Assessing the value of hepatic arterial phase CT imaging in patients with breast cancer.
Bibliographic record
Abstract
5 Background: Hypervascular liver metastases, classically seen in melanoma and other cancers, may be best seen on a hepatic arterial phase (HAP) CT and possibly missed on the standard portal venous phase (PVP). Breast cancer sometimes produces hypervascular liver metastases, but the incidence of this is not well established. Hence, some centers perform biphasic liver CT (HAP + PVP) as standard protocol in breast cancer patients, while others do not. Our center does not include HAP in this patient population; although, it is sometimes protocolled with HAP as per radiologist preference. We sought to determine if the detection for presence or absence of liver metastases is significantly affected by the addition of HAP in breast cancer. Methods: This retrospective study was conducted using a custom search on our Picture Archiving and Communication System for all female patients who received a biphasic liver CT (HAP + PVP) from Mar 2013 - Mar 2015. Inclusion criteria included known breast cancer, liver metastases described on CT report, and follow-up imaging to confirm the finding. A total of 25 CT studies met inclusion criteria. Results: 14/25 (56%) studies demonstrated typical non-hypervascular hepatic metastases. 11/25 (44%) demonstrated hypervascular hepatic lesions. Of these latter, 4/25 (16%) represented hypervascular metastases, while 7/25 (28%) pertained to indeterminate arterial-enhancing lesions called suspicious by the reporting radiologist. Further imaging including MRI, ultrasound, and follow-up CT were recommended in these indeterminate suspicious lesions, all of which confirmed benign entities. Of the 18 studies with true hepatic metastases, the presence of metastatic disease was detectable on the PVP in 18/18 (100%, P< .0001) regardless of the metastases’ hypervascular status. Conclusions: We found hypervascular metastases to be present in 22% (4/18; CI95 [3-41%]) of breast cancer patients with true liver metastases. However, the detection for the presence of hepatic metastases was not improved with the addition of HAP. The HAP instead led to detection of more indeterminate but ultimately benign entities of no clinical significance, thus resulting in unnecessary imaging and arguably greater patient anxiety.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".