| Literature DB >> 32540554 |
Matteo Basilio Suter1, Filippo Pesapane2, Giorgio Maria Agazzi3, Tania Gagliardi4, Olga Nigro5, Anna Bozzini6, Francesca Priolo7, Silvia Penco8, Enrico Cassano9, Claudio Chini10, Alessandro Squizzato11.
Abstract
Breast cancer diagnosis and staging is based on mammography, ultrasound, and magnetic resonance imaging (MRI). Contrast enhanced spectral mammography (CESM) has gained momentum as an innovative and clinically useful method for breast assessment. CESM is based on abnormal enhancement of neoplastic tissue compared to surrounding breast tissue. We performed a systematic review of prospective trial to evaluate its diagnostic performance, following standard PRISMA-DTA. We used a bivariate random-effects regression approach to obtain summary estimates of both sensitivity and specificity of CESM. 8 studies published between 2003 and 2019 were included in the meta-analysis for a total of 945 lesions. The summary area under the curve obtained from all the study was 89% [95% CI 86%-91%], with a sensitivity of 85% [95% CI 73%-93%], and a specificity of 77% [95% CI 60%-88%]. With a pre-test probability of malignancy of 57% a positive finding at CESM gives a post-test probability of 83% while a negative finding a post-test probability of 20%. CESM shows a suboptimal sensitivity and specificity in the diagnosis of breast cancer in a selected population, and at present time, it could be considered only as a possible alternative test for breast lesions assessment when mammography and ultrasound are not conclusive or MRI is contraindicated or not available.Entities:
Keywords: Breast neoplasms; Contrast enhanced spectral mammography; Mammography; Meta-analysis; Systematic review
Mesh:
Substances:
Year: 2020 PMID: 32540554 PMCID: PMC7375655 DOI: 10.1016/j.breast.2020.06.005
Source DB: PubMed Journal: Breast ISSN: 0960-9776 Impact factor: 4.380
Study characteristics.
| Study | Patients | Lesions | BC | DCIS | Median age (range) | Projection used | Criteria evaluated | Inclusion criteria | Exposure (Gy) | Contrast media |
|---|---|---|---|---|---|---|---|---|---|---|
| 18 | 18 | 11 | 1 | 52 | CC | CE | BI-RADS 4–5 on Mx | 6 | Optiray 300 | |
| 70 | 80 | 30 | 5 | 55 | CC | CE + morphology | Suspicious lesion on Mx, US, MRI | 1.76 | Ultravist 370 | |
| 120 | 133 | 80 | NR | 56 (27–86) | CC MLO | CE + morphology | Recall from screening + Suspicious lesion on Mx, US, MRI | 0.7–3.6 | Xenetix 300 | |
| 26 | 26 | 14 | 1 | 51 | MLO | CE | Suspicious lesion on Mx | 0.7 | Omnipaque 350 | |
| 193 | 225 | 143 | 16 | 55 | CC MLO | CE + morphology | Suspicious lesion on Mx | NR | NR | |
| 22 | 22 | 10 | 1 | NR (40–74) | CC | CE + morphology | Suspicious lesion on Mx, US | NR | Omnipaque 300 | |
| NR | 178 | 104 | 6 | 46 | Unclear | CE + morphology | Unclear | NR | NR | |
| 235 | 263 | 177 | 6 | NR | CC MLO | CE + morphology | Suspicious lesion on US or clinical | NR | Iohexol |
Legend: BC breast cancer DCIS ductal carcinoma in situ Gy Grey CC cranio-caudal CE contrast enhancement Mx mammography US ultrasound MRI magnetic resonance imaging MLO mediolateral oblique NR not reported.
Fig. 1The figure shows the workflow for study screening and selection.
Risk of bias.
| Ref. | Study | Risk of bias | Applicability concerns | |||||
|---|---|---|---|---|---|---|---|---|
| Patient selecion | Index Test | Reference Standard | Flow and Timing∗ | Patient selecion | Index Test | Reference Standard | ||
| 26 | Brandan 2016 | H | L | L | L(0%) | H | L | L |
| 28 | Diekmann 2011 | L | L | L | H(17%) | H | L | L |
| 27 | Dromain 2011 | L | L | L | H(10%) | L | L | L |
| 29 | Lewin 2003 | U | L | L | L(1%) | L | L | L |
| 30 | Łuczyńska 2016 | H | L | L | L(0%) | H | L | L |
| 31 | Jong 2003 | L | L | L | L(5%) | H | L | L |
| 32 | Tohamey 2018 | U | H | H | L(8%) | H | H | H |
| 33 | Xing 2019 | U | L | L | L(0%) | U | L | L |
L Low risk U Unclear risk H High risk.
∗ percentage of no histology (our threshold = 5%).
Fig. 2The plot shows the summary bivariate ROC curve for CESM diagnostic accuracy.
Fig. 3The figure shows the scatterplot obtained using logit sensitivity vs logit specificity suggesting no evidence of a threshold effect.
Fig. 4The Fagan plot (a) and the probability modifying plot (b) show that with a pre-test probability of malignancy as in our sample of 57% a positive finding at CESM gives a post-test probability of 83% while a negative finding a post-test probability of 20%.
Fig. 5The figure shows influence analysis and outlier analysis based on Cook’s distance and standardized predicted random effects. The study by Luczynska et al. resulted to be both an outlier and the most influential.
Fig. 6The figure shows results for univariate metaregression. None of the investigated covariates was associated with statistically significant different sensitivities or specificities.
Fig. 7The figure shows the funnel plot with no evidence of small study effect.