Compare › NTA vs. F-MRPS
NTA vs. F-MRPS: When tracking particles by light isn’t enough.
Nanoparticle Tracking Analysis has been an important step forward from DLS — it visualizes individual particles and provides single-particle tracking data that ensemble methods cannot. For many applications, NTA is a practical and informative tool. But for biological nanoparticles, particularly extracellular vesicles, viruses, and gene therapy vectors, NTA’s reliance on light scattering creates systematic blind spots that are now well-documented in peer-reviewed literature.
F-MRPS measures particles electrically, not optically. This single difference eliminates the root cause of NTA’s limitations for biological samples — without sacrificing the single-particle resolution and fluorescence phenotyping capability that makes NTA more informative than DLS.
The comparison on this page draws on peer-reviewed data from a Johns Hopkins University study published in the Journal of Extracellular Vesicles (Arab et al., 2021) that compared four orthogonal single-particle platforms — MRPS, NTA, nanoFCM, and SP-IRIS — across both synthetic and biological EV samples.
Where the methods diverge
NTA is a genuine advance over DLS. It also has well-documented limits.
Unlike DLS, NTA tracks individual particles and delivers single-particle resolution of Brownian motion. That makes it significantly more informative for polydisperse samples. The limitations described below are not unique to any one vendor — they are inherent to the optical tracking principle that all NTA instruments share.
Head-to-head
NTA vs. F-MRPS: a direct comparison
| NTA Nanoparticle Tracking Analysis |
F-MRPS Spectradyne ARC |
|---|
View plain text data table
| Attribute | NTA | F-MRPS (Spectradyne ARC) |
|---|---|---|
| Measurement principle | Optical — single-particle tracking of scattered light via Brownian motion | Electrical + optical — direct physical sizing, simultaneous fluorescence |
| Single-particle measurement | Yes — individual particle tracking | Yes — individual particle detection and measurement |
| Small particle sensitivity | Poor — D&sup6; scaling causes systematic undercounting below ~150 nm for EVs; ~10,000x error at 65 nm (Arab et al. 2021) | High — detects particles down to 50 nm independent of optical properties. Validated against TEM |
| Size distribution accuracy | Moderate — reports false peak near 130 nm for EV samples; fails to resolve polydisperse mixtures below ~150 nm | High — power law distribution reproduced in agreement with TEM; resolves multiple populations simultaneously |
| Absolute concentration | Partial — possible but systematically low for biological particles due to detection efficiency drop-off | Yes — every particle counted; divided by precisely measured volume. No optical assumptions |
| Single-particle fluorescence | Partial — fluorescence NTA (f-NTA) available but sensitivity limited for small particles | Yes — up to 3 simultaneous channels alongside electrical sizing and concentration |
| Refractive index dependence | High — detection efficiency and sizing depend on optical contrast; low for EVs in aqueous media | None — electrical sensing is independent of optical properties |
| Sample volume | Typically 300–500 µL; concentration must be optimised | Only 3 µL required |
| MISEV compliance | Commonly used but known limitations acknowledged by MISEV guidelines | Meets MISEV guidelines for EV size and concentration reporting |
Why it matters
The NTA limitation in practice: three key application areas
The D\u00b6 detection falloff isn’t an abstract concern. In biological nanoparticle applications, it directly affects the accuracy and reproducibility of results that matter most to your research.
Peer-reviewed evidence: MRPS vs. NTA for EV characterization
Arab et al. (2021) in the Journal of Extracellular Vesicles compared MRPS, NTA, nanoFCM, and SP-IRIS for EV characterization from two cell lines. All methods except NTA reported a power-law size distribution consistent with TEM. NTA reported a peaked distribution with a mode above 100 nm \u2014 a false peak caused by detection sensitivity falloff \u2014 and undercounted EV concentrations by approximately one order of magnitude compared to MRPS and nanoFCM. The authors concluded that NTA’s sensitivity to small particles varies with sample composition in a way that is difficult to control or predict.
Read our summary of the Arab et al. study →See it for yourself
See the size distribution your NTA data is missing.
Send us your EV, LNP, or virus sample and we’ll run a free measurement on the ARC. You’ll receive the complete size distribution down to 50 nm, absolute concentration, and \u2014 where applicable \u2014 fluorescence phenotyping data. You can then directly compare the result to your existing NTA data.
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