NTDscope: A multi-contrast portable microscope for disease diagnosis
Bibliographic record
Abstract
Abstract Accurate diagnostics are essential for disease control and elimination efforts. However, access to diagnostics for neglected tropical diseases (NTDs) is hindered by limited healthcare infrastructure in many NTD-endemic regions, as well as by reliance on time- and labor-intensive diagnostic methods, such as smear microscopy. New diagnostic tools that are portable, rapid, low-cost, and meet World Health Organization (WHO) sensitivity and specificity targets are urgently needed to accelerate NTD control and elimination programs. Here, we introduce the NTDscope, a portable microscopy platform that enables point-of-care imaging and automated detection of parasites and other pathogens in patient samples. The NTDscope builds on and extends the capabilities of the LoaScope, a device that turned the camera of a mobile phone into a microscope and used on-board image processing to automatically quantify Loa loa microfilariae burden in whole blood samples. The NTDscope replaces the mobile phone of the LoaScope with a system-on-module (SOM) that enables the integration of multiple imaging modalities in a single package designed to improve robustness and expand applications. In this work, we demonstrate use of the NTDscope as a portable brightfield, darkfield, and fluorescence microscope for samples including microfilariae and helminth eggs. We also show that the device can be used to quantify molecular assays, such as a lateral flow test and a CRISPR-Cas13a-based assay. The ability to combine diagnostic capabilities of conventional microscopy with molecular assays and machine learning in a single device could expand access to diagnostics for populations in NTD-endemic areas and beyond. Author summary Neglected tropical diseases (NTDs) impact one billion of the world’s most vulnerable individuals. Diagnostics are a necessary part of NTD disease control and elimination efforts, but identifying infected individuals remains a challenge. Here we present the NTDscope, a portable multi-contrast microscope designed to diagnose multiple NTDs at the point-of-care. We show that the NTDscope can be used to detect the parasitic worm Loa loa in videos of whole blood samples and parasitic eggs in images of urine and stool samples. The NTDscope can also be used to image thick blood smears in disposable capillaries and serves as a lateral flow assay reader. In addition to brightfield and darkfield imaging, fluorescence imaging on the device enables molecular assays based on CRISPR-Cas enzymes. This portable (<1 kg), field-friendly device—tested in Cameroon, Gabon, Côte d’Ivoire, and Bangladesh—has the potential to become a platform technology that addresses diagnostic needs for multiple NTDs and could serve as a key element of decentralized healthcare in the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".