Evidence map›Paper›PMID 39838990›Full record

ArticleQuantitative imaging in medicine and surgery2025

Image-guided biopsy of clinically occult nipple lesions: techniques and learning points.

Lijuan Jasmine Chan, Haiyuan Shi

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Lijuan Jasmine ChanDepartment of Radiology, Changi General Hospital, Singapore, Singapore.ORCID https://orcid.org/0000-0002-0526-1643
Haiyuan ShiDepartment of Radiology, Changi General Hospital, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Percutaneous biopsy is the standard of care for breast lesions, except nipple lesions which are primarily biopsied by excision due to perceived risks of pain and bleeding. However, excisional biopsy of nipple lesion inevitably leads to disfigurement and possible loss of the nipple-areolar complex (NAC), highlighting the need for minimally invasive biopsy techniques. We present our experience of seven patients who underwent ultrasound-guided core biopsy or vacuum-assisted biopsy (VAB) for sampling of clinically occult nipple lesions. All patients tolerated the biopsy procedures well with minimal to mild pain. A patient was complicated by a subcentimetre skin laceration which was sutured with good wound healing and cosmesis. Radiopathological concordance was achieved in all patients. Five out of 7 patients did not require further surgical management after biopsy, avoiding the unnecessary disfigurement from conventional excisional biopsy of nipple. The remaining two patients were diagnosed with pre-malignant lesions and further surgical treatment was performed. This study highlights the important pre-procedural preparation, biopsy techniques and learning points derived from our experience. Learning points that increase the efficacy of obtaining suitable tissue samples, such as enhancing lesion visualisation, appropriate biopsy needle selection and optimising analgesia were discussed. Potential complications and common pitfalls, such as mimics of nipple calcifications, were also included. In conclusion, image-guided percutaneous biopsy techniques are feasible minimally invasive alternatives to excisional biopsy of the nipple.

Indexed as

biopsyNipple lesionpercutaneousultrasound-guided

Identifiers

PMID39838990
PMCPMC11744165

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.