| Title |
Predictive value of primary tumor parameters using 18F-FDG PET/CT for occult lymph node metastasis in breast cancer with clinically negative axillary lymph node
|
|---|---|
| Published in |
Annals of Nuclear Medicine, August 2018
|
| DOI | 10.1007/s12149-018-1288-2 |
| Pubmed ID | |
| Authors |
Jang Yoo, Bom Sahn Kim, Hai-Jeon Yoon |
| Abstract |
This study aimed to demonstrate the clinical significance of total lesion glycolysis (TLG) of primary breast cancer using 18F-FDG PET/CT to predict axillary lymph node (ALN) metastasis in invasive ductal breast cancer (IDC) with a clinically negative axillary lymph node (cN-ALN). 135 patients, newly diagnosed with IDC with CN-ALN between July 2016 and October 2017, were retrospectively enrolled. We estimated primary tumor PET/CT parameters including the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and TLG, as well as clinicopathologic findings. All patients received breast surgery followed by pathologic axillary lymph node examination. Of the 135 patients, 31 (23.0%) were diagnosed with pathologically proven metastatic ALN. In univariate analysis, SUVmax, MTV, and TLG of the primary breast tumor were correlated with metastatic ALN along with tumor size, lymphovascular invasion, CD34, and D2-40. On multivariate analysis, TLG (> 5.74, p = 0.009) had independent significance for predicting ALN metastasis in IDC with cN-ALN. We demonstrated that TLG of primary tumors can be useful in predicting pathologic ALN metastasis in IDC patients with cN-ALN. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 12% |
| Student > Bachelor | 2 | 12% |
| Student > Master | 2 | 12% |
| Researcher | 2 | 12% |
| Professor > Associate Professor | 2 | 12% |
| Other | 1 | 6% |
| Unknown | 6 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 41% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Neuroscience | 1 | 6% |
| Computer Science | 1 | 6% |
| Unknown | 7 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 November 2018.
All research outputs
#13,928,657
of 23,099,576 outputs
Outputs from Annals of Nuclear Medicine
#254
of 637 outputs
Outputs of similar age
#175,888
of 331,391 outputs
Outputs of similar age from Annals of Nuclear Medicine
#7
of 18 outputs
Altmetric has tracked 23,099,576 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 637 research outputs from this source. They receive a mean Attention Score of 2.4. This one has gotten more attention than average, scoring higher than 60% of its peers.
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We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.