When a fine needle aspiration comes back as QNS it means the patient waits longer for a diagnosis, the care team schedules a repeat procedure, and the lab logs another entry in its quality metrics. Industry estimates put FNA QNS rates at 15-25%, depending on specimen type and site experience. For a lab running any meaningful FNA volume, that is not a rare event. It is a recurring line item, and one with consequences that extend well past the lab bench. For example, for a lab processing 5,000 FNAs annually, a 20% QNS rate equates to 1,000 failed diagnoses.
What “Quantity Not Sufficient” Actually Means
A specimen can contain diagnostic material and still be called QNS if that material does not survive the steps between aspiration and slide.
Conventional cell block preparation methods, including plasma-thrombin technique and agarose-based reagents like HistoGel, rely on multiple transfer and centrifugation steps. Each step is an opportunity for cellular material to be lost through decantation, cassette leakage, or tissue loss during microtomy. Reported cell loss with conventional cell block processing runs as high as 33%.¹ Even a modified plasma-thrombin protocol designed specifically to reduce centrifugation-related loss still returned insufficient material in 18% of cases in a method-comparison study, underscoring how much loss is built into the standard technique it was designed to improve on.
Why QNS Is a Systemic Problem, Not an Individual One
It is tempting to treat QNS as a technique issue: a less experienced cytotechnologist, an unusually paucicellular sample, an off day. But the data suggests otherwise. Cell loss during conventional processing is largely structural. It happens because of how cells disperse through a cell block, not because of any single person’s skill.
This shows up in a few consistent ways across labs:
- Technician-dependent variability. Techniques like plasma-thrombin are highly sensitive to individual handling, which makes QNS rates difficult to standardize or predict across a cytology program.
- Blind sectioning. In a conventional cell block, cellular material disperses throughout the block rather than concentrating in a predictable location. A technician sectioning the block is working without knowing exactly where the diagnostic material sits, which means they may cut past it or stop short of it.
- Compounding loss across steps. Each transfer, centrifugation, and embedding step adds its own loss. By the time a block reaches the microtome, the cumulative effect can be substantial even when the original aspirate was cellular.
None of this is a reflection of the people doing the work. It is a reflection of the tools they are working with.
The Cost of a QNS Result
A QNS call is rarely the end of the story. It is usually the start of a second one:
- For the patient, a QNS result often means a second procedure, additional time off work, added anxiety, and a delayed treatment path.
- For the referring physician, repeat biopsies affect patient experience and can reflect on their own diagnostic yield, even when the cause sits downstream in processing.
- For the lab, QNS rates show up in quality metrics, and repeat procedures carry real cost in staff time, reagents, and scheduling.
- For trial sponsors, a QNS result on a biomarker-driven or rare-disease trial can mean a failed eligibility criterion, not just a scheduling delay. Every specimen represents a patient who consented, prepared, and waited. In precision oncology, a paucicellular biopsy may yield just enough material for a morphologic read before running out ahead of the IHC or NGS panel that determines treatment eligibility. That loss isn’t recoverable with a reschedule. For many patients, it closes the door entirely.
The 15-25% QNS range is not evenly distributed across specimen types. Paucicellular aspirates, small nodules, and low-volume trial biopsies tend to carry disproportionate risk, which is exactly where the cost of a repeat procedure is highest.
What a Lower QNS Rate Actually Requires
Reducing QNS requires rethinking where cell loss happens in the workflow rather than asking technicians to be more careful with the same tools.
Most conventional methods rely on centrifugation to concentrate cells, followed by decanting off the supernatant, a step that discards fluid but also carries away some fraction of the cellular material suspended in it. Vacuum filtration offers a different approach: cells are drawn through a filter directly into a sectionable matrix, which eliminates or reduces the decanting step depending on sample type. In paucicellular specimens like FNAs, material can be filtered directly without prior centrifugation, removing the loss point entirely. In more cellular samples, some concentration may still be needed first, but the matrix approach ensures that once cells are captured, they are concentrated into one location rather than dispersed through a block, making sectioning predictable rather than a guess.
Research comparing preparation methods has found that this kind of filtration-and-matrix-capture approach can reduce cell loss from roughly a third of the specimen down to the low single digits, while increasing the proportion of sections with diagnostic value from under 15% to over 90%.¹ That is the kind of gap that shows up not as an incremental improvement, but as a fundamentally different QNS rate.
Lumea has been exploring this problem directly with the CytoPod System, which uses this vacuum filtration and matrix-capture approach to concentrate cellular material into a single, predictable location so QNS is no longer the default outcome for paucicellular specimens. You can read more about the approach on the CytoPod page.
QNS does not have to be the cost of doing cytology. It is the cost of the tools currently used to do it.
¹Pop et al., “A new method for preparing cell blocks from paucicellular aspirates” (n=16 clinical sample comparison evaluating CytoPod matrix yield vs. conventional cell block preparation).
²Aisagbonhi O, Birungi A, Atwine R, et al. Modified plasma-thrombin method of cell block preparation for fine-needle aspiration biopsies in resource-limited settings. Am J Clin Pathol. 2018;150(2):137-145. https://academic.oup.com/ajcp/article/150/2/137/5035151
