Brachytherapy: An emblematic example of extreme hypofractionated regimen

In order to provide more convenient irradiation regimens for patient comfort, radiation facility organization and health expenses, new hypofractionated protocols have been evaluated. Moderately (dose/fraction: 2.3 to 3 Gy), then ultra (dose/fraction: 5.2 to 6.1 Gy) hypofractionated irradiations were first validated. The current question is: is it possible to go forward using extreme hypofractionated regimens (EHR) based on 1 to 3 fractions. Different irradiation techniques are under investigation. However, brachytherapy remains the smartest way to deliver a high dose in a small volume. We report prospective and retrospective study results which evaluated EHR for breast and prostate brachytherapy. While oncological outcome and toxicity profile appear extremely encouraging for low-risk breast cancer after a 1 to 4 fractions (6.25 to 20 Gy/fraction), the use of a single fraction of 19 to 23 Gy appears debatable for prostate cancer. Brachytherapy represents an emblematic example of EHR but longer follow-up and more mature results are awaited in order to specify the right indications and refine the EQD2 calculation method including new biological and technical factors.     

Enlarged high frequency oscillations of the median nerve somatosensory evoked potential and survival in amyotrophic lateral sclerosis

ObjectiveA large N20 and P25 of the median nerve somatosensory evoked potential (SEP) predicts short survival in amyotrophic lateral sclerosis (ALS). We investigated whether high frequency oscillations (HFOs) over N20 are enlarged and associated with survival in ALS.MethodsA total of 145 patients with ALS and 57 healthy subjects were studied. We recorded the median nerve SEP and measured the onset-to-peak amplitude of N20 (N20o-p), and peak-to-peak amplitude between N20 and P25 (N20p-P25p). We obtained early and late HFO potentials by filtering SEP between 500 and 1 kHz, and measured the peak-to-peak amplitude. We followed up patients until endpoints (death or tracheostomy) and analyzed the relationship between SEP or HFO amplitudes and survival using a Cox analysis.ResultsPatients showed larger N20o-p, N20p-P25p, and early and late HFO amplitudes than the control values. N20p-P25p was associated with survival periods (p = 0.0004), while early and late HFO amplitudes showed no significant association with survival (p = 0.4307, and p = 0.6858, respectively).ConclusionsThe HFO amplitude in ALS is increased, but does not predict survival.SignificanceThe enlarged HFOs in ALS might be a compensatory phenomenon to the hyperexcitability of the sensory cortex pyramidal neurons.     

李延应用泽泻汤合温胆汤治疗舒张压高的临床经验

随着社会的发展,人类生活方式的改变,高血压病越来越高发,具有低龄化趋势,代谢综合征常伴随发生,此种情况下的高血压往往是以舒张压升高为主,临床表现常与“亚健康”状态混淆,未能引起患者甚至部分医生的重视,然而事实上越来越多的科学研究证实舒张压高之危害十分明显,不容忽视。尽管现代医学对舒张压高的病因及病理机制有明确的阐述,但是暂时没有特效的药物。李延教授在治疗高血压病方面有着丰富的临床经验,临床中运用泽泻汤合温胆汤加减治疗舒张压高之眩晕,切中病机,加减灵活,屡有良效。文中从中医角度阐述舒张压高的病因病机,介绍李师辨病辨证思路,组方用药特点,附三则典型验案,另加个人心得体会,以期为舒张压高的有效治疗提供思路。     

Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review

Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre- and post-intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV-based interventions reduced the amount of moderate- and/or high-intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV-based training. Peak oxygen uptake () and submaximal running parameters (eg, LT1, LT2) improved following both HRV-based and predefined training, with no clear difference in the extent of improvement in . Submaximal running parameters tended to improve more following HRV-based training. Research findings to date have been limited and inconsistent. Both HRV-based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater.     

Improving Surgical Training

Improving Surgical Training is a programme piloting an innovative, evidence-based approach to training. It was developed in response to the Shape of Training report which reviewed postgraduate training and recommended changes in medical education to meet the demands of the modern NHS. A series of initiatives have been developed to enhance the experience for surgical trainees not only to encourage a more focussed and supported method, but also to improve their job satisfaction. The initiatives have combined a greater emphasis on time for training provided by trainers with allocated time for training with multidisciplinary teamworking and the use of technology enhanced learning with simulation of both technical and non-technical skills. The pilot started in 2018 with core training in general surgery and has been expanded to include vascular surgery, urology and trauma and orthopaedics over the last 2 years. Initial feedback from both trainees, trainers and schools of surgery have identified different challenges to aid implementation. The programme is being very carefully evaluated by an independent company as well as careful oversight by the General Medical Council which are paramount to its success.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.