducted a receiver operating characteristics (ROC) study based on the TPD scores for each dose level and reconstruction strategy. RESULTS: For FBP, the achieved optimum values of the area under the ROC curve (AUC) at 100%, 50%, 25%, and 12.5% of standard dose were 0.75, 0.74, 0.72, and 0.70, respectively, compared to 0.81, 0.79, 0.76, and 0.74 for OS-EM with AC-SC-RC and 0.78, 0.77, 0.74, 0.72 for OS-EM with SC-RC. CONCLUSIONS: Our results suggest that studies reconstructed by OS-EM with AC-SC-RC could possibly be reduced, on average, to 25% of the originally administered dose without causing diagnostic accuracy (AUC) to decrease below that of FBP.

A context-sensitive deep learning approach for microcalcification detection in mammograms.

A challenging issue in computerized detection of clustered microcalcifications (MCs) is the frequent occurrence of false positives (FPs) caused by local image patterns that resemble MCs. We develop a context-sensitive deep neural network (DNN), aimed to take into account both the local image features of an MC and its surrounding tissue background, for MC detection. The DNN classifier is trained to automatically extract the relevant image features of an MC as well as its image context. The proposed approach was evaluated on a set of 292 mammograms using free-response receiver operating characteristic (FROC) analysis on the accuracy both in detecting individual MCs and in detecting MC clusters. The results demonstrate that the proposed approach could achieve significantly higher FROC curves when compared to two MC-based detectors. It indicates that incorporating image context information in MC detection can be beneficial for reducing the FPs in detections.

[Microsurgical subinguinal varicocelectomy with delivery of the testis and ligation of gubernacular veins: Evaluation of clinical effects].

OBJECTIVE: To compare the clinical effects and postoperative complications of microsurgical subinguinal varicocelectomy (MSV) with or without delivery of the testis and ligation of gubernacular veins in the treatment of varicocele. METHODS: We retrospectively analyzed the clinical data about 163 varicocele patients treated by MSV, 40 with (group A) and the other 123 without delivery of the testis and ligation of gubernacular veins (group B). We compared the operation time, postoperative complications, rate of recurrence, and semen parameters before and at 3 months after surgery between the two groups of patients. RESULTS: The operation time was significantly longer in group A than in B (ï¼»81.1 ± 20.0ï¼½ vs ï¼»62.3 ± 9.6ï¼½ min, P = 0.041). Sperm concentration, total sperm count per ejaculate, sperm viability, and the percentage of progressively motile sperm were significantly improved in both groups at 3 months after MSV as compared with the baseline (P < 0.05). There were no statistically significant differences in the above semen parameters between the two groups of patients with grade Ⅲ varicocele before and after surgery (P < 0.05). Scrotal edema developed in 5 cases in group A and wound infection in 2 cases in group B after MSV, but no postoperative testicular atrophy or recurrence was observed in either of the two groups. CONCLUSIONS: MSV with delivery of the testis and ligation of gubernacular veins showed no advantages over that without in reducing varicocele recurrence and improving semen parameters, but rather involved longer operation time and a higher incidence rate of postoperative complications.

Creation of Bt rice expressing a fusion protein of Cry1Ac and Cry1I-like using a green tissue-specific promoter.

The insecticidal genes from Bacillus thuringiensis Berliner (Bt) have long been successfully used for development of insect-resistant rice. However, commercial planting of Bt rice has been delayed by the concern over food safety, although no scientific evidence is ever found to justify the concern. To address this safety concern, we developed a transgenic insect-resistant rice line using a green tissue promoter to minimize the Bt protein expression in the rice seeds. The Bt protein expressed in the rice was a fusion protein of two different Bt toxins, Cry1Ac and Cry1I-like protein. The fusion of the two toxins may be helpful to delay the development of insect resistance to Bt rice. Laboratory and field bioassays demonstrated that the transgenic rice plants created by this study were highly active against the rice leaf folder Cnaphalocrocis medinalis (Guenée) and the striped stem borer Chilo suppressalis (Walker). Western analysis indicated that the fusion protein was specifically expressed in green tissues but not in seeds. Therefore, the transgenic rice created in this study should be useful to mitigate the food safety concern and to delay the development of insect resistance.

Respiratory signal estimation for cardiac perfusion SPECT using deep learning.

BACKGROUND: Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a respiratory signal describing the heart displacements during breathing. However, using external tracking devices to estimate respiratory signals can add cost and operational complications in a clinical setting. PURPOSE: We aim to develop a deep learning (DL) approach that uses only SPECT projection data for respiratory signal estimation. METHODS: A modified U-Net was implemented that takes temporally finely sampled SPECT sub-projection data (100 ms) as input. These sub-projections are obtained by reframing the 20-s list-mode data, resulting in 200 sub-projections, at each projection angle for each SPECT camera head. The network outputs a 200-time-point motion signal for each projection angle, which was later aggregated over all angles to give a full respiratory signal. The target signal for DL model training was from an external stereo-camera visual tracking system (VTS). In addition to comparing DL and VTS, we also included a data-driven approach based on the center-of-mass (CoM) strategy. This CoM method estimates respiratory signals by monitoring the axial changes of CoM for counts in the heart region of the sub-projections. We utilized 900 subjects with stress cardiac perfusion SPECT studies, with 302 subjects for testing and the remaining 598 subjects for training and validation. RESULTS: The Pearson's correlation coefficient between the DL respiratory signal and the reference VTS signal was 0.90, compared to 0.70 between the CoM signal and the reference. For respiratory motion correction on SPECT images, all VTS, DL, and CoM approaches partially de-blured the heart wall, resulting in a thinner wall thickness and increased recovered maximal image intensity within the wall, with VTS reducing blurring the most followed by the DL approach. Uptake quantification for the combined anterior and inferior segments of polar maps showed a mean absolute difference from the reference VTS of 1.7% for the DL method for patients with motion >12 mm, compared to 2.6% for the CoM method and 8.5% for no correction. CONCLUSION: We demonstrate the capability of a DL approach to estimate respiratory signal from SPECT projection data for cardiac perfusion imaging. Our results show that the DL based respiratory motion correction reduces artefacts and achieves similar regional quantification to that obtained using the stereo-camera VTS signals. This may enable fully automatic data-driven respiratory motion correction without relying on external motion tracking devices.

Regulation of chlorophyll biosynthesis by light-dependent acetylation of NADPH:protochlorophyll oxidoreductase A in Arabidopsis.

Chlorophylls are the major pigments that harvest light energy during photosynthesis in plants. Although reactions in chlorophyll biogenesis have been largely known, little attention has been paid to the post-translational regulation mechanism of this process. In this study, we found that four lysine sites (K128/340/350/390) of NADPH:protochlorophyllide oxidoreductase A (PORA), which catalyzes the only light-triggered step in chlorophyll biosynthesis, were acetylated after dark-grown seedlings transferred to light via acetylomics analysis. Etiolated seedlings with K390 mutation of PORA had a lower greening rate and decreased PORA acetylation after illumination. Importantly, K390 of PORA was found extremely conserved in plants and cyanobacteria via bioinformatics analysis. We further demonstrated that the acetylation level of PORA was increased by exposing the dark-grown seedlings to the histone deacetylase (HDAC) inhibitor TSA. Thus, the HDACs probably regulate the acetylation of PORA, thereby controlling this non-histone substrate to catalyze the reduction of Pchlide to produce chlorophyllide, which provides a novel regulatory mechanism by which the plant actively tunes chlorophyll biosynthesis during the conversion from skotomorphogenesis to photomorphogenesis.

Haplotype analysis and marker development of five salt-tolerant-related genes in rice (Oryza sativa L.).

Salinity stress is a great threat to the growth and productivity of crops, and development of salt-tolerant crops is of great necessity to ensure food security. Although a few genes with natural variations that confer salt tolerance at germination and seedling stage in rice have been cloned, effective intragenic markers for these genes are awaited to be developed, which hinder the use of these genes in genetic improvement of salt tolerance in rice. In this study, we first performed haplotype analysis of five rice salt-tolerant-related genes using 38 rice accessions with reference genome and 4,726 rice germplasm accessions with imputed genotypes and classified main haplotype groups and haplotypes. Subsequently, we identified unique variations for elite haplotypes reported in previous studies and developed 11 effective intragenic makers. Finally, we conducted genotyping of 533 of the 4,726 rice accessions from worldwide and 70 approved temperate geng/japonica cultivars in China using the developed markers. These results could provide effective donors and markers of salt-tolerant-related genes and thus could be of great use in genetic improvement of salt tolerance in rice.

An overview of traditional Chinese medicine affecting gut microbiota in obesity.

Obesity, a chronic metabolic disease with a complex pathophysiology, is caused by several variables. High-fat diets lead to the disruption of the gut microbiota and impaired gut barrier function in obese people. The dysbiosis and its metabolites through the intestinal barrier lead to an imbalance in energy metabolism and inflammatory response, which eventually contributes to the development of chronic diseases such as diabetes, hypertension, and cardiovascular disease. Current medicines are therapeutic to obesity in the short term; however, they may bring significant physical and emotional problems to patients as major side effects. Therefore, it is urgent to explore new therapeutic methods that have definite efficacy, can be taken for a long time, and have mild adverse effects. Numerous studies have demonstrated that traditional Chinese medicine (TCM) can control the gut microbiota in a multi-targeted and comprehensive manner, thereby restoring flora homeostasis, repairing damaged intestinal mucosal barriers, and eventually curbing the development of obesity. The active ingredients and compounds of TCM can restore the normal physiological function of the intestinal mucosal barrier by regulating gut microbiota to regulate energy metabolism, inhibit fat accumulation, affect food appetite, and reduce intestinal mucosal inflammatory response, thereby effectively promoting weight loss and providing new strategies for obesity prevention and treatment. Although there are some studies on the regulation of gut microbiota by TCM to prevent and treat obesity, all of them have the disadvantage of being systematic and comprehensive. Therefore, this work comprehensively describes the molecular mechanism of obesity mediated by gut microbiota based on the research state of obesity, gut microbiota, and TCM. A comprehensive and systematic summary of TCM targeting the regulation of gut microbiota for the treatment of obesity should be conducted in order to provide new strategies and ideas for the treatment of obesity.

Retrieval boosted computer-aided diagnosis of clustered microcalcifications for breast cancer.

PURPOSE: The authors propose an image-retrieval based approach for case-adaptive classifier design in computer-aided diagnosis (CADx). The conventional approach in CADx is to first train a pattern-classifier based on a set of existing training samples and then apply this classifier to subsequent new cases. The purpose of this work is to improve the classification accuracy of a CADx classifier by making use of a set of known cases retrieved from a reference library that are similar to the case under consideration. METHODS: In the proposed approach, the authors will first apply image-retrieval to obtain a set of lesion images from a library of known cases that have similar image features to a case being diagnosed (i.e., query). These retrieved cases are then used to optimize a pattern-classifier toward boosting its classification accuracy on the query case. The basic idea is to put more emphasis on those cases that are similar to the query. The proposed approach is demonstrated first using a linear classifier and then extended to a nonlinear classifier induced by kernel principal component analysis. RESULTS: The proposed retrieval-driven approach was tested on a library of mammogram images from 1006 cases (646 benign and 360 malignant) obtained from multiple institutions and was demonstrated to yield significant improvement in classification performance. Measured by the area under the receiver operating characteristic curve (AUC), the case-adaptive approach could boost the classification performance of a linear classifier from AUC = 0.7415 to AUC = 0.7807; similar improvement was also obtained for a nonlinear classifier, with AUC boosted from 0.7527 to 0.7838. CONCLUSIONS: Use of additional cases from a reference library that have similar image features can improve the classification accuracy of a CADx classifier on a query case. It can even outperform retraining the classifier with all the cases from the entire reference library. This implies that cases with similar image features are more relevant in defining the local decision boundary of the CADx classifier around the query.

A quantitative study of motion estimation methods on 4D cardiac gated SPECT reconstruction.

PURPOSE: Motion-compensated temporal processing can have a major impact on improving the image quality in gated cardiac single photon emission computed tomography (SPECT). In this work, we investigate the effect of different optical flow estimation methods for motion-compensated temporal processing in gated SPECT. In particular, we explore whether better motion estimation can substantially improve reconstructed image quality, and how the estimated motion would compare to the ideal case of known motion in terms of reconstruction. METHODS: We consider the following three methods for obtaining the image motion in 4D reconstruction: (1) the Horn-Schunck optical flow equation (OFE) method, (2) a recently developed periodic OFE method, and (3) known cardiac motion derived from the NURBS-based cardiac-torso (NCAT) phantom. The periodic OFE method is used to exploit the inherent periodic nature in cardiac gated images. In this method, the optical flow in a sequence is modeled by a Fourier harmonic representation, which is then estimated from the image data. We study the impact of temporal processing on 4D reconstructions when the image motion is obtained with the different methods above. For quantitative evaluation, we use simulated imaging with multiple noise realizations from the NCAT phantom, where different patient geometry and lesion sizes are also considered. To quantify the reconstruction results, we use the following measures of reconstruction accuracy and defect detection in the myocardium: (1) overall error level in the myocardium, (2) regional accuracy of the left ventricle (LV) wall, (3) accuracy of regional time activity curves of the LV, and (4) perfusion defect detectability with a channelized Hotelling observer (CHO). In addition, we also examine the effect of noise on the distortion in the reconstructed LV wall shape by detecting its contours. As a preliminary demonstration, these methods are also tested on two sets of clinical acquisitions. RESULTS: For the different quantitative measures considered, the periodic OFE further improved the reconstruction accuracy of the myocardium compared to OFE in 4D reconstruction; its improvement in reconstruction almost matched that of the known motion. Specifically, the overall mean-squared error in the myocardium was reduced by over 20% with periodic OFE; with noise level fixed at 10%, the regional bias on the LV was reduced from 20% (OFE) to 14% (periodic OFE), compared to 11% by the known motion. In addition, the CHO results show that there was also improvement in lesion detectability with the periodic OFE. The regional time activity curves obtained with the periodic OFE were also observed to be more consistent with the reference; in addition, the contours of the reconstructed LV wall with the periodic OFE were demonstrated to show less degree of variations among different noise realizations. Such improvements were also consistent with the results obtained from the clinical acquisitions. CONCLUSIONS: Use of improved optical flow estimation can further improve the accuracy of reconstructed images in 4D. The periodic OFE method not only can achieve improvements over the traditional OFE, but also can almost match that of the known motion in terms of the several quality measures considered.

A comparison study of image features between FFDM and film mammogram images.

PURPOSE: This work is to provide a direct, quantitative comparison of image features measured by film and full-field digital mammography (FFDM). The purpose is to investigate whether there is any systematic difference between film and FFDM in terms of quantitative image features and their influence on the performance of a computer-aided diagnosis (CAD) system. METHODS: The authors make use of a set of matched film-FFDM image pairs acquired from cadaver breast specimens with simulated microcalcifications consisting of bone and teeth fragments using both a GE digital mammography system and a screen-film system. To quantify the image features, the authors consider a set of 12 textural features of lesion regions and six image features of individual microcalcifications (MCs). The authors first conduct a direct comparison on these quantitative features extracted from film and FFDM images. The authors then study the performance of a CAD classifier for discriminating between MCs and false positives (FPs) when the classifier is trained on images of different types (film, FFDM, or both). RESULTS: For all the features considered, the quantitative results show a high degree of correlation between features extracted from film and FFDM, with the correlation coefficients ranging from 0.7326 to 0.9602 for the different features. Based on a Fisher sign rank test, there was no significant difference observed between the features extracted from film and those from FFDM. For both MC detection and discrimination of FPs from MCs, FFDM had a slight but statistically significant advantage in performance; however, when the classifiers were trained on different types of images (acquired with FFDM or SFM) for discriminating MCs from FPs, there was little difference. CONCLUSIONS: The results indicate good agreement between film and FFDM in quantitative image features. While FFDM images provide better detection performance in MCs, FFDM and film images may be interchangeable for the purposes of training CAD algorithms, and a single CAD algorithm may be applied to either type of images.

The Complete Chloroplast Genome Sequence of Machilus chuanchienensis (Lauraceae): Genome Structure and Phylogenetic Analysis.

Machilus chuanchienensis is an ecological tree distributed in southwestern China. It has a significant valuation with making Hawk tea using its leaves, an ethnic traditional tea-like beverage with a long history in Chinese tea culture. The whole chloroplast (cp) genome is an ideal model for the phylogenetic study of Lauraceae because of its simple structure and highly conserved features. There have been numerous reports of complete cp genome sequences in Lauraceae, but little is known about M. chuanchienensis. Here, the next-generation sequencing (NGS) was used to sequence the M. chuanchienensis cp genome. Then, a comprehensive comparative genome analysis was performed. The results revealed that the M. chuanchienensis's cp genome measured 152,748 base pairs (bp) with a GC content of 39.15% and coded 126 genes annotated, including comprising eight ribosomal RNA (rRNA), 36 transporter RNA (tRNA), and 82 protein-coding genes. In addition, the cp genome presented a typical quadripartite structure comprising a large single-copy (LSC; 93,811) region, a small single-copy (SSC; 18,803) region, and the inverted repeats (IRs; 20,067) region and contained 92 simple sequence repeat (SSR) locus in total. Phylogenetic relationships of 37 species indicated that M. chuanchienensis was a sister to M. balansae, M. melanophylla, and M. minutiflora. Further research on this crucial species may benefit significantly from these findings.