Dual-Split CT to Simulate Multiple Radiation Doses From a Single Scan-Liver Lesion Detection Compared With Dose-Matched Single-Energy CT.

OBJECTIVES: The aim of this study was to evaluate the potential use of simulated radiation doses from a dual-split CT scan for dose optimization by comparing their lesion detectability to dose-matched single-energy CT acquisitions at different radiation dose levels using a mathematical model observer. MATERIALS AND METHODS: An anthropomorphic abdominal phantom with liver lesions (5-10 mm, both hyperattenuating and hypoattenuating) was imaged using a third-generation dual-source CT in single-energy dual-source mode at 100 kVp and 3 radiation doses (5, 2.5, 1.25 mGy). The tube current was 67% for tube A and 33% for tube B. For each dose, 5 simulated radiation doses (100%, 67%, 55%, 45%, 39%, and 33%) were generated through linear image blending. The phantom was also imaged using traditional single-source single-energy mode at equivalent doses. Each setup was repeated 10 times. Image noise texture was evaluated by the average spatial frequency (fav) of the noise power spectrum. Liver lesion detection was measured by the area under the receiver operating curve (AUC), using a channelized Hotelling model observer with 10 dense Gaussian channels. RESULTS: Fav decreased at lower radiation doses and differed between simulated and single-energy images (eg, 0.16 mm-1 vs 0.14 mm-1 for simulated and single-energy images at 1.25 mGy), indicating slightly blotchier noise texture for dual-split CT. For hyperattenuating lesions, the mean AUC ranged between 0.92-0.99, 0.81-0.96, and 0.68-0.89 for single-energy, and between 0.91-0.99, 0.78-0.91, and 0.70-0.85 for dual-split at 5 mGy, 2.5 mGy, and 1.25 mGy, respectively. For hypoattenuating lesions, the AUC ranged between 0.90-0.98, 0.75-0.93, and 0.69-0.86 for the single-energy, and between 0.92-0.99, 0.76-0.87, and 0.67-0.81 for dual-split at 5 mGy, 2.5 mGy, and 1.25 mGy, respectively. AUC values were similar between both modes at 5 mGy, and slightly lower, albeit not significantly, for the dual-split mode at 2.5 and 1.25 mGy. CONCLUSIONS: Lesion detectability was comparable between multiple simulated radiation doses from a dual-split CT scan and dose-matched single-energy CT. Noise texture was slightly blotchier in the simulated images. Simulated doses using dual-split CT can be used to assess the impact of radiation dose reduction on lesion detectability without the need for repeated patient scans.

Improvement of N and P ratio for enhanced biomass productivity and sustainable cultivation of Chlorella vulgaris microalgae.

Microalgae cultivation could contribute to the achievement of several sustainable development goals (SDGs). However, cultivating Chlorella vulgaris, like any other microalgae, is challenging due to various biotic, abiotic and process related factors that can affect its growth and biomass productivity. Nutrient availability, particularly N and P, and their ratio play a crucial role in building cellular structures and maintaining metabolic processes, determining basically the maximum achievable biomass productivity under given circumstances. The present article aims to improve the N and P ratio to enhance the biomass productivity of Chlorella vulgaris microalgae as well as to characterize the biomass growth kinetics that can be used for prediction purposes. The results showed that the nutrient solutions prepared with increased nitrate concentration (T1 - N:P = 55:1 and T3 - N:P = 28:1) promoted chlorophyll formation and significantly outperformed the control sample (BG-11 - N:P = 35:1) with 192% and 183%, leading to higher biomass productivity with 1160 µg L-1 and 1103 µg L-1, respectively. Moreover, a strong positive correlation was revealed (0.81) between phosphate concentration and microalgae activity rate, indicating the role of phosphorous in energy transfer, resulted in stimulated microalgae activity rates with 71.2% and 70.66% in the phosphate-increased nutrient solutions (T2 - N:P = 14:1 and T3 - N:P = 28:1). In addition, an exponential equation was introduced to characterize the biomass growth kinetics, of which the theoretically achievable maximum chlorophyll concentration (CTAM) and the theoretical cultivation time (tcultivation) were determined for the tested nutrient solutions with variable N:P ratio. It was concluded, that the higher the N:P ratio, the higher the CTAM is, nevertheless the absolute concentration of these nutrients need to be considered as well. The introduced two key parameters could provide valuable information for decision makers regarding the optimization of growth conditions, nutrient supplementation, and harvesting, additionally decreasing the production costs and making the cultivation cycles more effective and sustainable.

Ability of ChatGPT to generate competent radiology reports for distal radius fracture by use of RSNA template items and integrated AO classifier.

The amount of acquired radiology imaging studies grows worldwide at a rapid pace. Novel information technology tools for radiologists promise an increase of reporting quality and as well quantity at the same time. Automated text report drafting is one branch of this development. We defined for the present study in total 9 cases of distal radius fracture. Command files structured according to a template of the Radiological Society of North America (RSNA) and to Arbeitsgemeinschaft Osteosynthese (AO) classifiers were given as input to the natural language processing tool ChatGPT. ChatGPT was tasked with drafting an appropriate radiology report. A parameter study (n = 5 iterations) was performed. An overall high appraisal of ChatGPT radiology report quality was obtained in a score card based assessment. ChatGPT demonstrates the capability to adjust output files in response to minor changes in input command files. Existing shortcomings were found in technical terminology and medical interpretation of findings. Text drafting tools might well support work of radiologists in the future. They would allow a radiologist to focus time on the observation of image details and patient pathology. ChatGPT can be considered a substantial step forward towards that aim.

Assessing Perfusion in Steno-Occlusive Cerebrovascular Disease Using Transient Hypoxia-Induced Deoxyhemoglobin as a Dynamic Susceptibility Contrast Agent.

BACKGROUND AND PURPOSE: Resting brain tissue perfusion in cerebral steno-occlusive vascular disease can be assessed by MR imaging using gadolinium-based susceptibility contrast agents. Recently, transient hypoxia-induced deoxyhemoglobin has been investigated as a noninvasive MR imaging contrast agent. Here we present a comparison of resting perfusion metrics using transient hypoxia-induced deoxyhemoglobin and gadolinium-based contrast agents in patients with known cerebrovascular steno-occlusive disease. MATERIALS AND METHODS: Twelve patients with steno-occlusive disease underwent DSC MR imaging using a standard bolus of gadolinium-based contrast agent compared with transient hypoxia-induced deoxyhemoglobin generated in the lungs using an automated gas blender. A conventional multi-slice 2D gradient echo sequence was used to acquire the perfusion data and analyzed using a standard tracer kinetic model. MTT, relative CBF, and relative CBV maps were generated and compared between contrast agents. RESULTS: The spatial distributions of the perfusion metrics generated with both contrast agents were consistent. Perfusion metrics in GM and WM were not statistically different except for WM MTT. CONCLUSIONS: Cerebral perfusion metrics generated with noninvasive transient hypoxia-induced changes in deoxyhemoglobin are very similar to those generated using a gadolinium-based contrast agent in patients with cerebrovascular steno-occlusive disease.