Climate toxicity: An increasingly relevant clinical issue in Cancer Care

Energy consumption in MRI: Determinants and management options

BACKGROUND

Energy consumption awareness is a known concern, and radiology departments have energy-intensive consuming machines. The means of energy consumption management in MRI scanners have yet to be evaluated.

PURPOSE

To measure the MRI energy consumption and to evaluate the means to reduce it.

MATERIALS AND METHODS

Data was retrieved for two MRI scanners through the hospital's automated energy consumption measurement software. After correlation with picture archiving and communication system (PACS) files, they were segmented by machine and mode (as follows: stand-by, idle and active) and analyzed. Active mode data for a specific brain MRI protocol have been isolated, and equivalent low energy consuming protocol was made. Both were performed on phantom and compared. Same protocol was performed on a phantom using 3.0T 16 and 32 head channels coils. Multiples sequences were acquired on phantom to evaluate power consumption.

RESULTS

Stand-by mode accounted for 60 % of machine time and 40 % of energy consumption, active mode accounted for 20 % machine time and 40 % energy consumption, idle mode for 20 % imachine time and 20 % consumption. DWI and TOF sequences were the most consuming in our brain-MRI protocol. The low energy consuming protocol allowed a saving of approximately 10 % of energy consumption, which amounted for 0.20€ for each examination. This difference was mainly due to an energy consumption reduction of the DWI sequence. There were no difference in consumption between a 3.0T 16 and 32 channels head coils. Sequence's active power and duration (especially considering slice thickness) have to be taken into account when trying to optimize energy consumption.

CONCLUSION

There are two key factors to consider when trying to reduce MRI scan energy consumption. Stand-by mode energy consumption has to be taken into account when choosing an MRI scan, as it can't be changed further on. Active mode energy consumption is dependent of the MRI protocols used, and can be reduced with sequences adaptation, which must take into account sequence's active power and duration, on top of image quality.

Ambient temperature modulates body weight changes in patients with advanced oncological diseases and anorexia cachexia syndrome

OBJECTIVE

To assess the impact of ambient temperature (AT) on the evolution of bodyweight in patients with heterogeneous types of cancer in advanced stages of the disease (stages III and IV) and anorexia- cachexia syndrome (ACS).

METHODS

A prospective naturalistic multicenter study of patients undergoing oncological treatment at four hospitals during a three-year period (2017-2020) in the Autonomous Community of Extremadura in southwestern Spain with a continentalized Mediterranean climate of mild and relatively rainy winters, and particularly hot and sunny summers. Bodyweight changes were obtained from the medical records of 84 oncological patients (59 men and 25 women, age range 37-91 yrs). Mean monthly AT was used to examine the association of weight changes across cold and warm bimesters -BIMs (December and January, vs. July and August), Trimesters -TRIMs (July to September vs. December to February), and Semesters -SEMs (May to October vs. November to April). Weight changes between two consecutive weight measures were categorized as weight gain, weight loss, or no weight change. Differences across cold and warm seasons were analysed using parametric (ANOVA), and nonparametric statistics (Chi-square and binomial z tests). An alpha-rate of 0.05 was used for all analyses.

RESULTS

A weight loss trend was observed during BIMs cold periods in comparison to warm ones (p 0.04). However, differences in average bodyweight were not significant. The negative impact of cold periods was more marked in men than in women, (p = 0.05; p = 0.03, for cold vs. warm BIMs and TRIMs, respectively). In contrast, significantly higher weight gain percentages were found in women during warm TRIMs and SEMs (p = 0.03, and p = 0.01, respectively). As for the number of patients dying during the study (N = 56; 39 men, 17 women), there were a significant interaction between temperature (cold/warm), and mean weight F (1, 499) = 6.06, p = 0.01, which revealed a pattern of weight loss in the cold semester as opposed to weight gain during the warm SEM months.

CONCLUSIONS

AT temperature modulated body weight changes in patients with advanced oncological disease and ACS. Two main limitations of the study were the absence of information on diets as a moderating factor of weight loss/gain, and the lack of the patients' weight measurements closest to the date of diagnosis prior to admittance to the study. As for the practical implications, it remains to be seen whether an adjunctive heat supply will serve a buffering effect on weight loss during colder seasons for patients with advanced cancer and ACS.