Influence of study design on digital pathology image quality evaluation : the need to define a clinical task

Despite the current rapid advance in technologies for whole slide imaging, there is still no scientific consensus on the recommended methodology for image quality assessment of digital pathology slides. For medical images in general, it has been recommended to assess image quality in terms of doctors’ success rates in performing a specific clinical task while using the images (clinical image quality, cIQ). However, digital pathology is a new modality, and already identifying the appropriate task is difficult. In an alternative common approach, humans are asked to do a simpler task such as rating overall image quality (perceived image quality, pIQ), but that involves the risk of nonclinically relevant findings due to an unknown relationship between the pIQ and cIQ. In this study, we explored three different experimental protocols: (1) conducting a clinical task (detecting inclusion bodies), (2) rating image similarity and preference, and (3) rating the overall image quality. Additionally, within protocol 1, overall quality ratings were also collected (task-aware pIQ). The experiments were done by diagnostic veterinary pathologists in the context of evaluating the quality of hematoxylin and eosin-stained digital pathology slides of animal tissue samples under several common image alterations: additive noise, blurring, change in gamma, change in color saturation, and JPG compression. While the size of our experiments was small and prevents drawing strong conclusions, the results suggest the need to define a clinical task. Importantly, the pIQ data collected under protocols 2 and 3 did not always rank the image alterations the same as their cIQ from protocol 1, warning against using conventional pIQ to predict cIQ. At the same time, there was a correlation between the cIQ and task-aware pIQ ratings from protocol 1, suggesting that the clinical experiment context (set by specifying the clinical task) may affect human visual attention and bring focus to their criteria of image quality. Further research is needed to assess whether and for which purposes (e.g., preclinical testing) task-aware pIQ ratings could substitute cIQ for a given clinical task

Caniene cutane mastceltumoren

Canine cutaneous mast cell tumors (cMCT) are a commonly encountered neoplasia in small animal practice. Ninety-six percent of the cMCT can be diagnosed with cytology. Because of the variating biological character, it's difficult to establish a prognosis. Therefore, the prognosis is assessed with multiple prognostic factors: tumor location, systemic complaints, metastases, histological and cytological grading, proliferation markers, KIT-staining pattern, KIT-mutation and tumor free margins. The treatment of choice is based upon the results of these prognostic factors, the clinical stage and the tumor location. Possible treatments include surgery, radiotherapy, chemotherapy, electrochemotherapy, tyrosine kinase inhibitors, cryotherapy and intraregional therapy with deionized water

Effects of common image manipulations on diagnostic performance in digital pathology: human study

A very recent work of Ref.[1] studied the effects of image manipulation and image degradation on the perceived attributes of image quality (IQ) of digital pathology slides. However, before any conclusions and recommendations can be formulated regarding specific image manipulations (and IQ attributes), it is necessary to investigate their effects on the diagnostic performance of clinicians when interpreting these images. In this study, 6 expert pathologists interpreted digital images of H&E stained animal pathology samples in a free-response (FROC) experiment. Participants marked locations suspicious for viral inclusions (inclusion bodies) and rated them using a continuous scale from 0 (low confidence) to 100% (high confidence). The images were the same as in Ref.[1]: crops of digital pathology slides of 3 different animal tissue samples, all 1200×750 pixels in size. Each participant viewed a total of 72 images: 12 nonmanipulated (reference) images (4 of each tissue type), and 60 manipulated images (5 for each reference image). The extent of artificial manipulations was adjusted relative to the reference images using the HDR-VDP metric [2] in the luminance domain: added Gaussian blur (sb=3), decreased gamma (-5%), added white Gaussian noise (sn=10), decreased color saturation (-5%), and JPG compression (libjpeg 50). The images were displayed on a 3MP medical color LCD in a controlled viewing environment. Preliminary analysis assessing the change in the number of positive markings in the reference and manipulated images indicates that blurring and changes in gamma, followed by changes in color saturation, could have an effect on diagnostic performance. This largely coincides with the findings from Ref.[1], where IQ ratings appeared to be most affected by changes in color and gamma parameters. Importantly, diagnostic performance appears to be content dependent; it is different across tissue types. Further data analysis (including JAFROC) is ongoing and shall be reported in the conference talk

Haemangiosarcoma in a captive Asiatic lion (Panthera leo persica)

A 2.7-year-old male captive Asiatic lion (Panthera leo persica) died unexpectedly without preceding symptoms. Gross necropsy revealed liver and lung tumours, which proved to be haemangiosarcomas by histopathology. Some of the liver tumours were ruptured, leading to massive intra-abdominal haemorrhage and death. Haemangiosarcomas are rare in domestic and exotic felids, occurring in skin, thoracic-abdominal cavity and bones. Although these tumours mainly appear to be occurring in older cats, they are sometimes observed in younger animals, as in the present case. This is the first description of haemangiosarcoma in a young Asiatic lion

Dietary-dependent changes in the enteric nervous system and endothelium of premature piglets

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