Abstract
Plain Language Summary
This Letter to the Editor discusses recently published evidence about a portable device that measures electrical properties in breast tissue. The device is not intended to diagnose breast cancer or replace mammography. Instead, it may help identify which women should be referred sooner for additional breast imaging when access to diagnostic services is limited.
The recent publication of the multicenter cross-sectional study evaluating the performance of JULIETA 1 —a portable bioimpedance spectroscopy device—offers a timely opportunity to examine the role that technologies of this kind might play in settings where access to diagnostic evaluation remains persistently inadequate. This letter presents no new data; rather, it contextualizes the published evidence within the public health reality of breast cancer in settings where operational barriers—not diagnostic uncertainty—remain the primary obstacle to timely care. The question at the center of this commentary is not whether JULIETA can replace mammography, but whether a non-invasive tool of this kind can help identify, earlier and more systematically, the women who need to move forward along the diagnostic pathway.
This discussion is especially pertinent for breast cancer, where in many settings the core problem is not the scale of disease but the persistent failure to translate early detection into timely diagnostic follow-up and treatment. Worldwide, breast cancer is the most commonly diagnosed malignancy in women and the leading cause of cancer death among them, with 2.3 million new cases and 666,103 deaths recorded in 2022. 2 This burden falls disproportionately on low- and middle-income countries, where late-stage diagnosis is more common and access to timely treatment remains limited. 2 The prognostic implications are well established: five-year relative survival approaches 100% at stage I but falls to approximately 31% at stage IV. 3 The situation in Colombia reflects this pattern clearly. According to the Cuenta de Alto Costo, with data as of 31 October 2025, breast cancer accounted for 18.03% of all prioritized cancers within the national insurance system; only 44.47% of solid tumors had been staged at diagnosis, and among those, just 54.82% were classified as stages I–II, while mammography coverage stood at 38%. 4 These figures point to a bottleneck that is largely operational, driven by structural and logistical barriers that limit effective, timely engagement with the diagnostic pathway.
Against this backdrop, complementary approaches such as bioimpedance spectroscopy merit serious consideration. The biological basis is established: prior literature has documented measurable differences in the electrical properties of benign and malignant breast tissue.5,6 Building on this, the multicenter study in question evaluated JULIETA against mammography as the reference standard, collecting data prospectively across four Colombian cities. After a pre-specified curation protocol, the final analysis included 673 breasts from 469 women. The hierarchical algorithm achieved a sensitivity of 73% (95% CI: 61–85), a specificity of 76% (95% CI: 67–85), and a negative predictive value of 82.1% for distinguishing BI-RADS 1–2 from BI-RADS ≥3 findings. 1 Considered within a prioritization framework—rather than as a definitive diagnostic instrument—these results support continued investigation of bioimpedance spectroscopy as a complementary resource in settings where access to evaluation remains the principal bottleneck.
Beyond these performance metrics, the study furnishes important evidence on the operational feasibility of this approach under routine clinical conditions. JULIETA is portable, radiation-free, and painless, with a short application time and no serious adverse events reported during the evaluation. 1 These characteristics matter because the device’s potential utility depends not only on its performance but on whether it can realistically be integrated into settings where access is the limiting factor. It should be noted, however, that the study was conducted at urban diagnostic centers with established mammographic infrastructure, and the analytical dataset was reduced by missing variables. Validation in a broader range of clinical settings remains necessary.
The recently published paper 1 provides clinical evidence that JULIETA can be meaningfully evaluated as a prioritization-support tool within the breast cancer diagnostic pathway. Its value, in the context examined, does not lie in replacing established diagnostic modalities—it lies in addressing a specific and largely operational gap: the systematic risk-stratification of patients to optimize the diagnostic queue in settings with limited mammographic throughput. We regard this as the principal contribution of the published work, and the basis on which JULIETA warrants continued clinical evaluation in settings where access remains a decisive determinant of diagnostic opportunity.
Footnotes
Acknowledgements
D.G. leads artificial intelligence development at Salva Health; M.A.N. is a Clinical Specialist at Salva Health; S.L. is the Chief Technology Officer at Salva Health; and V.G. is an R&D Engineer at Salva Health. Salva Health is the company developing JULIETA.
Ethical Considerations
This Letter does not report new individual-level data; therefore, ethics approval and informed consent were not required.
Consent to Participate
All studies cited were conducted in accordance with institutional and national ethical standards and, where applicable, received ethics approval and informed consent.
Consent for Publication
This Letter does not include identifiable individual data, images, or videos.
Author Contributions
Provided via the CRediT taxonomy in the submission system.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: D.G. leads artificial intelligence development at Salva Health; M.A.N. is a Clinical Specialist at Salva Health; S.L. is the Chief Technology Officer at Salva Health; and V.G. is an R&D Engineer at Salva Health. Salva Health is the company developing JULIETA.
Data Availability Statement
Data sharing is not applicable to this article as no new datasets were generated or analysed. Any supporting information is available from the cited sources or from the corresponding author upon reasonable request.
