Pattern classification of interstitial lung diseases from computed tomography images using a ResNet-based network with a split-transform-merge strategy and split attention.

In patients with interstitial lung disease (ILD), accurate pattern assessment from their computed tomography (CT) images could help track lung abnormalities and evaluate treatment efficacy. Based on excellent image classification performance, convolutional neural networks (CNNs) have been massively investigated for classifying and labeling pathological patterns in the CT images of ILD patients. However, previous studies rarely considered the three-dimensional (3D) structure of the pathological patterns of ILD and used two-dimensional network input. In addition, ResNet-based networks such as SE-ResNet and ResNeXt with high classification performance have not been used for pattern classification of ILD. This study proposed a SE-ResNeXt-SA-18 for classifying pathological patterns of ILD. The SE-ResNeXt-SA-18 integrated the multipath design of the ResNeXt and the feature weighting of the squeeze-and-excitation network with split attention. The classification performance of the SE-ResNeXt-SA-18 was compared with the ResNet-18 and SE-ResNeXt-18. The influence of the input patch size on classification performance was also evaluated. Results show that the classification accuracy was increased with the increase of the patch size. With a 32 × 32 × 16 input, the SE-ResNeXt-SA-18 presented the highest performance with average accuracy, sensitivity, and specificity of 0.991, 0.979, and 0.994. High-weight regions in the class activation maps of the SE-ResNeXt-SA-18 also matched the specific pattern features. In comparison, the performance of the SE-ResNeXt-SA-18 is superior to the previously reported CNNs in classifying the ILD patterns. We concluded that the SE-ResNeXt-SA-18 could help track or monitor the progress of ILD through accuracy pattern classification.

Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors.

BACKGROUND: To develop an artificial intelligence (AI) model with radiomics and deep learning (DL) features extracted from CT images to distinguish benign from malignant ovarian tumors. METHODS: We enrolled 149 patients with pathologically confirmed ovarian tumors. A total of 185 tumors were included and divided into training and testing sets in a 7:3 ratio. All tumors were manually segmented from preoperative contrast-enhanced CT images. CT image features were extracted using radiomics and DL. Five models with different combinations of feature sets were built. Benign and malignant tumors were classified using machine learning (ML) classifiers. The model performance was compared with five radiologists on the testing set. RESULTS:  Among the five models, the best performing model is the ensemble model with a combination of radiomics, DL, and clinical feature sets. The model achieved an accuracy of 82%, specificity of 89% and sensitivity of 68%. Compared with junior radiologists averaged results, the model had a higher accuracy (82% vs 66%) and specificity (89% vs 65%) with comparable sensitivity (68% vs 67%). With the assistance of the model, the junior radiologists achieved a higher average accuracy (81% vs 66%), specificity (80% vs 65%), and sensitivity (82% vs 67%), approaching to the performance of senior radiologists. CONCLUSIONS:  We developed a CT-based AI model that can differentiate benign and malignant ovarian tumors with high accuracy and specificity. This model significantly improved the performance of less-experienced radiologists in ovarian tumor assessment, and may potentially guide gynecologists to provide better therapeutic strategies for these patients.

Evaluating the contact anatomy and contact bone volume of spinal screws using a novel drilled surface image.

Intraoperative navigation systems have been widely applied in spinal fusion surgery to improve the implantation accuracy of spinal screws using orthogonal tomographic and surface-rendering imaging. However, these images contain limited anatomical information and no information on bone volume contact by the implanted screw, which has been proven to affect the stability of implanted screws. This study proposed a novel drilled surface imaging technique that displays anatomical integration properties to calculate the contact bone volume (CBV) of the screws implanted along an implantation trajectory. A cylinder was used to represent the area traversed by the screws, which was manually rotated and translated to a predetermined implantation trajectory according to a vertebra model obtained using computed tomography (CT) image volumes. The drilled surface image was reconstructed by interpolating the CT numbers at the predefined sampling points on the cylinder surface. The anatomical integration property and CBV of the screw implanted along the transpedicular trajectory (TT) and cortical bone trajectory (CBT) were evaluated and compared. The drilled surface image fully revealed the contact anatomical structure of the screw under the trajectories, improving the understanding of the anatomical integration of the screw and surrounding tissues. On average, the CBV of the CBT was 30% greater than that of the TT. The proposed drilled surface image may be applied in preoperative planning and integrated into intraoperative navigation systems to evaluate the anatomical integration and degree of bone contact of the screw implanted along a trajectory.

Dibenzocyclooctendiones (DBCDOs): Arginine-Selective Chemical Labeling Reagents Obtained through Benzilic Acid Rearrangement.

We demonstrate that dibenzocyclooctendiones (DBCDOs) are efficient chemical reagents for the site-specific labeling of arginine-containing biomolecules. Unlike the commonly used probes, DBCDOs undergo an irreversible ring-contracted rearrangement with the guanidinium group on arginine residues under mild reaction conditions. The regioselective dual-labeled arginine residues were obtained in a one-pot reaction with our tested substrates. The efficiency of DBCDOs reactions and their ease of synthesis make DBCDOs an attractive choice for the site-selective bioconjugation of arginine.

Caffeine enhances BOLD responses to electrical whisker pad stimulation in rats during alpha-chloralose anaesthesia.

By reducing the cerebral blood flow and thereby increasing the resting deoxyhaemoglobin concentration, many human studies have shown that caffeine has a beneficial effect on enhancing the magnitude of blood-oxygenation-level-dependent (BOLD) responses. However, the effect of caffeine on BOLD responses in animals under anaesthesia has not been demonstrated. In this study, we aimed to determine the effect of systemic caffeine administration on BOLD responses in rats under alpha-chloralose. By applying electric whisker pad stimulation to male Sprague-Dawley rats, we performed fMRI measurements before and after the caffeine injection (40 mg/kg, n = 7) or an equivalent volume of saline (n = 6) at 7T. To understand the potential perturbation of animal physiology during stimulation, arterial blood pressure was measured in a separate group of animals (n = 3) outside the scanner. Caffeine significantly decreased baseline BOLD signals (p = .05) due to the increased deoxyhaemoglobin level. Both BOLD responses and t-values in the primary somatosensory cortex were significantly increased (both p < .05). The blood pressure changed insignificantly (p > .05). No significant differences in BOLD responses and t-values were observed in the control condition of saline injection (both p > .05). These findings suggested that, although the cerebral activity was lower under alpha-chloralose anaesthesia, the higher level of deoxygemoglobin at the baseline under the caffeinated condition can benefit the magnitude of BOLD responses in rats. These findings suggest that animal models might serve as potential platforms for further caffeine-related fMRI research studies.

Calculating air volume fractions from computed tomography images for chronic obstructive pulmonary disease diagnosis.

Quantitative evaluation using image biomarkers calculated from threshold-segmented low-attenuation areas on chest computed tomography (CT) images for diagnosing chronic obstructive pulmonary diseases (COPD) has been widely investigated. However, the segmentation results depend on the applied threshold and slice thickness of the CT images because of the partial volume effect (PVE). In this study, the air volume fraction (AV/TV) of lungs was calculated from CT images using a two-compartment model (TCM) for COPD diagnosis. A relative air volume histogram (RAVH) was constructed using the AV/TV values to describe the air content characteristics of lungs. In phantom studies, the TCM accurately calculated total cavity volumes and foam masses with percent errors of less than 8% and ±4%, respectively. In patient studies, the relative volumes of normal and damaged lung tissues and the damaged-to-normal RV ratio were defined and calculated from the RAVHs as image biomarkers, which correctly differentiated COPD patients from controls in 2.5- and 5-mm-thick images with areas under receiver operating characteristic curves of >0.94. The AV/TV calculated using the TCM can prevent the effect of slice thickness, and the image biomarkers calculated from the RAVH are reliable for diagnosing COPD.

Short- and long-term reproducibility of BOLD signal change induced by breath-holding at 1.5 and 3 T.

Cerebrovascular reactivity (CVR) can give insight into the cerebrovascular function. CVR can be estimated by measuring a blood-oxygen-level-dependent (BOLD) response combined with breath-holding (BH). The reproducibility of this technique has been addressed and existing studies have focused on short-term reproducibility using a 3 T magnetic resonance imaging (MRI) system. However, little is known about the long-term reproducibility of this procedure and the corresponding reproducibility using a 1.5 T MRI system. Here, we systematically examined the short- and long-term reproducibility of BOLD responses to BH across field strengths. Nine subjects participated in three MRI sessions separated by 30 minutes (sessions 1 and 2: short term) and 68-92 days (sessions 1 and 3, long term) at both 1.5 and 3 T MRI. Our findings revealed that significant differences between field strengths were detected in the activated gray matter volume and BOLD signal change (both P < 0.001), with smaller magnitudes at 1.5 T. However, activation patterns were reproducible, independent of the time interval, brain region or field strength. All interscan coefficient of variation values were below the 33% fiducial limit, and the intraclass correlation coefficient values were above 0.4, which is usually considered the acceptability limit in functional studies. These findings suggest that the response of BOLD signal to BH for assessing CVR is reproducible over time at 1.5 and 3 T. This technique can be considered a tool for monitoring longitudinal changes in patients with cerebrovascular diseases, and its use should be encouraged for clinical 1.5 T MRI systems.

A novel computed tomography image synthesis method for correcting the spectrum dependence of CT numbers.

The quantitative evaluation of computed tomography (CT) images is widely investigated and applied in clinical diagnosis. However, the CT number of tissue can vary with scanners or applied tube voltages because of the x-ray spectrum dependence of measured linear attenuation coefficients that degrades evaluation accuracy and limits multicenter or multimodality research. This study proposed a novel CT image synthesis method to correct the spectrum dependence of CT numbers by normalizing them to the same spectrum condition. Stoichiometric calibration was performed to derive the spectrum characteristic parameters (SCPs) of six spectra from two CT scanners with different applied tube voltages. Subsequently, conversion relationships between CT numbers and tissue parameters (TPs) were determined using the SCPs and standard tissue data. The CT number of a tissue measured from a spectrum condition was converted to TPs using these relationships, and the results were used to estimate the CT number of the tissue in another spectrum condition using the corresponding SCPs. Phantom, cadaver, and patient studies were performed to evaluate the proposed method. In the phantom study, image synthesis reduced the mean difference between the CT numbers of tissue-equivalent phantoms measured using different spectra from 57.96 to 33.94 HU. In the cadaveric study, the mean difference between the CT numbers of a temporal bone flap measured using different spectra was lowered by over 57%. In the patient image study, a significant difference of 81.5 HU was observed between the mean CT numbers of femoral shafts obtained from the two scanners; this difference was reduced to less than 17 HU, which was nonsignificant, when the proposed method was used. The proposed image synthesis method could reduce the spectrum dependence of CT numbers measured with different spectra and could be applied clinically to improve the accuracy of multicenter and multimodality evaluation and research.

Effects of Hemodynamic Response Function Selection on Rat fMRI Statistical Analyses.

The selection of the appropriate hemodynamic response function (HRF) for signal modeling in functional magnetic resonance imaging (fMRI) is important. Although the use of the boxcar-shaped hemodynamic response function (BHRF) and canonical hemodynamic response (CHRF) has gained increasing popularity in rodent fMRI studies, whether the selected HRF affects the results of rodent fMRI has not been fully elucidated. Here we investigated the signal change and t-statistic sensitivities of BHRF, CHRF, and impulse response function (IRF). The effect of HRF selection on different tasks was analyzed by using data collected from two groups of rats receiving either 3 mA whisker pad or 3 mA forepaw electrical stimulations (n = 10 for each group). Under whisker pad stimulation with large blood-oxygen-level dependent (BOLD) signal change (4.31 ± 0.42%), BHRF significantly underestimated signal changes (P < 0.001) and t-statistics (P < 0.001) compared with CHRF or IRF. CHRF and IRF did not provide significantly different t-statistics (P > 0.05). Under forepaw stimulation with small BOLD signal change (1.71 ± 0.34%), different HRFs provided insignificantly different t-statistics (P > 0.05). Therefore, the selected HRF can influence data analysis in rodent fMRI experiments with large BOLD responses but not in those with small BOLD responses.

The effect of caffeine on cerebral metabolism during alpha-chloralose anesthesia differs from isoflurane anesthesia in the rat brain.

RATIONALE: Caffeine is a widely studied psychostimulant, even though its exact effect on brain activity remains to be elucidated. Positron emission tomography (PET) allows studying mechanisms underlying cerebral metabolic responses to caffeine in caffeine-naïve rats. Rodent studies are typically performed under anesthesia. However, the anesthesia may affect neurotransmitter systems targeted by tested drugs. OBJECTIVES: The scope of the present study was to address the impairing or enhancing effect of two common anesthetics, alpha-chloralose and isoflurane, on the kinetics of caffeine. METHODS: The first group of rats (n = 15) were anesthetized under 1.5% isoflurane anesthesia. The second group of rats (n = 15) were anesthetized under alpha-chloralose (80 mg/kg). These rats received an intravenous injection of saline (n = 5) or of 2.5 mg/kg (n = 5) or 40 mg/kg (n = 5) caffeine for both groups. RESULTS: With 2.5 mg/kg or 40 mg/kg caffeine, whole-brain cerebral metabolism was significantly reduced by 17.2% and 17% (both P < 0.01), respectively, under alpha-chloralose anesthesia. However, the lower dose of caffeine (2.5 mg/kg) had a limited effect on brain metabolism, whereas its higher dose (40 mg/kg) produced enhancements in brain metabolism in the striatum, hippocampus, and thalamus (all P < 0.05) under isoflurane anesthesia. CONCLUSION: These findings demonstrate significant differences in brain responses to caffeine on the basic of the anesthesia regimen used, which highlights the importance of attention to the anesthetic used when interpreting findings from animal pharmacological studies because of possible interactions between the anesthetic and the drug under study.

Osteogenic and angiogenic potentials of the cell-laden hydrogel/mussel-inspired calcium silicate complex hierarchical porous scaffold fabricated by 3D bioprinting.

3D printing has been popularly used in the bone tissue engineering, as many of the biomaterials for this field of study can be prepared for and produced from this additive manufacturing technique. In this study, we strategized a solvent-free processing to fabricate the polydopamine-modified calcium silicate (PDACS)/poly-caprolactone (PCL) scaffold with Wharton's jelly mesenchymal stem cells (WJMSCs) incorporated with human umbilical vein endothelial cells (HUVEC)-laden hydrogel. The PDACS/PCL/hydrogel 3D scaffold yielded a Young's modulus of the 3D scaffolds as high as 75 MPa. In addition, the vascular morphogenesis and cellular behaviors regulated by our hybrid scaffolds were also intricately evaluated. Furthermore, the HUVEC in the bioink exhibited higher levels of angiogenic biomarkers and showed potential for the formation of complex vascular networks. Higher levels of bone formation proteins were also observed in our composites. Such a hybrid of synthetic materials with cell constituents not only enhances osteogenesis but also stimulates vessel network development in angiogenesis, presenting the fact that 3D printing can be further applied in improving bone tissue regeneration in numerous aspects. We believe that this method may serve as a useful and effective approach for the regeneration of defective complex hard tissues in deep bone structures.

MRI-based measurements of whole-brain global cerebral blood flow: Comparison and validation at 1.5T and 3T.

BACKGROUND: Whole-brain global cerebral blood flow (CBF) determined by MRI techniques, calculated using total CBF (TCBF) from phase-contrast MRI (PC-MRI), and brain parenchyma volume (BPV) from T1 -weighted image, have become increasingly popular in many applications. PURPOSE/HYPOTHESIS: To determine if MRI-based measurements of whole-brain global CBF data obtained across different field strengths could be merged, TCBF and BPV data acquired at 1.5T and 3T were compared. STUDY TYPE: Prospective study. POPULATION: Seventeen healthy subjects (eight females, aged 21-29 years old). FIELD STRENGTH/SEQUENCE: Fast spoiled gradient echo (FSPGR) and PC-MRI at both 1.5T and 3T. ASSESSMENT: TCBF and BPV data acquired at 1.5T and 3T were compared. STATISTICAL TESTS: The relationships of TCBF and whole-brain global CBF between two field strengths were examined by using the Pearson correlation coefficient analysis and intraclass correlation coefficient (ICC). RESULTS: Regression analysis revealed a strong correlation between TCBF at two field strengths (R2 = 0.78, P < 0.001), and the ICC was 0.85, suggesting measurements of TCBF at 1.5T were comparable and correlated with those at 3T. There was a significant difference in BPV between field strengths, where the white matter estimate was significantly larger at 1.5T when compared with that at 3T (P < 0.001). When TCBF was further normalized to the brain parenchyma mass to obtain whole-brain global CBF, it only showed a moderate correlation between measurements at the two field strengths (R2 = 0.46, P = 0.003) and lower ICC of 0.66, reflecting the slightly higher interstrength variability in the whole-brain global CBF measurements. DATA CONCLUSION: TCBF measurements could be performed equally well with comparable results at both field strengths, but specific attention should be given when TCBF is further normalized to BPV to obtain whole-brain global CBF. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1273-1280.

The Development of Skull Prosthesis Through Active Contour Model.

Skull defects result in brain infection and inadequate brain protection and pose a general danger to patient health. To avoid these situations and prevent re-injury, a prosthesis must be constructed and grafted onto the deficient region. With the development of rapid customization through additive manufacturing and 3D printing technology, skull prostheses can be fabricated accurately and efficiently prior to cranioplasty. However, an unfitted skull prosthesis made with a metal implant can cause repeated infection, potentially necessitating secondary surgery. This paper presents a method of creating suitably geometric graphics of skull defects to be applied in skull repair through active contour models. These models can be adjusted in each computed tomography slice according to the graphic features, and the curves representing the skull defect can be modeled. The generated graphics can adequately mimic the natural curvature of the complete skull. This method will enable clinical surgeons to rapidly implant customized prostheses, which is of particular importance in emergency surgery. The findings of this research can help surgeons provide patients with skull defects with treatment of the highest quality.

3D Printing of Cytocompatible Water-Based Light-Cured Polyurethane with Hyaluronic Acid for Cartilage Tissue Engineering Applications.

Diseases in articular cartilages have affected millions of people globally. Although the biochemical and cellular composition of articular cartilages is relatively simple, there is a limitation in the self-repair ability of the cartilage. Therefore, developing strategies for cartilage repair is very important. Here, we report on a new liquid resin preparation process of water-based polyurethane based photosensitive materials with hyaluronic acid with application of the materials for 3D printed customized cartilage scaffolds. The scaffold has high cytocompatibility and is one that closely mimics the mechanical properties of articular cartilages. It is suitable for culturing human Wharton's jelly mesenchymal stem cells (hWJMSCs) and the cells in this case showed an excellent chondrogenic differentiation capacity. We consider that the 3D printing hybrid scaffolds may have potential in customized tissue engineering and also facilitate the development of cartilage tissue engineering.

Optimized analysis of blood flow and wall shear stress in the common carotid artery of rat model by phase-contrast MRI.

The present study systemically investigated the influence of gated/non-gated sequences, velocity encoding (VENC), and spatial resolution on blood flow, wall shear stress (WSS), and artery area evaluations when scanning the common carotid artery (CCA) in rats using phase-contrast magnetic resonance imaging (PC-MRI). We first tested whether or not non-gated PC-MRI was appropriate for evaluating blood flow and WSS in rats. For both gated and non-gated techniques, VENC values in the range of 60-120 cm/s with an interval of 10 cm/s were also tested. Second, we optimized the in-plane resolution of PC-MRI for blood flow and WSS measurements. Results showed the usage of a gated instrument can provide more reproducible assessments, whereas VENC had an insignificant influence on all hemodynamic measurements (all P > 0.05). Lower resolutions, such as 0.63 mm, led to significant overestimations in blood flow and artery area quantifications and to an underestimation in WSS measurements (all P < 0.05). However, a higher resolution of 0.16 mm slightly increased measurement variation. As a tradeoff between accuracy and scan time, we propose a gated PC-MRI sequence with a VENC of 120 cm/s and a resolution of 0.21 mm to be used to extract hemodynamic information about rat CCA.

Polymer gel dosimeters for pretreatment radiotherapy verification using the three-dimensional gamma evaluation and pass rate maps.

Polymer gel dosimeters (PGDs) have been widely studied for use in the pretreatment verification of clinical radiation therapy. However, the readability of PGDs in three-dimensional (3D) dosimetry remain unclear. In this study, the pretreatment verifications of clinical radiation therapy were performed using an N-isopropyl-acrylamide (NIPAM) PGD, and the results were used to evaluate the performance of the NIPAM PGD on 3D dose measurement. A gel phantom was used to measure the dose distribution of a clinical case of intensity-modulated radiation therapy. Magnetic resonance imaging scans were performed for dose readouts. The measured dose volumes were compared with the planned dose volume. The relative volume histograms showed that relative volumes with a negative percent dose difference decreased as time elapsed. Furthermore, the histograms revealed few changes after 24h postirradiation. For the 3%/3mm and 2%/2mm criteria, the pass rates of the 12- and 24-h dose volumes were higher than 95%, respectively. This study thus concludes that the pass rate map can be used to evaluate the dose-temporal readability of PGDs and that the NIPAM PGD can be used for clinical pretreatment verifications.

Converting computed tomography images into photon interaction coefficients by using stoichiometric calibration and parametric fit models.

PURPOSE: X ray and γ-ray are widely applied in radiology, radiotherapy, and nuclear medicine. Linear attenuation coefficients and linear energy absorption coefficients are essential for dose calculation and image correction. In this study, a method that entails combining the stoichiometric calibration and parametric physical models was developed to convert computed tomography (CT) images into the linear attenuation coefficients and linear energy absorption coefficients. METHODS: A calibration scan was performed using standard tissue-equivalent materials to obtain the characteristics of the x-ray energy spectrum. Subsequently, relationships between CT numbers and tissue parameters were established using standard soft tissue and bone tissue data adopted from the literature. The linear attenuation coefficient and linear energy absorption coefficient were calculated using the parametric fit model. RESULTS: The results showed a linear relationship between CT numbers and tissue parameters. The tissue-equivalent materials differed from real human tissues, leading to considerable errors in estimation of mass attenuation coefficients when the photon energy was lower than 50 keV. Mass attenuation coefficients and mass energy transfer coefficients of five tissues were calculated and validated using clinical CT images. The error was less than ± 5% and ± 8%, compared with the values of the International Commission on Radiation Units (ICRU) 46 report. CONCLUSIONS: The probability of photon interaction with tissues and physical characteristics of tissues can be accurately evaluated by using the proposed method and applied in various clinical applications.

A Novel Two-Compartment Model for Calculating Bone Volume Fractions and Bone Mineral Densities From Computed Tomography Images.

Osteoporosis is a disease characterized by a degradation of bone structures. Various methods have been developed to diagnose osteoporosis by measuring bone mineral density (BMD) of patients. However, BMDs from these methods were not equivalent and were incomparable. In addition, partial volume effect introduces errors in estimating bone volume from computed tomography (CT) images using image segmentation. In this study, a two-compartment model (TCM) was proposed to calculate bone volume fraction (BV/TV) and BMD from CT images. The TCM considers bones to be composed of two sub-materials. Various equivalent BV/TV and BMD can be calculated by applying corresponding sub-material pairs in the TCM. In contrast to image segmentation, the TCM prevented the influence of the partial volume effect by calculating the volume percentage of sub-material in each image voxel. Validations of the TCM were performed using bone-equivalent uniform phantoms, a 3D-printed trabecular-structural phantom, a temporal bone flap, and abdominal CT images. By using the TCM, the calculated BV/TVs of the uniform phantoms were within percent errors of ±2%; the percent errors of the structural volumes with various CT slice thickness were below 9%; the volume of the temporal bone flap was close to that from micro-CT images with a percent error of 4.1%. No significant difference (p >0.01) was found between the areal BMD of lumbar vertebrae calculated using the TCM and measured using dual-energy X-ray absorptiometry. In conclusion, the proposed TCM could be applied to diagnose osteoporosis, while providing a basis for comparing various measurement methods.

iPARTS2: an improved tool for pairwise alignment of RNA tertiary structures, version 2.

Since its first release in 2010, iPARTS has become a valuable tool for globally or locally aligning two RNA 3D structures. It was implemented by a structural alphabet (SA)-based approach, which uses an SA of 23 letters to reduce RNA 3D structures into 1D sequences of SA letters and applies traditional sequence alignment to these SA-encoded sequences for determining their global or local similarity. In this version, we have re-implemented iPARTS into a new web server iPARTS2 by constructing a totally new SA, which consists of 92 elements with each carrying both information of base and backbone geometry for a representative nucleotide. This SA is significantly different from the one used in iPARTS, because the latter consists of only 23 elements with each carrying only the backbone geometry information of a representative nucleotide. Our experimental results have shown that iPARTS2 outperforms its previous version iPARTS and also achieves better accuracy than other popular tools, such as SARA, SETTER and RASS, in RNA alignment quality and function prediction. iPARTS2 takes as input two RNA 3D structures in the PDB format and outputs their global or local alignments with graphical display. iPARTS2 is now available online at http://genome.cs.nthu.edu.tw/iPARTS2/.

A Comprehensive Evaluation of NIPAM Polymer Gel Dosimeters on Three Orthogonal Planes and Temporal Stability Analysis.

Polymer gel dosimeters have been proven useful for dose evaluation in radiotherapy treatments. Previous studies have demonstrated that using a polymer gel dosimeter requires a 24 h reaction time to stabilize and further evaluate the measured dose distribution in two-dimensional dosimetry. In this study, the short-term stability within 24 h and feasibility of N-isopropylacrylamide (NIPAM) polymer gel dosimeters for use in three-dimensional dosimetry were evaluated using magnetic resonance imaging (MRI). NIPAM gels were used to measure the dose volume in a clinical case of intensity-modulated radiation therapy (IMRT). For dose readouts, MR images of irradiated NIPAM gel phantoms were acquired at 2, 5, 12, and 24 h after dose delivery. The mean standard errors of dose conversion from using dose calibration curves (DRC) were calculated. The measured dose volumes at the four time points were compared with those calculated using a treatment planning system (TPS). The mean standard errors of the dose conversion from using the DRCs were lower than 1 Gy. Mean pass rates of 2, 5, 12, and 24 h axial dose maps calculated using gamma evaluation with 3% dose difference and 3 mm distance-to-agreement criteria were 83.5% ± 0.9%, 85.9% ± 0.6%, 98.7% ± 0.3%, and 98.5% ± 0.9%, respectively. Compared with the dose volume histogram of the TPS, the absolute mean relative volume differences of the 2, 5, 12, and 24 h measured dose volumes were lower than 1% for the irradiated region with an absorbed dose higher than 2.8 Gy. It was concluded that a 12 h reaction time was sufficient to acquire accurate dose volume using the NIPAM gels with MR readouts.