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Our aim was to outline a procedure for obtaining a rapid autopsy in order to collect high-quality postmortem tissue for genomic analysis.
This report details a bi-institutional collaborative effort to coordinate a rapid autopsy for a pediatric patient who had died at home. We discuss the scientific rationale for offering a rapid autopsy to caregivers of pediatric patients as well as parental perspectives on broaching the subject of autopsy. We then review the logistics and coordination involved with planning a rapid autopsy and the sequence of events needed to maximize tissue quality.
We report the successful coordination of a rapid autopsy for a patient who died in a hospice setting at her out-of-state home. The time interval from death to the start of the rapid autopsy procedure was 4.5 hours, despite the logistical considerations demanded by the location of the patient. Tumor aliquots and nonneoplastic tissues were successfully snap frozen for downstream genomic studies.
Significance of Results:
Physicians should consider trialing a rapid autopsy program at their institution that could be offered to caregivers of pediatric patients. This case report offers a framework to help clinicians develop their own rapid autopsy programs as well as guidelines to help streamline this process for appropriate candidates going forward.
In Chapter 1, Dickinson analyzes the complex history of theoretical and computational vision. With some exceptions, the trend in recent decades is away from explicit structural representation and toward direct mapping of image features to semantic categories based on machine learning. The best-known formulations of the older, structural paradigm are those of Marr (Marr and Nishihara 1978) and Biederman (1987), although the central idea that objects are represented as configurations of parts has a long history (Barlow 1972; Binford 1971; Dickinson, Pentland, and Rosenfeld 1992; Hoffman and Richards 1984; Hubel and Wiesel 1959, 1968; Milner 1974; Palmer 1975; Selfridge 1959; Sutherland 1968). A configural representation would be carried by ensembles of processing units or neurons, each encoding the shape and relative position of a constituent part. This coding format is appealing because it solves three major problems in object vision. The first problem is the enormous dimensionality (on the order of 106) of retinal activity patterns. A signal of this complexity is too unwieldy to communicate between brain regions (owing to wiring constraints) or store in memory (owing to limited information capacity of synaptic weight patterns). Compression of this signal into a list of part specifications on the order of 101 to 102 would make communication and storage more practical. The second problem is the extremely variable mapping between retinal images and object identity. The same object can produce an infinity of very different retinal images depending on its position, orientation, lighting, partial occlusion, and other factors.