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21(st) century workflow: A proposal.

Fine JL - J Pathol Inform (2014)

Bottom Line: Pathologists have not yet developed a well-articulated plan for effectively utilizing digital imaging technology in their work.This paper outlines a proposal that is intended to begin meaningful progress toward achieving helpful computer-assisted pathology sign-out systems, such as pathologists' computer-assisted diagnosis (pCAD). pCAD is presented as a hypothetical intelligent computer system that would integrate advanced image analysis and better utilization of existing digital pathology data from lab information systems.This proposal provides stakeholders with a conceptual framework that can be used to facilitate development work, communication, and identification of new automation strategies.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.

ABSTRACT
Digital pathology is rapidly developing, but early systems have been slow to gain traction outside of niche applications such as: Second-opinion telepathology, immunostain interpretation, and intraoperative telepathology. Pathologists have not yet developed a well-articulated plan for effectively utilizing digital imaging technology in their work. This paper outlines a proposal that is intended to begin meaningful progress toward achieving helpful computer-assisted pathology sign-out systems, such as pathologists' computer-assisted diagnosis (pCAD). pCAD is presented as a hypothetical intelligent computer system that would integrate advanced image analysis and better utilization of existing digital pathology data from lab information systems. A detailed example of automated digital pathology is presented, as an automated breast cancer lymph node sign-out. This proposal provides stakeholders with a conceptual framework that can be used to facilitate development work, communication, and identification of new automation strategies.

No MeSH data available.


Related in: MedlinePlus

A pathologists’ computer assisted diagnosis (pCAD) system organizes images of lymph node fragments into a series of well triaged regions of interests (ROIs) that are ready for rapid pathologist review. At top are the lymph node fragments, displayed in order from largest to smallest, without regard to the source WSIs (i.e., neighboring fragments may not be from the same WSI or slide). Through a series of image analysis and anatomic rules, the pCAD system subdivides the imaged fragments into clinically relevant ROIs (not shown in detail but depicted by the vertical blue arrow). For the specific work task of finding tumor metastases, the ROIs are triaged or sorted for pathologist review, from most-suspicious (left) to least (right). The riskiest, left-most ROI is a subcapsular sinus image that contains a small tumor metastasis that is highlighted by a red dot. Remaining ROIs are benign appearing, but are still sorted by other factors, including lymph node compartment, surgical designation, etc. Note that the least suspicious peri-nodal fat ROIs are off to the right; such ROIs could be reviewed last, rapidly (i.e., low magnification), or perhaps not at all if the pCAD system were clinically trustworthy
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Figure 5: A pathologists’ computer assisted diagnosis (pCAD) system organizes images of lymph node fragments into a series of well triaged regions of interests (ROIs) that are ready for rapid pathologist review. At top are the lymph node fragments, displayed in order from largest to smallest, without regard to the source WSIs (i.e., neighboring fragments may not be from the same WSI or slide). Through a series of image analysis and anatomic rules, the pCAD system subdivides the imaged fragments into clinically relevant ROIs (not shown in detail but depicted by the vertical blue arrow). For the specific work task of finding tumor metastases, the ROIs are triaged or sorted for pathologist review, from most-suspicious (left) to least (right). The riskiest, left-most ROI is a subcapsular sinus image that contains a small tumor metastasis that is highlighted by a red dot. Remaining ROIs are benign appearing, but are still sorted by other factors, including lymph node compartment, surgical designation, etc. Note that the least suspicious peri-nodal fat ROIs are off to the right; such ROIs could be reviewed last, rapidly (i.e., low magnification), or perhaps not at all if the pCAD system were clinically trustworthy

Mentions: Next is the actual task of finding tumor. SLNB slides typically contain one or more histologic sections of lymph node and fat fragments, and the hypothetical computer system would be able to identify these [Figure 3]. Further, individual lymph node fragments can generally be divided into three compartments: Subcapsular sinus, lymph node interior, and peri-nodal fat [Figure 4]. These compartments can be further subdivided into ROIs that are small enough for rapid pathologist review. The computer would preview the ROIs; optimally it would dependably identify and prioritize tumor-positive ROIs. If no ROIs were positive, then the ROIs should be ranked or triaged based on risk and/or atypia assessment. Multiple factors could be used, but the goal is to deliver the most relevant ROIs to the pathologist as early as possible [Figure 5]. Clearly benign fat or lymphoid tissue should be reviewed later, if at all. The computer would show ROIs to the pathologist interactively, and the pathologist would confirm any tumor findings.


21(st) century workflow: A proposal.

Fine JL - J Pathol Inform (2014)

A pathologists’ computer assisted diagnosis (pCAD) system organizes images of lymph node fragments into a series of well triaged regions of interests (ROIs) that are ready for rapid pathologist review. At top are the lymph node fragments, displayed in order from largest to smallest, without regard to the source WSIs (i.e., neighboring fragments may not be from the same WSI or slide). Through a series of image analysis and anatomic rules, the pCAD system subdivides the imaged fragments into clinically relevant ROIs (not shown in detail but depicted by the vertical blue arrow). For the specific work task of finding tumor metastases, the ROIs are triaged or sorted for pathologist review, from most-suspicious (left) to least (right). The riskiest, left-most ROI is a subcapsular sinus image that contains a small tumor metastasis that is highlighted by a red dot. Remaining ROIs are benign appearing, but are still sorted by other factors, including lymph node compartment, surgical designation, etc. Note that the least suspicious peri-nodal fat ROIs are off to the right; such ROIs could be reviewed last, rapidly (i.e., low magnification), or perhaps not at all if the pCAD system were clinically trustworthy
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4260324&req=5

Figure 5: A pathologists’ computer assisted diagnosis (pCAD) system organizes images of lymph node fragments into a series of well triaged regions of interests (ROIs) that are ready for rapid pathologist review. At top are the lymph node fragments, displayed in order from largest to smallest, without regard to the source WSIs (i.e., neighboring fragments may not be from the same WSI or slide). Through a series of image analysis and anatomic rules, the pCAD system subdivides the imaged fragments into clinically relevant ROIs (not shown in detail but depicted by the vertical blue arrow). For the specific work task of finding tumor metastases, the ROIs are triaged or sorted for pathologist review, from most-suspicious (left) to least (right). The riskiest, left-most ROI is a subcapsular sinus image that contains a small tumor metastasis that is highlighted by a red dot. Remaining ROIs are benign appearing, but are still sorted by other factors, including lymph node compartment, surgical designation, etc. Note that the least suspicious peri-nodal fat ROIs are off to the right; such ROIs could be reviewed last, rapidly (i.e., low magnification), or perhaps not at all if the pCAD system were clinically trustworthy
Mentions: Next is the actual task of finding tumor. SLNB slides typically contain one or more histologic sections of lymph node and fat fragments, and the hypothetical computer system would be able to identify these [Figure 3]. Further, individual lymph node fragments can generally be divided into three compartments: Subcapsular sinus, lymph node interior, and peri-nodal fat [Figure 4]. These compartments can be further subdivided into ROIs that are small enough for rapid pathologist review. The computer would preview the ROIs; optimally it would dependably identify and prioritize tumor-positive ROIs. If no ROIs were positive, then the ROIs should be ranked or triaged based on risk and/or atypia assessment. Multiple factors could be used, but the goal is to deliver the most relevant ROIs to the pathologist as early as possible [Figure 5]. Clearly benign fat or lymphoid tissue should be reviewed later, if at all. The computer would show ROIs to the pathologist interactively, and the pathologist would confirm any tumor findings.

Bottom Line: Pathologists have not yet developed a well-articulated plan for effectively utilizing digital imaging technology in their work.This paper outlines a proposal that is intended to begin meaningful progress toward achieving helpful computer-assisted pathology sign-out systems, such as pathologists' computer-assisted diagnosis (pCAD). pCAD is presented as a hypothetical intelligent computer system that would integrate advanced image analysis and better utilization of existing digital pathology data from lab information systems.This proposal provides stakeholders with a conceptual framework that can be used to facilitate development work, communication, and identification of new automation strategies.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.

ABSTRACT
Digital pathology is rapidly developing, but early systems have been slow to gain traction outside of niche applications such as: Second-opinion telepathology, immunostain interpretation, and intraoperative telepathology. Pathologists have not yet developed a well-articulated plan for effectively utilizing digital imaging technology in their work. This paper outlines a proposal that is intended to begin meaningful progress toward achieving helpful computer-assisted pathology sign-out systems, such as pathologists' computer-assisted diagnosis (pCAD). pCAD is presented as a hypothetical intelligent computer system that would integrate advanced image analysis and better utilization of existing digital pathology data from lab information systems. A detailed example of automated digital pathology is presented, as an automated breast cancer lymph node sign-out. This proposal provides stakeholders with a conceptual framework that can be used to facilitate development work, communication, and identification of new automation strategies.

No MeSH data available.


Related in: MedlinePlus