CT Method Research Articles

A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation

To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessment of coronary artery calcium score (CACS). Sixty adult patients who underwent two unenhanced chest CT examinations, a normal dose CT (NDCT) and an ULDCT, were enrolled prospectively between September 2017 to December 201. A special training set was created to learn the characteristics of the real noise affecting the ULDCT implementing a fully convolutional neural network with batch normalisation. Subsequently, the 60 ULDCTs of the evaluation set were denoised. Two blinded radiologists assessed the NDCT, ULDCT, and denoised-ULDCT (DULDCT), assigning a CACS and categorised each scan as having a score above or below 100 and presence of calcifications (score 0 versus >0). Statistical analysis was used to evaluate the agreement between the readers and differences in CACSs between each imaging method. After excluding one patient, the cohort included 59 patients (median age 67 years, 58% men). The ULDCT median effective radiation dose (ERD) was 0.172 mSv, which was 2.8% of the NDCT median ERD. Denoising improved the signal-to-noise ratio by 27.7% (p<0.001). Interobserver agreement was almost perfect between readers (intraclass correlation coefficient >0.993). CACSs were lower for ULDCT and DULDCT as compared to the NDCT (p≤0.001). In differentiating between the presence and absence of coronary artery calcifications, DULDCT showed greater accuracy (98-100%) and positive likelihood ratio (14.29->99) compared to ULDCT (92% and 2.78, respectively). DULCT significantly reduced the image noise and better identified patients with no coronary artery calcifications than native ULDCT.

Identification and Validation of Reference Genes for RT-qPCR Normalization in Nauphoeta cinerea (Olivier, 1789) (Blattodea, Blaberidae)

Quantitative RT-PCR (q-RT-PCR) is a powerful tool that allows large-scale analysis of very small changes in gene expression. For the calculation of gene expression, such as the delta-delta Ct method, different PCR primer efficiencies (E) may affect the result, as PCR primer yields are assumed to be comparable for the gene of interest and housekeeping gene. Therefore, identification of a suitable reference gene for data normalization is an important step in the development of qPCR assays. Furthermore, accurate and reliable results depend on the use of stable reference genes for normalization. The aim of the current study is the identification and validation of a set of six housekeeping genes (GADPH, RPS18, α-TUB, EF1α, ArgK, and ACTB) in cockroach species Nauphoeta cinerea adults using five different algorithms (ΔCt method, Bestkeeper, geNorm, Normfinder and RefFinder) to evaluate the stability of selected reference genes expression. Our results show that α-Tub use provides accurate normalization of gene expression levels in N. cinerea adults. In addition, since the GADPH is selected as the second most stable reference gene, GADPH can be also used for transcript analysis N. cinerea adults. Our study also showed that ACTB (β-actin) should not be used for normalizing transcript levels when examining N. cinerea adults. Additionally, validation studies for reference genes in cockroaches are very few (only one) in the literature. Therefore, the results highlight the need for validation of reference genes under biotic and abiotic conditions in q-RT-PCR studies in cockroaches.

Induction of Bax and Activation of Caspases Hydro Ethanoic Leaf Extract of Citrullus colocynthis(L)- Mediated Apoptosis in Human Liver Cancer Cells Hep G2

Introduction: Citrullus colocynthis is a desert plant of the cucurbitaceae family. C. colocynthis grows in many countries with semi dry lands and that seeds are rich in oil which can encourage their sustainable agriculture to produce an economic biodiesel with a competitive price. Apoptosis, also termed as programmed cell death this is a key regulator of tissue homeostasis.&#x0D; Aim of the Study: To study the induction of bax and activation of caspases hydro ethanolic leaf extract of Citrullus colocynthis (L)- mediated apoptosis in human liver cancer cells Hep G2.&#x0D; Materials and Methods: In the present study, a human liver cancer cell line was procured from the National Centre for Cell science (NCCS), Pune, India. The cytotoxic potential of plant extract was analysed by MTG assay. mRNA expression of BaxmRNA and caspase-mRNA were analysed by Real-Time PCR using gene specific primers and a comparative CT method was used to analyse expression of genes. The data were analysed statistically using Graph pad prism software Version 5.&#x0D; Results: MTT analysis showed that Citrullus colocynthis a significant increase in proliferation of human liver cancer cells (P&lt;0.05) compared to untreated cells. However, 400 and 500 /g of the extract showed maximum effect in controlling cell growth. Results of the &lt;mRNA expression analysis showed that Citrullus colocynthis reduced the expression of BaxmRNA/ caspase-mRNA in human liver cancer cells at 400 and 500 /g (P&lt;0.05).&#x0D; Discussion: The anticancer effect of Citrullus colocynthis has been via a variety of pathways which includes apoptotic pathway, anti-inflammatory traits, and antioxidant pathway, etc [1]. Effect of HEAM on the mRNA level of tumor related genes (p53, Bcl-2), inflammatory (IL-1β, IL-6 and c-jun) and anti-inflammatory (IL-4) cytokines. Representative photographs of ethidium-bromide-stained 2% agarose gels for each gene after 7 months of treatment.&#x0D; Conclusion: The hydroethanolic leaf extract obtained from the Citrullus colocynthis exhibited anti-proliferative effect on human liver cancer cells HepG2 cell line by affecting the expression of the Bax mRNA and Bax mRNA and hindering the cell viability. Hence, it can be a great scope for using the extract into medicinal properties with further studies to improve herbal medicine for cancer over expensive drugs.

Selection of Reference Genes for RT-qPCR Analysis in the Hawthorn Spider Mite, Amphitetranychus viennensis (Acarina: Tetranychidae), Under Acaricide Treatments.

Hawthorn spider mite, Amphitetranychus viennensis Zacher, one of the most damaging arthropod pests for Rosaceaous fruit trees and ornamentals, has developed resistance to most of the commercially available acaricides. To understand the molecular basis of acaricide resistance, a standardized protocol for real-time quantitative reverse transcription PCR (RT-qPCR) following the MIQE (minimum information for publication of quantitative real time PCR experiments) guidelines is needed. In this study, we screened for the internal references in A. viennensis to study in acaricide resistance. In total, 10 candidate reference genes, including EF1A, 28S rRNA, 18S rRNA, α-tubulin, Actin3, RPS9, GAPDH, V-ATPase B, RPL13, and V-ATPase A, were assessed under the treatments of four commonly used acaricides with distinct mode-of-actions (MOAs). Based on the Insecticide Resistance Action Committee MOA classification, avermectin, bifenazate, spirodiclofen, and fenpropathrin belong to group 6, 20D, 23, and 3A, respectively. The expression profiles of these candidate genes were evaluated using geNorm, Normfinder, BestKeeper, and ∆Ct methods, respectively. Eventually, different sets of reference genes were recommended for each acaricide according to RefFinder, a comprehensive platform integrating all four above-mentioned algorithms. Specifically, the top three recommendations were 1) 28S, V-ATPase A, and Actin 3 for avermectin, 2) GAPDH, RPS9, and 28S for bifenazate, 3) Actin 3, V-ATPase B, and α-tubulin for spirodiclofen, and 4) Actin 3, α-tubulin, and V-ATPase A for fenpropathrin. Although unique sets of genes are proposed for each acaricide, α-tubulin, EF1A, and GAPDH are the most consistently stably expressed reference genes when A. viennensis was challenged chemically. Our findings lay the foundation for the study of acaricide resistance in the phytophagous mites in general, and in the hawthorn spider mite, A. viennensis, in particular.

Quantification of the volume fraction of fat, water and bone mineral in spongiosa for red marrow dosimetry in molecular radiotherapy by using a dual-energy (SPECT/)CT

A patient-specific absorbed dose calculation for red marrow dosimetry requires quantifying patient-specific volume fractions of the red marrow, yellow marrow, and trabecular bone in the spongiosa of several skeletal sites. This quantification allows selecting appropriate S values calculated from the parameterized radiation transport models for bone and bone marrow dosimetry. Currently, no comprehensive, individualized, and non-invasive procedure is available for quantifying the volume fractions of red marrow, yellow marrow, and trabecular bone in the spongiosa. This study aims to provide a new quantitative method based on dual-energy computed tomography to fill this gap in red marrow dosimetry using a (SPECT/)CT system. MethodsFirst, a method for parametrizing the photon attenuation coefficients relative to water was implemented. Next, a method to calculate the effective atomic number (Zeff) and effective mass density (ρeff) using dual-energy CT (DECT) was employed. Lastly, two- and three-material decomposition using a dual-energy quantitative CT method (DEQCT) was performed in an anthropomorphic spine phantom and two bone samples of a boar, respectively.The measurements of Zeff and ρeff were compared with the syngo.CT DE Rho/Z tool (Siemens Healthineers). Furthermore, the DEQCT method implemented in this study (DEQCT-I) was compared with a second DEQCT method based on the use of external material standards (DEQCT-II). DEQCT-II was used as reference method for calculating relative errors. ResultsThe two-material decomposition in the anthropomorphic spine phantom presented a maximum relative error of −10% for the bone mineral density quantification. Furthermore, Zeff and ρeff calculated by DEQCT-I differed from syngo.CT DE Rho/Z tool by less than 4.4% and 1.9%, respectively. The three-material decomposition in the two bone samples showed a maximum relative error of 21%, −17%, and 15% for the quantification of the volume fractions of fat, water, and bone mineral equivalent materials. Lastly, Zeff and ρeff calculated by DEQCT-I differed from syngo.CT DE Rho/Z tool by less than 8.2% and 7.0%, respectively. ConclusionThis study shows that quantifying the volume fraction of fat, water, and bone mineral using a phantom-independent and post-reconstruction DEQCT method is feasible. DEQCT-I has the advantage of not requiring prior information about the X-ray spectra or the detector sensitivity function, as is the case with spectral-based DEQCT methods. Instead, DEQCT-I, similar to other DEQCT methods depends on the chemical description of reference materials and a beam hardening correction function.DEQCT-I method provides an individualized and non-invasive procedure using a (SPECT/)CT system to apply S values based on the patient-specific volume fractions of yellow marrow, red marrow, and bone mineral in red marrow dosimetry.

Selection and Validation of Reliable Reference Genes for qRT-PCR Normalization of Bursaphelenchus xylophilus from Different Temperature Conditions and Developmental Stages

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a powerful technique for studying gene expression. The key to quantitative accuracy depends on the stability of the reference genes used for data normalization under different experimental conditions. Pine wood nematode (PWN, Bursaphelenchus xylophilus) is the causal agent of the devastating pine wilt disease (PWD). Extensive and prompt research is needed to understand the molecular mechanism of PWD, but identification of the reference PWN genes for standardized qRT-PCR has not been reported yet. We have analyzed eight candidate reference genes of PWN across different temperature conditions and developmental stages. Delta Ct method, GeNorm, NormFinder, BestKeeper, and RefFinder algorithms were used to evaluate the stability of expression of these genes. Finally, we use heat shock protein 90 (HSP90) in different temperatures and arginine kinase gene (AK) in different developmental stages to confirm the stability of these genes. UBCE and EF1γ were most stable across different temperature treatments, whereas EF1γ and Actin were most stable across different developmental stages. In general, these results indicate that EF1γ is the most stable gene for qRT-PCR under different conditions. The systematic analysis of qRT-PCR reference gene selection will be helpful for future functional analysis and exploration of B. xylophilus genetic resources.

An unsupervised reconstruction method for low-dose CT using deep generative regularization prior

Low-dose CT imaging requires reconstruction from noisy indirect measurements which can be defined as an ill-posed linear inverse problem. In addition to conventional FBP method in CT imaging, recent compressed sensing based methods exploit handcrafted priors which are mostly simplistic and hard to determine. More recently, deep learning (DL) based methods have become popular in medical imaging field. In CT imaging, DL based methods try to learn a function that maps low-dose images to normal-dose images. Although the results of these methods are promising, their success mostly depends on the availability of high-quality massive datasets. In this study, we proposed a method that does not require any training data or a learning process. Our method exploits such an approach that deep convolutional neural networks (CNNs) generate patterns easier than the noise, therefore randomly initialized generative neural networks can be suitable priors to be used in regularizing the reconstruction. In the experiments, the proposed method is implemented with different loss function variants. Both analytical CT phantoms and human CT images are used with different views. Conventional FBP method, a popular iterative method (SART), and TV regularized SART are used in the comparisons. We demonstrated that our method with different loss function variants outperforms the other methods both qualitatively and quantitatively.

Superheating of Structure I Gas Hydrates within the Structure II Cyclopentane Hydrate Shell.

The superheated state of methane (CH4) hydrate that exists under the surface ice layer can persist for considerable lengths of time, which showed promise as a method for storing and transporting natural gas. This study extends this further by coating sI CH4 hydrate with one of several sII hydrates, thus eliminating the need for a defect-free continuous interface between the sI and sII hydrates. Gas hydrate crystals were kept intact above their dissociation temperature by immersing them in liquid cyclopentane (CP), as observed with powder X-ray diffraction and X-ray CT methods. It was observed that placing the CH4 hydrate in CP converted the outer layer of CH4 hydrate to a thin layer of CP hydrate at around 270 K under atmospheric pressure, which is ∼80 K higher than the usual dissociation temperature. It was also observed that sI CO2 hydrate and C2H6 hydrate could be preserved by CP hydrate.

COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images.

Chest CT can display the main pathogenic factors of chronic obstructive pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to establish deep convolutional neural network (CNN) models using these two imaging markers to diagnose and grade COPD. Subjects who underwent chest CT and pulmonary function test (PFT) from one hospital (n = 373) were retrospectively included as the training cohort, and subjects from another hospital (n = 226) were used as the external test cohort. According to the PFT results, all subjects were labeled as Global Initiative for Chronic Obstructive Lung Disease (GOLD) Grade 1, 2, 3, 4 or normal. Two DenseNet-201 CNNs were trained using CT images of lung parenchyma and bronchial wall to generate two corresponding confidence levels to indicate the possibility of COPD, then combined with logistic regression analysis. Quantitative CT was used for comparison. In the test cohort, CNN achieved an area under the curve of 0.899 (95%CI: 0.853-0.935) to determine the existence of COPD, and an accuracy of 81.7% (76.2-86.7%), which was significantly higher than the accuracy 68.1% (61.6%-74.2%) using quantitative CT method (p < 0.05). For three-way (normal, GOLD 1-2, and GOLD 3-4) and five-way (normal, GOLD 1, 2, 3, and 4) classifications, CNN reached accuracies of 77.4 and 67.9%, respectively. CNN can identify emphysema and airway wall remodeling on CT images to infer lung function and determine the existence and severity of COPD. It provides an alternative way to detect COPD using the extensively available chest CT. CNN can identify the main pathological changes of COPD (emphysema and airway wall remodeling) based on CT images, to infer lung function and determine the existence and severity of COPD. CNN reached an area under the curve of 0.853 to determine the existence of COPD in the external test cohort. The CNN approach provides an alternative and effective way for early detection of COPD using extensively used chest CT, as an important alternative to pulmonary function test.

Abstract P1-08-30: Validation of the AAGAB gene as a novel on-treatment biomarker predicting pCR in patients receiving NACT for early breast cancer

Abstract Background: Neoadjuvant chemotherapy (NACT) for breast cancer is given prior to surgery, aiming to reduce tumour burden and provide early information on response to treatment. Tumours with a pathological complete response (pCR) following NACT are less likely to recur than those in patients with residual disease following NACT, suggesting that pCR following NACT may be a surrogate of good prognosis. In addition, NACT provides a “window of opportunity” where sequential sampling of a tumour enables observation of changes occurring in response to treatment. We previously demonstrated that on-treatment biomarkers improve the accuracy of predicting response before resection, by performing differential gene expression analysis across sequential samples from 50 patients, across 3 time points; pre NACT, mid chemo and post NACT (Bownes et al, 2019). A single gene marker (AAGAB) was identified as a novel potential on-treatment biomarker for pCR, with greater predictive accuracy than currently established prognostic tests, supporting the potential value of on-treatment biomarker monitoring in breast cancer to improve the accuracy of tumour response prediction. Aim: To validate and test the finding that increased expression of AAGAB at mid-chemotherapy associates with pCR in ER+ve and HER+ve breast cancer patients receiving NACT. Method: mRNA extracted from tumour from the mid-chemotherapy time point during NACT, from 28 breast cancer patients, was analysed using real-time reverse transcription-PCR (real-time RT-PCR). Firstly, mRNA was reverse transcribed using Invitrogen SuperScript IV Reverse Transcriptase (RT), then cDNA was used in an Applied Biosystems real-time RT-PCR Taqman Gene Expression Assay to measure AAGAB gene expression. GAPDH and SYMPK Taqman assays were used as endogenous controls, to allow calculation of (ΔΔCt) using the Comparative CT Method. Quantitative PCR was carried out on the Applied Biosystems StepOnePlusTM Real-Time PCR System and Relative Quantitation (RQ) was calculated using 2^-(ΔΔCt). For each patient RCB (residual cancer burden) was plotted against AAGAB expression and statistical significance calculated using the Wilcoxon rank sum exact test. Results: As a group, patients with RCB scores of 0 and I demonstrated a significantly higher level of expression that patients with RCB II and RCB III. We also observed that patients with pCR after NACT demonstrated higher levels of AAGAB expression. This increased expression was also seen in patients with a decrease in tumour cellularity of more than 85%. Conclusion: Our data suggest that measurement of AAGAB expression may provide an informative on-treatment biomarker of response to NACT. Citation Format: Fiona Semple, Alastair Ironside, Richard Bownes, Carlos Martinez-Perez, Natalie Wilson, Arran Turnbull, Olga Oikonomidou. Validation of the AAGAB gene as a novel on-treatment biomarker predicting pCR in patients receiving NACT for early breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-30.

Altered expression of NEAT1 variants and P53, PTEN, and BCL-2 genes in patients with acute myeloid leukemia

BackgroundNewly discovered evidence showed that long non-coding RNAs (lncRNAs) can play crucial roles in the development of cancer therapies. Nuclear Enriched Abundant Transcripts 1 (NEAT1) is one of the lncRNAs the expression of which changes in different cancers. The role of NEAT1 in apoptosis is discussed in various malignancies. This study aimed to determine the NEAT1 expression and its correlation with P53, PTEN, and BCL-2 genes expression in acute myeloid leukemia (AML) patients. MethodIn this study, using quantitative real-time polymerase chain reaction (qRT-PCR), we analyzed the expression of NEAT1, P53, PTEN, and BCL-2 genes in 21 AML patients. Moreover, relative quantification analysis was performed by delta-delta CT method (2 −ΔΔCT) method. ResultsOur results showed that NEAT1 expression was significantly lower in AML patients compared to healthy controls (P-value < 0.05). While a significant correlation was observed between the expression levels of NEAT1 and PTEN genes in AML patients (P-value < 0.05), there was no correlation between the expression levels of NEAT1 with P53 and BCL-2 (P-value > 0.05). ConclusionAccording to the results, increased expression of NEAT1 gene may play a role in the apoptosis of AML cells, despite the oncogenic role in most solid tumors.

Sertoli, Leydig, and Spermatogonial Cells' Specific Gene and Protein Expressions as Dog Testes Evolve from Immature into Mature States.

Simple SummarySertoli-, Leydig-, and spermatogonial-cells proliferate and differentiate from birth to puberty and then stay stable in adulthood. We hypothesized that expressions of spermatogenesis-associated genes are not enhanced with the increase of these cells’ numbers. To accomplish this postulation, we investigated the abundances of Sertoli cell-specific FSHR and AMH, Leydig cell-specific LHR and INSL3, and spermatogonia-specific THY1 and CDH1 markers in immature and mature canine testis. Four biological replicates of immature and mature testes were processed, and RT-PCR was performed to elucidate cells’ specific markers. Results showed that the gene expressions of all the studied cells’ specific markers were downregulated in adult testis compared with immature testis. Western blot and immunohistochemistry showed the presence of these proteins in the testis. Protein expressions of these markers were greater in immature compared with mature testis. The results support the postulation that the gene expressions do not directly correlate with the increase of the cell numbers during post-natal development but changes in gene expressions show functional significance.Sertoli, Leydig, and spermatogonial cells proliferate and differentiate from birth to puberty and then stay stable in adulthood. We hypothesized that expressions of spermatogenesis-associated genes are not enhanced with a mere increase of these cells’ numbers. To accept this postulation, we investigated the abundances of Sertoli cell-specific FSHR and AMH, Leydig cell-specific LHR and INSL3, and spermatogonia-specific THY1 and CDH1 markers in immature and mature canine testis. Four biological replicates of immature and mature testes were processed, and RT-PCR was performed to elucidate the cells’ specific markers. The data were analyzed by ANOVA, using the 2−∆∆Ct method to ascertain differences in mRNA expressions. In addition, Western blot and IHC were performed. Gene expressions of all the studied cells’ specific markers were down-regulated (p < 0.05) in adult testis compared with immature testis. Western blot and immunohistochemistry showed the presence of these proteins in the testis. Protein expressions were greater in immature testis compared with mature testis (p < 0.05). Despite the obvious expansion of these cells’ numbers from immature to adult testis, the cells’ specific markers were not enriched in mature testis compared with immature dog testis. The results support the postulation that the gene expressions do not directly correlate with the increase of the cell numbers during post-natal development but changes in gene expressions show functional significance.

MicroRNA Expression in Neonates with Late-onset Sepsis – A Cross-sectional Comparative Study

ABSTRACT Background Neonatal sepsis is a major health concern among neonates with higher morbidity and mortality rate. Studies have recently speculated the importance of differential expression of circulating mature micro-RNAs (miRNAs) which could serve as diagnostic as well as prognostic markers for risk of mortality in neonatal sepsis. This study aimed to analyze the expression pattern and to assess the diagnostic/prognostic value of miRNAs miR-21, miR-29a miR-31, miR-146a, and miR-155 in late-onset neonatal sepsis. Methods A cross-sectional comparative study was conducted including 42 healthy controls and 42 neonates with late-onset neonatal sepsis. SYBR green-based miScript RT-PCR assay was used for the expression analysis and the comparative Ct method 2-delta (Ct) method was used for relative quantification of the candidate miRNAs in plasma. Significantly higher expression of miR-21 and miR-155 and lower expression of miR-29a and miR-146a was observed in cases compared to control except miR-31. In subgroups analysis, miR-21(p = .03) showed a significant difference between pre-term and term neonates and miR-31 (p = .01) and miR-155 (p = .03) showed a significant difference between low-birth-weight and normal-birth-weight neonates. miR-146a showed significantly lower expression in the non-survivor group compared to the survivor group (p = .005). A receiver operating characteristic curve (ROC) analysis of miR-21 and miR-29a (0.829 and 0.787 AUC of ROC curves) showed good discrimination for the identification of sepsis from non-sepsis neonates. Conclusion The current study shows evidence of differential expression of miRNAs in neonatal sepsis and this altered expression of candidate miRNAs could be involved in immune dysregulation, thus leading to sepsis-related severity in newborns.

Identification and Validation of Reference Genes for Gene Expression Analysis in Different Development Stages of Amylostereum areolatum.

A strict relationship exists between the Sirex noctilio and the Amylostereum areolatum, which is carried and spread by its partner. The growth and development of this symbiotic fungus is key to complete the life history of the Sirex woodwasp. Real-time quantitative polymerase chain reaction (RT-qPCR) is used to measure gene expression in samples of A. areolatum at different growth stages and explore the key genes and pathways involved in the growth and development of this symbiotic fungus. To obtain accurate RT-qPCR data, target genes need to be normalized by reference genes that are stably expressed under specific experimental conditions. In our study, the stability of 10 candidate reference genes in symbiotic fungal samples at different growth and development stages was evaluated using geNorm, NormFinder, BestKeeper, delta Ct methods, and RefFinder. Meanwhile, laccase1 was used to validate the stability of the selected reference gene. Under the experimental conditions of this study, p450, CYP, and γ-TUB were identified as suitable reference genes. This work is the first to systematically evaluate the reference genes for RT-qPCR results normalization during the growth of this symbiotic fungus, which lays a foundation for further gene expression experiments and understanding the symbiotic relationship and mechanism between S. noctilio and A. areolatum.

Prospective Clinical Feasibility Study for MRI-Only Brain Radiotherapy.

ObjectivesMRI-only radiotherapy (RT) provides a workflow to decrease the geometric uncertainty introduced by the image registration process between MRI and CT data and to streamline the RT planning. Despite the recent availability of validated synthetic CT (sCT) methods for the head region, there are no clinical implementations reported for brain tumors. Based on a preceding validation study of sCT, this study aims to investigate MRI-only brain RT through a prospective clinical feasibility study with endpoints for dosimetry and patient setup.Material and MethodsTwenty-one glioma patients were included. MRI Dixon images were used to generate sCT images using a CE-marked deep learning-based software. RT treatment plans were generated based on MRI delineated anatomical structures and sCT for absorbed dose calculations. CT scans were acquired but strictly used for sCT quality assurance (QA). Prospective QA was performed prior to MRI-only treatment approval, comparing sCT and CT image characteristics and calculated dose distributions. Additional retrospective analysis of patient positioning and dose distribution gamma evaluation was performed.ResultsTwenty out of 21 patients were treated using the MRI-only workflow. A single patient was excluded due to an MRI artifact caused by a hemostatic substance injected near the target during surgery preceding radiotherapy. All other patients fulfilled the acceptance criteria. Dose deviations in target were within ±1% for all patients in the prospective analysis. Retrospective analysis yielded gamma pass rates (2%, 2 mm) above 99%. Patient positioning using CBCT images was within ± 1 mm for registrations with sCT compared to CT.ConclusionWe report a successful clinical study of MRI-only brain radiotherapy, conducted using both prospective and retrospective analysis. Synthetic CT images generated using the CE-marked deep learning-based software were clinically robust based on endpoints for dosimetry and patient positioning.

КОМП’ЮТЕРНА ТОМОГРАФІЧНА ДЕНСИТОМЕТРІЯ ЛЕГЕНЬ В АЛГОРИТМІ ДІАГНОСТИКИ ІНТЕРСТИЦІАЛЬНИХ ЗАХВОРЮВАНЬ ЛЕГЕНЬ, В ТОМУ ЧИСЛІ ПРОФЕСІЙНОЇ ЕТІОЛОГІЇ ТА ЕКОЛОГІЧНО ОБУМОВЛЕНИХ

DENSITOMETRY OF THE LUNGS IN THE ALGORITHM FOR THE DIAGNOSIS OF INTERSTITIAL LUNG DISEASES, INCLUDING OCCUPATIONAL AND ECOLOGICAL DISEASES A. V. Basanets, N. V. Kurdil Abstract Interstitial lung diseases are among the most common diseases of the respiratory system. A significant proportion of them are occupational diseases with pneumoconiosis as the most prevalent condition. Determination of lung density by computed densitometry (CD) allows to quantify the degree of density of lung tissue in a different lung diseases. This review focuses on world and domestic literature on the application of CD for the diagnosis and monitoring of management of interstitial lung diseases such as pulmonary sarcoidosis, pulmonary tuberculosis, idiopathic pulmonary fibrosis, pulmonary embolism, systemic sclerosis, pneumoconiosis, etc. The method of determining of lung density index, its effectiveness depending on the method of CT and the algorithm of examination of the patients are described. Peculiarities of changes in lung density index depending on the form and pathogenesis of the disease, its correlation with lung function and morphological changes have been analyzed. The most reproducible and perfect indicators of CD are those determined by inspiratory CT, which should be taken into account in the further improvement of research protocols. The standardization of the CT imaging protocol should be implemented taking into account the need for possible reduction of the radiation dose. Conclusions. The technique of CD is recognized as a revolutionary diagnostic tool for quantifying the density of the lung parenchyma, which can be effectively used to diagnose and verify the diagnosis of interstitial lung diseases, including occupational diseases. Improving methods of occupational and environmental interstitial lung diseases diagnosing, preventing their progression and development of complications will improve the quality of healthcare service for workers, decrease morbidity, reduce treatment and disability reimbursement costs. Key words: interstitial lung diseases, occupational diseases, computed lung densitometry, computed tomography

Differential Expression of SLC25A38 Gene in Patients of Acute Lymphoblastic Leukaemia

Introduction: The SLC25A38 gene produces protein that belongs to the mitochondrial solute carrier family, SLC25. It is implicated in apoptotic pathways, which regulate intrinsic caspase-dependent apoptosis. Aim: To determine level of expression of SLC25A38 gene in patients of Acute Lymphoblastic Leukaemia (ALL). Materials and Methods: A cross-sectional study was done in the Department of Biochemistry, Indira Gandhi Institute of Medical Sciences, Patna, Bihar, India, from April 2019 to March 2020. The study included 30 leukaemia patients out of which 25 were adult males and five were adult females and 10 healthy volunteers were included as the control group. Level of expression of SLC25A38 gene normalised to Glyceraldehyde 3-phosphate Dehydrogenase (GAPDH) gene relative to normal healthy volunteers among the ALL patients was measured using quantitative real time polymerase chain reaction. All data collected were analysed using Statistical Package for the Social Sciences (SPSS) version 16.0 software. Results: An average of 5.3 fold expression of SLC25A38 gene normalised to GAPDH relative to normal healthy volunteer among the ALL patients was seen. The fold of expression was determined by 2-∆∆Ct method. There was a positive correlation between blast cell abundance and level of SLC25A38 gene expression (Pearson’s r=0.408, p=0.025). The expression level was found to be associated with the proportion of blast cells in the bone marrow. Conclusion: High expression of SLC25A38 gene is a common feature in ALL and may be a novel biomarker for prognosis and diagnosis, as well as a potential therapeutic target for ALL.

Photon-Counting CT Reconstruction With a Learned Forward Operator

Photon-Counting CT is an emerging imaging technology that promises higher spatial resolution and the possibility for material decomposition in the reconstruction. A major difficulty in Photon-Counting CT is to efficiently model cross-talk between detectors. In this work, we accelerate image reconstruction tasks for Photon-Counting CT by modelling the cross-talk with an appropriately trained deep convolutional neural network. The main result relates to proving convergence when using such a learned cross-talk model in the context of second-order optimisation methods for spectral CT. Another is to evaluate the method through numerical experiments on small-scale CT acquisitions generated using a realistic physics model. Using the reconstruction with a full cross-talk model as ground truth, the learned cross-talk model results in a 20&#x00A0;dB increase in peak-signal-to noise ratio compared to ignoring cross-talk altogether. At the same time, it effectively cuts the computation time of the full cross-talk model in half. Furthermore, the learned cross-talk model generalises well to both unseen data and unseen detector settings. Our results indicate that such a partially learned forward operator is a suitable way of modelling data generation in Photon-Counting CT with a computational benefit that becomes more noticeable for realistic problem sizes.

Tooth and Pulp Chamber Automatic Segmentation with Artificial Intelligence Network and Morphometry Method in Cone-beam CT

This study aims to extract teeth and alveolar bone structures in CBCT images automatically, which is a key step in CBCT image analysis in the field of stomatology. In this study, semantic segmentation was used for automatic segmentation. Five marked classes of CBCT images were input for U-net neural network training. Tooth hard tissue (including enamel, dentin, and cementum), dental pulp cavity, cortical bone, cancellous bone, and other tissues were marked manually in each class. The output data were from different regions of interest. The network configuration and training parameters were optimized and adjusted according to the prediction effect. This method can be used to segment teeth and peripheral bone structures using CBCT. The time of the automatic segmentation process for each CBCT was less than 13 min. The Dice of the evaluation reference image was 98 %. The U-net model combined with the watershed method can effectively segment the teeth, pulp cavity, and cortical bone in CBCT images. It can provide morphological information for clinical treatment.

Development of Dynamic X-ray CT for Evaluation of dynamic deformation behavior of rubber

To understand the mechanical properties of polymeric materials such as rubber, it is useful to observe the internal deformation state that occurs during deformation. Therefore, the purpose of this study is to establish a dynamic X-ray CT method for specimens under tensile amplitude, and to establish a method to directly evaluate the deformation behavior inside materials under dynamic conditions. Dynamic X-ray CT using the proposed method has successfully produced images that are sufficient to observe internal structures. The deformation behavior was evaluated as local strain amplitude. The results showed that the distribution curve of the local strain amplitude changed depending on the mixture conditions, and that the peak of the distribution curve of the local strain amplitude decreased and the distribution became wider as the fine particles were compounded.