Longitudinal microcomputed tomography detects onset and progression of pulmonary fibrosis in conditional deficient mice.

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease, which is usually diagnosed late in advanced stages. Little is known about the subclinical development of IPF. We previously generated a mouse model with conditional deficiency () that develops IPF-like lung disease.

The influence of contrast media on calcium-based imaging of the spine in dual-layer CT.

This study aimed to evaluate the impact of contrast media application on CT attenuation of the bone using a novel calcium-only imaging technique (VCa) from dual-layer spectral detector CT (DLCT), which enables CT-based bone mineral density measurement unimpeded by soft tissue components. For this, true non-contrast (TNC) and venous phase images (VP) of n = 97 patients were acquired. CT attenuation of the first lumbar vertebra (L1) was measured in TNC-VCa, VP-VCa, and in virtual non-contrast images (VNC).

Calcium-Based Imaging of the Spine at Dual-Layer CT and Evaluation of Vertebral Fractures in Multiple Myeloma.

Purpose: To evaluate the prediction of vertebral fractures in plasma cell dyscrasias using dual-layer CT (DLCT) with quantitative assessment of conventional CT image data (CI), calcium suppressed image data (CaSupp), and calculation of virtual calcium-only (VCa) image data.

Material And Methods: Patients ( = 81) with the diagnosis of a plasma cell dyscrasia and whole-body DLCT at the time of diagnosis and follow-up were retrospectively enrolled. CI, CaSupp25, and CaSupp100 were quantitatively analyzed using regions of interest in the lumbar vertebral bodies and fractured vertebral bodies on baseline or follow-up imaging.

Improvement of Breast Cancer Detection Using Dual-Layer Spectral CT.

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass.

Quantitative calcium-based assessment of osteoporosis in dual-layer spectral CT.

Objectives: To evaluate a novel calcium-only imaging technique (VCa) with subtracted bone marrow in osteoporosis in dual-layer CT (DLCT) compared to conventional CT images (CI) and dual-energy X-ray absorptiometry (DXA).

Material And Methods: Images of a multi-energy CT phantom with calcium inserts, quantitative CT calibration phantom, and of 55 patients (mean age: 64.6 ± 11.

Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.).

A Bayesian linkage disequilibrium-based multiple-locus mixed model identified QTLs for fibre, seed and oil traits and predicted breeding worthiness of test lines, enabling their simultaneous improvement in cotton. Improving cotton seed and oil yields has become increasingly important while continuing to breed for higher lint yield. In this study, a novel Bayesian linkage disequilibrium-based multiple-locus mixed model was developed for QTL identification and genomic prediction (GP).

Multiscale and multimodal imaging for three-dimensional vascular and histomorphological organ structure analysis of the pancreas.

Exocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas.

HairNet2: deep learning to quantify cotton leaf hairiness, a complex genetic and environmental trait.

Background: Cotton accounts for 80% of the global natural fibre production. Its leaf hairiness affects insect resistance, fibre yield, and economic value. However, this phenotype is still qualitatively assessed by visually attributing a Genotype Hairiness Score (GHS) to a leaf/plant, or by using the HairNet deep-learning model which also outputs a GHS.

Genetic Mapping and Characterization of Verticillium Wilt Resistance in a Recombinant Inbred Population of Upland Cotton.

Verticillium wilt (VW) is an important and widespread disease of cotton and once established is long-lived and difficult to manage. In Australia, the non-defoliating pathotype of is the most common, and extremely virulent. Breeding cotton varieties with increased VW resistance is the most economical and effective method of controlling this disease and is greatly aided by understanding the genetics of resistance.

Spectral performance evaluation of a second-generation spectral detector CT.

Purpose: The aim of this study was to characterize a second-generation wide-detector dual-layer spectral computed tomography (CT) system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities.

Methods: A phantom with multiple tissue-mimicking and material-specific inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated.

Dissecting the major genetic components underlying cotton lint development.

Numerous genetic loci and several functionally characterized genes have been linked to determination of lint percentage (lint%), one of the most important cotton yield components, but we still know little about the major genetic components underlying lint%. Here, we first linked the genetic loci containing MYB25-like_At and HD1_At to the fiberless seed trait of 'SL1-7-1' and found that MYB25-like_At and HD1_At were very lowly expressed in 'SL1-7-1' ovules during fiber initiation. We then dissected the genetic components involved in determination of lint% using segregating populations derived from crosses of fuzzless mutants and intermediate segregants with different lint%, which not only confirmed the HD1_At locus but identified the HD1_Dt locus as being the major genetic components contributing to fiber initiation and lint%.

Metal Artifact Reduction in Photon-Counting Detector CT: Quantitative Evaluation of Artifact Reduction Techniques.

Objectives: With the introduction of clinical photon-counting detector computed tomography (PCD-CT) and its novel reconstruction techniques, a quantitative investigation of different acquisition and reconstruction settings is necessary to optimize clinical acquisition protocols for metal artifact reduction.

Materials And Methods: A multienergy phantom was scanned on a clinical dual-source PCD-CT (NAEOTOM Alpha; Siemens Healthcare GmbH) with 4 different central inserts: water-equivalent plastic, aluminum, steel, and titanium. Acquisitions were performed at 120 kVp and 140 kVp (CTDI vol 10 mGy) and reconstructed as virtual monoenergetic images (VMIs; 110-150 keV), as T3D, and with the standard reconstruction "none" (70 keV VMI) using different reconstruction kernels (Br36, Br56) and with as well as without iterative metal artifact reduction (iMAR).

Pancreatic CT perfusion: quantitative meta-analysis of disease discrimination, protocol development, and effect of CT parameters.

Background: This study provides a quantitative meta-analysis of pancreatic CT perfusion studies, investigating choice of study parameters, ability for quantitative discrimination of pancreatic diseases, and influence of acquisition and reconstruction parameters on reported results.

Methods: Based on a PubMed search with key terms 'pancreas' or 'pancreatic,' 'dynamic' or 'perfusion,' and 'computed tomography' or 'CT,' 491 articles published between 1982 and 2020 were screened for inclusion in the study. Inclusion criteria were: reported original data, human subjects, five or more datasets, measurements of pancreas or pancreatic pathologies, and reported quantitative perfusion parameters.

Evaluation and timing optimization of CT perfusion first pass analysis in comparison to maximum slope model in pancreatic adenocarcinoma.

For implementation, performance evaluation and timing optimization of CT perfusion first pass analysis (FPA) by correlation with maximum slope model (MSM) in pancreatic adenocarcinoma, dynamic CT perfusion acquisitions of 34 time-points were performed in 16 pancreatic adenocarcinoma patients. Regions of interest were marked in both parenchyma and carcinoma. FPA, a low radiation exposure CT perfusion technique, was implemented.

Evaluation of optimal acquisition delays of DECT iodine maps in pancreatic adenocarcinoma: A potential alternative to the Patlak model of CT perfusion.

Introduction: By using bolus tracking with an appropriate acquisition delay dual-energy computed tomography (DECT) iodine maps might serve as a replacement of CT perfusion maps at reduced radiation exposure. This study aimed to evaluate the optimal acquisition delays of DECT for the replacement of parameter maps calculated with the Patlak model in pancreatic adenocarcinoma by corresponding iodine maps.

Materials And Methods: Dual-source dynamic DECT acquisitions at 80 kV/Sn140 kV of 14 patients with pancreatic carcinoma were used to calculate CT perfusion maps of blood volume and permeability with the Patlak model.

Dual-energy CT-based stopping power prediction for dental materials in particle therapy.

Radiotherapy with protons or light ions can offer accurate and precise treatment delivery. Accurate knowledge of the stopping power ratio (SPR) distribution of the tissues in the patient is crucial for improving dose prediction in patients during planning. However, materials of uncertain stoichiometric composition such as dental implant and restoration materials can substantially impair particle therapy treatment planning due to related SPR prediction uncertainties.

Quantification of airway wall contrast enhancement on virtual monoenergetic images from spectral computed tomography.

Objectives: Quantitative computed tomography (CT) plays an increasingly important role in phenotyping airway diseases. Lung parenchyma and airway inflammation could be quantified by contrast enhancement at CT, but its investigation by multiphasic examinations is limited. We aimed to quantify lung parenchyma and airway wall attenuation in a single contrast-enhanced spectral detector CT acquisition.

Asynchronous calibration of quantitative computed tomography bone mineral density assessment for opportunistic osteoporosis screening: phantom-based validation and parameter influence evaluation.

Asynchronous calibration could allow opportunistic screening based on routine CT for early osteoporosis detection. In this phantom study, a bone mineral density (BMD) calibration phantom and multi-energy CT (MECT) phantom were imaged on eight different CT scanners with multiple tube voltages (80-150 kV) and image reconstruction settings (e.g.

The Past, Present, and Future of Host Plant Resistance in Cotton: An Australian Perspective.

Cotton is a key global fiber crop. However, yield potential is limited by the presence of endemic and introduced pests and diseases. The introduction of host plant resistance (HPR), defined as the purposeful use of resistant crop cultivars to reduce the impact of pests and diseases, has been a key breeding target for the Commonwealth Scientific and Industrial Research Organisation (CSIRO) cotton breeding program.

Ultrahigh resolution whole body photon counting computed tomography as a novel versatile tool for translational research from mouse to man.

X-ray computed tomography (CT) is a cardinal tool in clinical practice. It provides cross-sectional images within seconds. The recent introduction of clinical photon-counting CT allowed for an increase in spatial resolution by more than a factor of two resulting in a pixel size in the center of rotation of about 150 µm.

Cotton Breeding in Australia: Meeting the Challenges of the 21st Century.

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) cotton breeding program is the sole breeding effort for cotton in Australia, developing high performing cultivars for the local industry which is worth∼AU$3 billion per annum. The program is supported by Cotton Breeding Australia, a Joint Venture between CSIRO and the program's commercial partner, Cotton Seed Distributors Ltd. (CSD).

Core Collections: Is There Any Value for Cotton Breeding?

Global plant breeding activities are reliant on the available genetic variation held in extant varieties and germplasm collections. Throughout the mid- to late 1900s, germplasm collecting efforts were prioritized for breeding programs to archive precious material before it disappeared and led to the development of the numerous large germplasm resources now available in different countries. In recent decades, however, the maintenance and particularly the expansion of these germplasm resources have come under threat, and there has been a significant decline in investment in further collecting expeditions, an increase in global biosecurity restrictions, and restrictions placed on the open exchange of some commercial germplasm between breeders.

Potential of a Second-Generation Dual-Layer Spectral CT for Dose Calculation in Particle Therapy Treatment Planning.

In particle therapy treatment planning, dose calculation is conducted using patient-specific maps of tissue ion stopping power ratio (SPR) to predict beam ranges. Improving patient-specific SPR prediction is therefore essential for accurate dose calculation. In this study, we investigated the use of the Spectral CT 7500, a second-generation dual-layer spectral computed tomography (DLCT) system, as an alternative to conventional single-energy CT (SECT) for patient-specific SPR prediction.

Genomic prediction of cotton fibre quality and yield traits using Bayesian regression methods.

Genomic selection or genomic prediction (GP) has increasingly become an important molecular breeding technology for crop improvement. GP aims to utilise genome-wide marker data to predict genomic breeding value for traits of economic importance. Though GP studies have been widely conducted in various crop species such as wheat and maize, its application in cotton, an essential renewable textile fibre crop, is still significantly underdeveloped.