| Literature DB >> 15018618 |
Marnix A J De Roos1, Ruud M Pijnappel, Wendy J Post, Jaap De Vries, Peter C Baas, Lex D Groote.
Abstract
BACKGROUND: It is helpful in planning treatment for patients with ductal carcinoma in situ (DCIS) if the size and grade could be reliably predicted from the mammography. The aims of this study were to determine if the type of calcification can be best used to predict histopathological grade from the mammograms, to examine the association of mammographic appearance of DCIS with grade and to assess the correlation between mammographic size and pathological size.Entities:
Year: 2004 PMID: 15018618 PMCID: PMC394346 DOI: 10.1186/1477-7819-2-4
Source DB: PubMed Journal: World J Surg Oncol ISSN: 1477-7819 Impact factor: 2.754
Clinical, radiological and pathological characteristics.
| Clinical, radiological and pathological characteristics | N (%) |
| Menopausal status (n = 115) | |
| Pre-menopausal | 27(24%) |
| Post-menopausal | 88(76%) |
| Screening detected (n = 115) | |
| Yes | 53(46%) |
| No | 62(54%) |
| Palpable lesion (n = 115) | |
| Yes | 26(23%) |
| No | 89(77%) |
| Mammographic appearance (n = 115) | |
| Microcalcifications | 70(61%) |
| Abnormality other than microcalcifications | 21(18%) |
| Combination of microcalcifications and a density | 17(15%) |
| Occult | 7(6%) |
| Mammographic appearance of microcalcifications (n = 87) | |
| Linear | 6(7%) |
| Coarse granular | 27(31%)8(9%) |
| Fine granular | 8(9%) |
| Linear and coarse granular | 27(31%) |
| Coarse and fine granular | 19(22%) |
| Distribution of microcalcifications (n = 87) | |
| Cluster | 50(57%) |
| Segment | 3743%) |
| Centricity of microcalcifications (n = 87) | |
| Multicentric (gap >2 cm) | 4(5%) |
| Unicentric | 83(95%) |
| Number of microcalcifications if countable (n = 87) | |
| 10 | 4(5%) |
| >10 | 83(95%) |
| Mammographic appearance of abnormalities other than microcalcifications (n = 38) | |
| Asymmetry | 1(3%) |
| Density | 32(84%) |
| Star lesion | 1(3%) |
| Distortion of architecture | 4(10%) |
| E.P.W.G. classification (n = 115) | |
| Grade 1 | 19(17%) |
| Grade 2 | 52(45%) |
| Grade 3 | 44(38%) |
| Van Nuys classification (n = 115) | |
| Grade 1 | 27(23%) |
| Grade 2 | 39(34%) |
| Grade 3 | 49(43%) |
Prediction models for the EPWG and Van Nuys classification for microcalcifications.
| Predicted grade | EPWG Classification | Total | Van Nuys classification | Total | ||||
| Grade 1 | Grade 2 | Grade 3 | Grade 1 | Grade 2 | Grade 3 | |||
| Grade 1 | 0 | 1 | 0 | 1 | 3 | 1 | 1 | 5 |
| Grade 2 | 8 | 32 | 12 | 52 | 6 | 23 | 8 | 37 |
| Grade 3 | 2 | 5 | 27 | 34 | 2 | 8 | 35 | 45 |
| Total | 10 | 38 | 39 | 87 | 11 | 32 | 44 | 87 |
Association between mammographic characteristics and histo-pathologcal grade according to the E.P.W.G. classification.
| Grade 1 | Grade 2 | Grade3 | ||
| Microcalcifications (n = 115) | ||||
| Yes | 10(53%) | 38(73%) | 39(89%) | 0.008 |
| No | 9(47%) | 14(27%) | 5(11%) | |
| Anormality other than microcalcifications (n = 115) | ||||
| Yes | 10(53%) | 18(35%) | 10(23%) | 0.065 |
| No | 9(47%) | 34(65%) | 34(77%) | |
| Linear microcalcifications (n = 87) | ||||
| Yes | 2(20%) | 5(13%) | 26(67%) | <0.001 |
| No | 8(80%) | 33(87%) | 13(33%) | |
| Coarse granular microcalcifications (n = 87) | ||||
| Yes | 8(80%) | 32(84%) | 32(82%) | |
| No | 2(20%) | 6(16%) | 7(18%) | 0.940 |
| Fine granular microcalcifications (n = 87) | ||||
| Yes | 5(50%) | 15(39%) | 7(18%) | |
| No | 5(50%) | 23(61%) | 32(82%) | 0.048 |
| Number of microcalcifications (n = 87) | ||||
| 10 | 2(20%) | 1(3%) | 1(3%) | |
| >10 | 8(80%) | 37(97%) | 38(97%) | 0.143 |
| Distribution of microcalcifications (n = 87) | ||||
| Cluster | 8(80%) | 23(61%) | 19(49%) | |
| Segment | 2(20%) | 15(39%) | 20(51%) | 0.163 |
Figure 1Correlation between mammographic and pathological size of mammographic microcalcifications (n = 87). Correlation coefficient (r) = 0.89 (p < 0.001), equation for the fit: PS = 0.55+0.86*MS (regression coefficient 0.86, p < 0.001)
Figure 2Correlation between mammographic and pathological size of an abnormality other than microcalcifications (n = 38). Correlation coefficient (r) = 0.77 (p < 0.001), equation for the fit: PS = 1.24+0.80*MS (regression coefficient 0.80, p < 0.001)