Department of Radiology, New York University Langone Medical Center, 660 First Avenue, New York, NY 10016.
Department of Radiology, New York University Langone Medical Center, 660 First Avenue, New York, NY 10016.
Acad Radiol. 2018 May;25(5):673-680. doi: 10.1016/j.acra.2017.11.009. Epub 2018 Jan 17.
Radiology-pathology correlation is time-consuming and is not feasible in most clinical settings, with the notable exception of breast imaging. The purpose of this study was to determine if an automated radiology-pathology report pairing system could accurately match radiology and pathology reports, thus creating a feedback loop allowing for more frequent and timely radiology-pathology correlation.
An experienced radiologist created a matching matrix of radiology and pathology reports. These matching rules were then exported to a novel comprehensive radiology-pathology module. All distinct radiology-pathology pairings at our institution from January 1, 2016 to July 1, 2016 were included (n = 8999). The appropriateness of each radiology-pathology report pairing was scored as either "correlative" or "non-correlative." Pathology reports relating to anatomy imaged in the specific imaging study were deemed correlative, whereas pathology reports describing anatomy not imaged with the particular study were denoted non-correlative.
Overall, there was 88.3% correlation (accuracy) of the radiology and pathology reports (n = 8999). Subset analysis demonstrated that computed tomography (CT) abdomen/pelvis, CT head/neck/face, CT chest, musculoskeletal CT (excluding spine), mammography, magnetic resonance imaging (MRI) abdomen/pelvis, MRI brain, musculoskeletal MRI (excluding spine), breast MRI, positron emission tomography (PET), breast ultrasound, and head/neck ultrasound all demonstrated greater than 91% correlation. When further stratified by imaging modality, CT, MRI, mammography, and PET demonstrated excellent correlation (greater than 96.3%). Ultrasound and non-PET nuclear medicine studies demonstrated poorer correlation (80%).
There is excellent correlation of radiology imaging reports and appropriate pathology reports when matched by organ system. Rapid, appropriate radiology-pathology report pairings provide an excellent opportunity to close feedback loop to the interpreting radiologist.
放射科与病理科的关联既耗时又不切实际，除了在乳腺影像学方面外，这种关联在大多数临床环境中都无法实现。本研究的目的是确定自动化的放射科-病理科报告配对系统是否能够准确匹配放射科和病理科的报告，从而创建一个反馈循环，以实现更频繁和及时的放射科-病理科关联。
一位经验丰富的放射科医生创建了一个放射科和病理科报告的匹配矩阵。这些匹配规则随后被导出到一个新的综合放射科-病理科模块中。我们机构从 2016 年 1 月 1 日至 2016 年 7 月 1 日的所有不同的放射科-病理科配对都包括在内（n=8999）。每个放射科-病理科报告配对的适当性被评为“相关”或“不相关”。与特定影像学研究中成像的解剖结构相关的病理报告被认为是相关的，而描述特定研究中未成像的解剖结构的病理报告则被认为是不相关的。
总体而言，放射科和病理科报告的相关性（准确性）为 88.3%（n=8999）。子集分析表明，腹部/盆腔 CT、头颈部/面部 CT、胸部 CT、肌肉骨骼 CT（不包括脊柱）、乳房 X 线摄影、腹部/盆腔 MRI、脑部 MRI、肌肉骨骼 MRI（不包括脊柱）、乳腺 MRI、正电子发射断层扫描（PET）、乳房超声和头颈部超声均显示出大于 91%的相关性。当进一步按成像方式分层时，CT、MRI、乳房 X 线摄影和 PET 显示出极好的相关性（大于 96.3%）。超声和非 PET 核医学研究显示出较差的相关性（80%）。
当按器官系统匹配时，放射科成像报告与适当的病理报告具有极好的相关性。快速、适当的放射科-病理科报告配对为向解释放射科医生提供了极好的机会来建立反馈循环。
