Dataset Information

Towards More Structure: Comparing TNM Staging Completeness and Processing Time of Text-Based Reports versus Fully Segmented and Annotated PET/CT Data of Non-Small-Cell Lung Cancer.

ABSTRACT: Results of PET/CT examinations are communicated as text-based reports which are frequently not fully structured. Incomplete or missing staging information can be a significant source of staging and treatment errors. We compared standard text-based reports to a manual full 3D-segmentation-based approach with respect to TNM completeness and processing time. TNM information was extracted retrospectively from 395 reports. Moreover, the RIS time stamps of these reports were analyzed. 2995 lesions using a set of 41 classification labels (TNM features + location) were manually segmented on the corresponding image data. Information content and processing time of reports and segmentations were compared using descriptive statistics and modelling. The TNM/UICC stage was mentioned explicitly in only 6% (n=22) of the text-based reports. In 22% (n=86), information was incomplete, most frequently affecting T stage (19%, n=74), followed by N stage (6%, n=22) and M stage (2%, n=9). Full NSCLC-lesion segmentation required a median time of 13.3?min, while the median of the shortest estimator of the text-based reporting time (R1) was 18.1?min (p=0.01). Tumor stage (UICC I/II: 5.2?min, UICC III/IV: 20.3?min, p < 0.001), lesion size (p < 0.001), and lesion count (n=1: 4.4?min, n=12: 37.2?min, p < 0.001) correlated significantly with the segmentation time, but not with the estimators of text-based reporting time. Numerous text-based reports are lacking staging information. A segmentation-based reporting approach tailored to the staging task improves report quality with manageable processing time and helps to avoid erroneous therapy decisions based on incomplete reports. Furthermore, segmented data may be used for multimedia enhancement and automatization.

SUBMITTER: Sexauer R

PROVIDER: S-EPMC6236664 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Towards More Structure: Comparing TNM Staging Completeness and Processing Time of Text-Based Reports versus Fully Segmented and Annotated PET/CT Data of Non-Small-Cell Lung Cancer.

Sexauer Raphael R Weikert Thomas T Mader Kevin K Wicki Andreas A Schädelin Sabine S Stieltjes Bram B Bremerich Jens J Sommer Gregor G Sauter Alexander W AW

Contrast media & molecular imaging 20181101

Results of PET/CT examinations are communicated as text-based reports which are frequently not fully structured. Incomplete or missing staging information can be a significant source of staging and treatment errors. We compared standard text-based reports to a manual full 3D-segmentation-based approach with respect to TNM completeness and processing time. TNM information was extracted retrospectively from 395 reports. Moreover, the RIS time stamps of these reports were analyzed. 2995 lesions usi ...[more]

PMID: 30515067

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Project description:ObjectivesFollowing a diagnosis of cancer, the detailed assessment of prognostic stage by radiology is a crucial determinant of initial therapeutic strategy offered to patients. Pretherapeutic stage by imaging is known to be inconsistently documented. We tested whether the completeness of cancer staging radiology reports could be improved through a nationally introduced pilot of proforma-based reporting for a selection of six common cancers.DesignProspective interventional study comparing the completeness of radiology cancer staging reports before and after the introduction of proforma reporting.SettingTwenty-one UK National Health Service hospitals.Participants1283 cancer staging radiology reports were submitted.Main outcome measuresRadiology staging reports across the six cancers types were evaluated before and after the implementation of proforma-based reporting. Report completeness was assessed using scoring forms listing the presence or absence of predetermined key staging data. Qualitative data regarding proforma implementation and usefulness were collected from questionnaires provided to radiologists and end-users.ResultsElectronic proforma-based reporting was successfully implemented in 15 of the 21 centres during the evaluation period. A total of 787 preproforma and 496 postproforma staging reports were evaluated. In the preproforma group, only 48.7% (5586/11 470) of key staging items were present compared with 87.3% (6043/6920) in the postproforma group. Thus, the introduction of proforma reporting produced a 78% improvement in staging completeness . This increase was seen across all cancer types and centres. The majority of participants found proforma reporting improved cancer reporting quality for their clinical practice .ConclusionThe implementation of proforma reporting results in a significant improvement in the completeness of cancer staging reports. Proforma-based assessment of cancer stage enables objective comparisons of patient outcomes across centres. It should therefore become an auditable quality standard for cancer care.

Dataset Information

Towards More Structure: Comparing TNM Staging Completeness and Processing Time of Text-Based Reports versus Fully Segmented and Annotated PET/CT Data of Non-Small-Cell Lung Cancer.

Publications

Towards More Structure: Comparing TNM Staging Completeness and Processing Time of Text-Based Reports versus Fully Segmented and Annotated PET/CT Data of Non-Small-Cell Lung Cancer.

Similar Datasets

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