Taylor K, Parashar D, Bouverat G, Poulos A, Gullien R, Stewart E, Aarre R, Crystal P, Wallis M
Cambridge Breast Unit, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, England, United Kingdom.
Cancer Research Centre, University of Warwick, Coventry, CV4 7AL, England, United Kingdom; Statistics and Epidemiology Unit, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, CV4 7AL, England, United Kingdom.
Radiography (Lond). 2017 Nov;23(4):343-349. doi: 10.1016/j.radi.2017.03.004. Epub 2017 Jul 8.
Optimum mammography positioning technique is necessary to maximise cancer detection. Current criteria for mammography appraisal lack reliability and validity with a need to develop a more objective system. We aimed to establish current international practice in assessing image quality (IQ), of screening mammograms then develop and validate a reproducible assessment tool.
A questionnaire sent to centres in countries undertaking population screening identified practice, participants for an expert panel (EP) of radiologists/radiographers and a testing panel (TP) of radiographers. The EP developed category criteria and descriptors using a modified Delphi process to agree definitions. The EP scored 12 screening mammograms to test agreement then a main set of 178 cases. Weighted scores were derived for each descriptor enabling calculation of numerical parameters for each new category. The TP then scored the main set. Statistical analysis included ANOVA, t-tests and Kendall's coefficient.
11 centres in 8 countries responded forming an EP of 7 members and TP of 44 members. The EP showed moderate agreement when the scoring the mini test set W = 0.50 p < 0.001 and the main set W = 0.55 p < 0.001, 'posterior nipple line' being the most difficult descriptor. The weighted total scores differentiated the 4 new categories Perfect, Good, Adequate and Inadequate (p < 0.001).
We have developed an assessment tool by Delphi consensus and weighted consensus criteria. We have successfully tabulated a range of numerical scores for each new category providing the first validated and reproducible mammography IQ scoring system.
最佳的乳房X线摄影定位技术对于最大限度地检测癌症至关重要。当前乳房X线摄影评估标准缺乏可靠性和有效性,需要开发一个更客观的系统。我们旨在确立当前国际上评估筛查乳房X线摄影图像质量(IQ)的实践方法,然后开发并验证一种可重复的评估工具。
向进行人群筛查的国家的中心发送问卷调查,以确定实践情况、放射科医生/放射技师专家小组(EP)和放射技师测试小组(TP)的参与者。EP使用改良的德尔菲法制定类别标准和描述符,以达成定义共识。EP对12张筛查乳房X线照片进行评分以测试一致性,然后对178例主要病例进行评分。为每个描述符得出加权分数,从而能够计算每个新类别的数值参数。然后TP对主要病例组进行评分。统计分析包括方差分析、t检验和肯德尔系数。
8个国家的11个中心做出回应,组成了一个由7名成员组成的EP和一个由44名成员组成的TP。EP在对小型测试集评分时显示出中等一致性(W = 0.50,p < 0.001),对主要病例组评分时一致性为W = 0.55,p < 0.001,“乳头后线”是最难的描述符。加权总分区分了4个新类别:完美、良好、足够和不足(p < 0.001)。
我们通过德尔菲共识和加权共识标准开发了一种评估工具。我们成功地为每个新类别列出了一系列数值分数,提供了首个经过验证且可重复的乳房X线摄影IQ评分系统。