| Literature DB >> 30714952 |
Annika Bach1, Clarissa Hameister1, Torsten Slowinski2, Ernst Michael Jung3, Anke Thomas4, Thomas Fischer5.
Abstract
BACKGROUND: Besides mammography, breast ultrasound is the most important imaging modality for women with suspected breast cancer. New software tools bear high potential for improved detectability and specification of malignant breast lesions.Entities:
Keywords: ASQ; B mode; BI-RADS; Ultrasound; breast cancer; breast lesion; breast neoplasms; diagnostic imaging; halo; peripheral rim; peripheral zone; sonography
Mesh:
Year: 2019 PMID: 30714952 PMCID: PMC6700716 DOI: 10.3233/CH-180484
Source DB: PubMed Journal: Clin Hemorheol Microcirc ISSN: 1386-0291 Impact factor: 2.375
Fig.1(A–D): Fibroadenoma without halo sign (A), small invasive breast cancer showing a clear surrounding halo (B), analysis of tumour in B using ImageJ (C), and a big, invasive breast cancer showing halo sign without an increased rim width in relation to halos of smaller breast cancers like in A (D).
Patient characteristics
| No. | Percentage | No. | Percentage | ||
| Total population | 37 | 100% | 37 | 100% | |
| Age, median (SD), years | 59±14,5 | Her2-neu expression | |||
| Age distribution, years | low | 22 | 59% | ||
| 18–30 | 0 | 0% | moderate | 4 | 11% |
| 31–45 | 7 | 19% | high | 4 | 11% |
| 46–60 | 12 | 32% | none | 2 | 5% |
| >60 | 18 | 49% | not available | 5 | 14% |
| Type of breath cancer | Proliferaion index Mib-1 | ||||
| NST | 29 | 78% | up to 25% | 28 | 76% |
| ILC | 7 | 19% | 25–50% | 4 | 11% |
| Other | 1 | 3% | 50–75% | 2 | 5% |
| T-Stage – tumor size | over 75% | 2 | 5% | ||
| T1 | 14 | 38% | not available | 1 | 3% |
| T2 | 9 | 24% | Hormone receptor status | ||
| T3 | 1 | 3% | ER status | 27 | 73% |
| T stage not available | 13 | 35% | PR status | 23 | 62% |
| N-Stage – nodal metastasis | Histologic sum score | ||||
| N0 | 12 | 32% | 4 | 2 | 5% |
| N1 | 4 | 11% | 5 | 0 | 0% |
| N2 | 3 | 8% | 6 | 16 | 43% |
| N3 | 1 | 3% | 7 | 3 | 8% |
| N stage not available | 13 | 35% | 8 | 10 | 27% |
| Grading | 9 | 4 | 11% | ||
| G1 | 2 | 5% | Tumor diameter (surgical specimen) | ||
| G2 | 15 | 41% | up to 2 cm | 14 | 38% |
| G3 | 7 | 19% | over 2 cm | 8 | 22% |
| Not available | 13 | 35% | over 4 cm | 2 | 5% |
| Lymphangioinvasion | 5 | 14% |
Fig.2Distribution of halo-to-lesion ratios derived from B-mode images and ASQ maps.
Fig.3Diagram of halo-to-lesion ratios derived from ASQ maps for different tumor sizes – the halo does not increase in proportion to tumor size but appears to have a fairly constant width.
Correlation of halo-to-lesion ratios derived from ASQ maps and B-mode images with different prognostic markers including Pearson correlation coefficients
| Halo-to-lesion ratio in B-mode | N-stage | Lymphangio-invasion | |
| Halo-to-lesion ratio in ASQ | 0.528* | –0.017 | 0.323** |
| Halo-to-lesion ratio in B-mode | –0.092 | –0.145 |
Pearson correlation coefficient. *Correlation significant at 0.01 (two-tailed). **Two-tailed significance of correlation at p = 0.051.
Fig.4Distribution of halo-to-lesion ratios for tumors with and without lymphangioinvasion in B-mode images (A) and ASQ maps (B).
Fig.5ROC curves of halo-to-lesion ratios derived from B-mode images (A) and ASQ maps (B) for predicting lymphangioinvasion of malignant breast lesions.
Fig.6Distribution of halo-to-lesion ratios for N-stages 0 to 2 derived from B-mode images (A) and ASQ maps (B).