Properties of the receptive fields of simple cells in macaque cortex were compared with properties of independent component filters generated by independent component analysis (ICA) on a large set of natural images. Histograms of spatial frequency bandwidth, orientation tuning bandwidth, aspect ratio and length of the receptive fields match well. This indicates that simple cells are well tuned to the expected statistics of natural stimuli. There is no match, however, in calculated and measured distributions for the peak of the spatial frequency response: the filters produced by ICA do not vary their spatial scale as much as simple cells do, but are fixed to scales close to the finest ones allowed by the sampling lattice. Possible ways to resolve this discrepancy are discussed.

Purpose: A relationship between mean heart dose (MHD) and acute coronary event (ACE) rate was reported in a study of patients with breast cancer (BC). The main objective of our cohort study was to validate this relationship and investigate if other dose-distribution parameters are better predictors for ACEs than MHD. Patients and Methods: The cohort consisted of 910 consecutive female patients with BC treated with radiotherapy (RT) after breast-conserving surgery. The primary end point was cumulative incidence of ACEs within 9 years of follow-up. Both MHD and various dose-distribution parameters of the cardiac substructures were collected from three-dimensional computed tomography planning data. Results: The median MHD was 2.37 Gy (range, 0.51 to 15.25 Gy). The median follow-up time was 7.6 years (range, 0.1 to 10.1 years), during which 30 patients experienced an ACE. The cumulative incidence of ACE increased by 16.5% per Gy (95% CI, 0.6 to 35.0; P = .042). Analysis showed that the volume of the left ventricle receiving 5 Gy (LV-V5) was the most important prognostic dose-volume parameter. The most optimal multivariable normal tissue complication probability model for ACEs consisted of LV-V5, age, and weighted ACE risk score per patient (c-statistic, 0.83; 95% CI, 0.75 to 0.91). Conclusion: A significant dose-effect relationship was found for ACEs within 9 years after RT. Using MHD, the relative increase per Gy was similar to that reported in the previous study. In addition, LV-V5 seemed to be a better predictor for ACEs than MHD. This study confirms the importance of reducing exposure of the heart to radiation to avoid excess risk of ACEs after radiotherapy for BC.

Avoiding irradiation of the region of the parotid gland containing stem cells reduces the risk of xerostomia (dry mouth).

A comprehensive individual toxicity risk profile is needed to improve radiation treatment optimisation, minimising toxicity burden, in head and neck cancer (HNC) patients. We aimed to develop and externally validate NTCP models for various toxicities at multiple time points. Using logistic regression, we determined the relationship between normal tissue irradiation and the risk of 22 toxicities at ten time points during and after treatment in 750 HNC patients. The toxicities involved swallowing, salivary, mucosal, speech, pain and general complaints. Studied predictors included patient, tumour and treatment characteristics and dose parameters of 28 organs. The resulting NTCP models were externally validated in 395 HNC patients. The NTCP models involved 14 organs that were associated with at least one toxicity. The oral cavity was the predominant organ, associated with 12 toxicities. Other important organs included the parotid and submandibular glands, buccal mucosa and swallowing muscles. In addition, baseline toxicity, treatment modality, and tumour site were common predictors of toxicity. The median discrimination performance (AUC) of the models was 0.71 (interquartile range: 0.68-0.75) at internal validation and 0.67 (interquartile range: 0.62-0.71) at external validation. We established a comprehensive individual toxicity risk profile that provides essential insight into how radiation exposure of various organs translates into multiple acute and late toxicities. This comprehensive understanding of radiation-induced toxicities enables a new radiation treatment optimisation concept that balances multiple toxicity risks simultaneously and minimises the overall toxicity burden for an individual HNC patient who needs to undergo radiation treatment.