Radiology reporting in oncology—oncologists’ perspective

Abstract

Background Structured reporting and standardized criteria are increasingly recognized as means of improving both radiological and clinical practice by allowing for better content and clarity. Our aim was to examine oncologists’ opinions and expectations concerning the radiologist’s report to identify general needs in daily practice and ways to improve interdisciplinary communication. Methods A 19-question survey was sent to 230 oncologists from three different countries (France, Romania, Switzerland) identified on the online web pages of different hospitals and private clinics. The survey was sent by electronic mail with an online survey program (Google Forms®). All recipients were informed of the purpose of the study. The data were collected by the online survey program and analysed through filtering the results and cross-tabulation. Results A total of 52 responses were received (response rate of 22.6%). The majority of the respondents (46/52, 88%) preferred the structured report, which follows a predefined template. Most of the respondents (40/52, 77%) used RECIST 1.1 or iRECIST in tumour assessment. Nearly half of the oncologists (21/52, 40%) measured 1–3 cases per week. On a 10-point Likert scale, 34/52 (65%) oncologists rated their overall level of satisfaction with radiologists’ service between 7 and 10. In contrast, 12/52 (19%) oncologists rated the radiologists’ service between 1 and 4. Moreover, 42/52 (80%) oncologists acknowledged that reports created by a radiologist with a subspecialty in oncologic imaging were superior to those created by a general radiologist. Conclusion Structured reports in oncologic patients and the use of RECIST criteria are preferred by oncologists in their daily clinical practice, which signals the need for radiologists also to implement such reports to facilitate communication. Furthermore, most of the oncologists we interviewed recognized the added value provided by radiologists specializing in oncologic imaging. Because this subspecialty is present in only a few countries, generally in large clinics, further training might become a challenge; nevertheless, intensive efforts should be made to enhance expertise in cancer imaging.

Indeterminate pulmonary nodules in non‐rhabdomyosarcoma soft tissue sarcoma: A study of the European paediatric Soft Tissue Sarcoma Study Group

“…in RMS 20 and enforces the importance of structured reporting in chest CT, as proposed for RMS by van Ewijk et al 28,29 . This also underlines the need for dedicated radiologists, as already demonstrated by their essential role in multidisciplinary oncological meetings 30–33 …”

“…28,29 This also underlines the need for dedicated radiologists, as already demonstrated by their essential role in multidisciplinary oncological meetings. [30][31][32][33] Moreover, despite the robust results obtained with the current definition of indeterminate pulmonary nodules, probably in complex patients such as those with NRSTS, the threshold may need further investigation and critical reconsideration. For example, the North American Children's Oncology Group uses the response evaluation criteria in solid tumors criteria for NRSTS, which considers lung lesions <10 mm as nonmeasurable.…”

Perceptions of radiologists on structured reporting for cancer imaging—a survey by the European Society of Oncologic Imaging (ESOI)

“…While SR appears to be regarded favorably among radiologists and clinicians [ 14 – 18 ], its widespread implementation remains challenging due to the current heterogeneity in terms of report structure and contents (i.e., lack of national and international standards), technical aspects (e.g., graphical user interface vs. document-based solutions), and its major impact on radiologists’ daily practice [ 19 ]. In addition, the field of radiology faces multiple changes such as increased numbers of examinations (as shown by OECD data [ 20 ]), radiologist shortage and burnout [ 21 ], a shift towards teleradiology services, as well as the application of artificial intelligence (AI) [ 6 ].…”