Journal of clinical pathology. Supplement (College of Pathologists)最新文献

{"title":"Symposium on automation and data processing in pathology. Preface.","authors":"T P Whitehead","doi":"10.1136/jcp.s2-3.1.xi","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.xi","url":null,"abstract":"","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.xi","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16357802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automation in diagnostic bacteriology.","authors":"R E Williams, R E Trotman","doi":"10.1136/jcp.s2-3.1.8","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.8","url":null,"abstract":"Diagnostic bacteriological laboratories in hospitals suffer the same problems as the other diagnostic services: an ever-increasing load of work not matched by an increase in the number of people available to do it. The laboratories have managed to increase their 'productivity' in terms of reports per technician partly by a greater use of technical short cuts and reliance on simpler tests, and partly, presumably, simply by working faster. Hitherto practically nothing has been done to improve the productivity of the staff by providing them with mechanical aids. The reasons for this neglect become apparent when one analyses the work done in","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16008155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic scanning for cervical smears.","authors":"A I Spriggs","doi":"10.1136/jcp.s2-3.1.1","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.1","url":null,"abstract":"In approaching the question of automatic recognition of malignant cells, it is necessary first to make one point about neoplasia in general. It would be convenient to have a detectable or measurable character which is specific for malignant cells, for instance a staining reaction. The fact that none has ever been found is itself an important datum which tells us something about cancer. There are plenty of specific characters for various normal cellsthings like secretion of insulin or keratin, or the possession of basophil granules or cilia: all these differentiated characters are specific because the cells are working to a program. In malignant transformation the various programs are lost or debased, and probably no common feature is to be expected. Instead, we find the utmost diversity. The above statements do not by any means imply that an experienced observer cannot ever identify malignant cells. In some situations, and this includes the cervix uteri, the cells shed from a carcinoma are completely different in appearance from the normal epithelial cells, though they differ greatly among themselves. In discussions about the possibility of automatic screening an engineer is apt to be baffled because he cannot get a straight answer to his question, 'What do you notice when you identify a cell as malignant?' There are therefore two sides to the problem of automatic screening for malignant cells. The first is the matter of deciding on one or more marker characters or parameters, and how to use or interpret them so as to screen specimens. The second is the technical one, how to serve up the cells to the sensing device and how to measure the parameters chosen at a speed high enough to satisfy population screening requirements. Both these aspects involve peculiar difficulties and these will be discussed below. But at first it is worth examining the standard against which our hypothetical machine will be measured.","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16357791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data processing in histopathology.","authors":"M K Alexander","doi":"10.1136/jcp.s2-3.1.74","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.74","url":null,"abstract":"A histopathologist performs in diagnosis at least five fundamental tasks: he abstracts and mentally integrates features of tissue structure; he relates these patterns to information drawn from memory and other records; he makes inferences from all these data; he then forms and finally communicates a description. In any consideration of the ways in which computer technology can affect this sequence, we are immediately faced with the fact that the primary process, the recognition of pattern, is an exceedingly complex and largely unanalysed cerebral activity. Automatic recognition of pattern is still in its infancy, and although a beginning has been made in the limited and relatively simple fields of cytology and chromosome analysis towards the removal of the human brain from the scene, it is proposed to confine the present discussion to the remaining aspects of the process, namely, the formation, storage, recall, and communication of descriptions. The process of describing and making inferences from the patterns which we recognize, although open to logical analysis, is again a complex business. In practice, the simpler and more obvious the pattern, the fewer the words we employ. In the simplest cases of all we may proceed directly to the inference and apply a classifying label without more ado. On the other hand, where the pattern is not clearly seen, our descriptions are more consciously analytical and form the basis for an assessment of probabilities. This part of the process is comparable to clinical diagnosis and in principle is open to the techniques of propositional calculus (Feinstein, 1967), numerical taxonomy, and multivariate analysis (Baron and Fraser, 1965; Hayhoe, Quaglino, and Doll, 1964) which are being used experimentally in that field. However, the more immediate benefits to histopathology which are likely to be obtained from the application of modern data processing methods lie in the direction of the storage and retrieval of data on a large scale. Before discussing methods it seems pertinent to consider the reasons for wishing to embark on any system of data collection. I would suggest that these are both local and general in nature. At the local level, the linking of the histopathology reports with the remainder of the patients' records is the primary need. The problem at this point becomes part of the much larger and more difficult problem of the organization of the medical record for data processing. The potential benefits to pathology of the capacity to make correlations with other laboratory and with clinical data need no emphasis, although we are as yet far from a successful solution. Secondly there is the indexing of the local collection of reports and sections: this is the traditional field for most of the data processing that has been practised in histopathology to the present time. To turn to the motives which could lead to the collection of data on a larger scale, these include the formation of large data banks for ref","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.74","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16357799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated blood group serology.","authors":"G H Tovey","doi":"10.1136/jcp.s2-3.1.34","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.34","url":null,"abstract":"Although automation was introduced into biochemistry in 1957 (Skeggs, 1957), it was not until 1963 that McNeil, Helrick, and Ferrari (1963) first described a mechanized technique forABO grouping. This was followed a few months later by a method employing the AutoAnalyzer continuous flow principle by which up to 40 samples per hour could be both ABO and Rh (D) grouped (Sturgeon, Cedergren, and McQuiston, 1963). During the succeeding six years developments have been such that blood samples can now be ABO grouped by machine, Rh typed, screened for irregular blood group antibodies, and some of the subtypes determined at a rate of one sample per 30 seconds, or 120 samples per hour. This is accomplished by a multichannel machine. There is also available a single-channel AutoAnalyzer for use in screening and quantitation.","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.34","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16081394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experience with on-line computing in clinical chemistry.","authors":"L G Whitby, D Simpson","doi":"10.1136/jcp.s2-3.1.107","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.107","url":null,"abstract":"The scientific practice of medicine is making increasing demands upon clinical chemistry departments and it is the experience of these laboratories, both in teaching and non-teaching hospitals, that their work loads double every four to five years (Lathe and Mitchell, 1966). The use of AutoAnalyzers' has markedly increased the capacity of these laboratories for carrying out repetitive types of analytical work (Table I), and at the same time introduced a degree of much needed uniformity into the methods of performing analyses. Developments in automatic chemical equipment may further increase the work capacity of these departments, but already a different set of problems has emerged. These can be summarized under several interrelated headings: (1) specimen collection and unequivocal identification of samples with the correct patient throughout the subsequent procedures; (2) accession procedures in the laboratory; (3) maintenance of reliable standards of analytical performance in large-scale operations; (4) processing of instrumental readings; (5) report preparation and presentation; (6) uses made of laboratory data (a) by the clinicians and (b) by the laboratory; (7) records storage and arrangements for their retrieval for various purposes. This paper will concentrate particularly on experience gained so far with computer-dependent systems designed to help with problems 2 to 5. Blaivas and Mencz (1967, 1968), reporting upon an extension of their earlier system (Blaivas, 1966), described how an IBM 1710 computer had been routinely used for process control, linked on line to as many as 30 AutoAnalyzers performing up to 20 different analyses. The reasons for wishing to develop an alternative to the system in use at King's County Research Laboratories included the substantial cost (capital or hire) of the IBM system, and the desire to incorporate additional features such as records storage and cumulative reporting of laboratory results using the computer. The system recently installed in this laboratory is intended ultimately to help with problem 7 also, by storing records of laboratory work in a way that will allow the issue of","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16357789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An evaluation of the Coulter model S.","authors":"D F Barnard, A B Carter, P J Crosland-Taylor, J W Stewart","doi":"10.1136/jcp.s2-3.1.26","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.26","url":null,"abstract":"This report is concerned with the performance of the fully automatic counter Coulter model S. The apparatus consists of four units two of which, the electrical power and the vacuum and air pressure units, may be placed under the bench. The counter itself and its printout must be sited side by side on the bench (Fig. 1). Apart from what can be seen on the front, the cabinet conceals a mass of electrical, hydraulic, and pneumatic apparatus some of which is shown in Figure 2. To operate the counter is simple. The sampling tube A (Fig. 3) is placed in the blood container and the bar pushed. As soon as the light behind the bar changes to red, the sample is removed, the form fed into the printout and some 40 seconds later, after some hissing and gurgling, the printer thumps out the form with the results of the haemoglobin, red cell count, white cell count, packed cell volume, mean corpuscular volume, mean corpuscular haemoglobin concentration, and mean corpuscular haemoglobin. The apparatus aspirates 1.2 to 1.3 ml of blood, most of which is used to flush out the previous sample, only 44.7 cmm being used for the measurements. The machine can count a diluted capillary blood sample fed into a second sample tube B (Fig. 3). The dilution required is 44.7 cmm in 10 ml but as it will accept volumes ranging from 9 to 11 ml, 40cmm can be diluted in 9 ml buffered saline and this results in an undercount of only 0.5 %. The counting rate is theoretically 180 per hour as the machine is capable of accepting a new sample every 20 seconds. In practice, feeding in samples and forms takes a little time and the fastest I have achieved, working alone, is 121 counts in 50 minutes, a rate of 145 per hour. The forms used at present are purchased from Coulter Electronics but we are designing a request form which will also be a report form, and as all the results will be on the left hand side, it is suitable for serial reporting (Fig. 4). The size of the form and the initial seven results are dictated by the printout of the apparatus. (An interface is now available which will punch the results on punch tape as an additional or alternative method of recording.)","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.26","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16357793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Basis of data control for anatomical pathology.","authors":"J C Smith","doi":"10.1136/jcp.s2-3.1.77","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.77","url":null,"abstract":"A principal function of the morbid anatomist is the generation of tissue diagnoses and the recording of them. This activity requires skill and produces large amounts of data. At the rate of 600 necropsies per year, and 20 diagnoses per necropsy, a single department may generate over 12,000 morphological terms in a year's time. These terms are of considerable importance; they express the frequency of various disease states, they reveal the relationships among different lesions, and, as the record continues, they disclose the changing incidence of human illnesses. It is, therefore, important to medicine and to the welfare of communities and perhaps nations, that these data be recorded and stored in such a way that retrievability is enhanced and analyses are possible. As the record enlarges, and the usefulness of it increases, the need for generating a retrievable account becomes imperative, and the responsibility for satisfying this need rests squarely on the shoulders of the morbid anatomists. While the anatomical record grows rapidly, the methods for retrieving those data have not been overlooked. There are simple methods and complex methods. There are code-by-hand methods (Systemized Nomenclature of Pathology, 1965), there are retrieve-by-machine methods (Systemized Nomenclature of Pathology, 1965; Carpenter, 1962), and there are methods that both code and retrieve by machine alone (Smith and Melton, 1964; Lamson and Dimsdale, 1966; Paplanus, Shepard, and Zvargulis, 1969). This welter of methods, however, does not entirely solve the problem before pathologists. Between the mountain of records to be retrieved on the one side, and the welter of methods for accomplishing the retrieval process on the other, lies the bottleneck of translating the English words of the former into the code signals of the latter. The success of any system will depend on the ease with which this step is accomplished. The bottleneck of coding is depicted in Figure 1. It is the coding procedure that requires special attention. Coding begins with a definition of what the retrieval process is expected to accomplish. The retrieval process should be expected to accomplish two main objectives: the first is the identification of any record that lists a particular diagnosis, and the second is the enumeration of the anatomical site involved and the pathological process independently of each other, and on hierarchical levels progressing from generality to specificity. Thus, enumerating the pathological involvement of anatomical systems regardless of the lesions, and on the other hand, enumerating pathological processes irrespective of their sites, may be easily undertaken. For example, the frequency of abnormalities of the central nervous system may be of interest regardless of what the abnormalities were. And in the same way, the incidence of pathological processes such as carcinoma in a necropsy population is a figure of interest irrespective of the sites at which they arose. The","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.77","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16357800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discrete analysis systems.","authors":"B E Northam","doi":"10.1136/jcp.s2-3.1.42","DOIUrl":"https://doi.org/10.1136/jcp.s2-3.1.42","url":null,"abstract":"Discrete analysis systems are so called because the samples are treated and carried through the major part of the analytical process in separate containers. Such systems can be very simple involving only a diluting module and a colorimeter or be highly sophisticated multichannel machines. Up to the present time laboratory automation (or strictly 'mechanization') has been dominated by the continuous flow systems and discrete systems have not yet had time to establish themselves widely as serious competitors. In this paper I cannot attempt to give an evaluation of individual systems and I shall confine myself to a discussion of general principles and indicate how these systems may differ from one another.","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1969-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/jcp.s2-3.1.42","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16357795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The biology of mycoplasmas.","authors":"D Taylor-Robinson","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":78352,"journal":{"name":"Journal of clinical pathology. Supplement (College of Pathologists)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1968-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"16354926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}