At the Chinese Academy of Sciences (CAS), the Morphology Core functions as a shared infrastructure that converts tissue into reproducible, quantitative data, supporting both discovery research and translational workflows.

Like many large research institutes, the core faces a dual reality:

• Hundreds of brightfield slides generated daily for routine histology, validation, and archiving
• A rapidly increasing demand for TSA-based multiplex immunofluorescence (mIF) to interrogate tumor immune contexture at scale

To address both needs with a single, consistent workflow, the core deployed KFBIO’s integrated brightfield–fluorescence whole-slide imaging (WSI) platform, supporting:

1. TSA multiplex immunofluorescence for tumor microenvironment (TME) profiling

2. Ultra-fast brightfield scanning for routine morphology, large-scale archiving, and dataset construction

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Scientific Background: Why TLS Matters in TME Studies

Tertiary lymphoid structures (TLSs) form at sites of chronic inflammation, including tumors. These ectopic lymphoid aggregates are composed primarily of B cells, T cells, and supporting dendritic cells, and have emerged as:

• A prognostic biomarker for overall survival in untreated cancer patients
• A predictive indicator of response to immunotherapies in solid tumors

Despite their importance, TLS assessment remains challenging. Traditional evaluation by pathologists is time-consuming and often requires additional tissue sections stained by IHC or immunofluorescence.

For a morphology core supporting multiple research groups, this creates a clear requirement:

TLS and broader TME features must be assessed with high confidence, at scale, and with a data trail that supports re-analysis, collaboration, and publication-quality output.

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The Challenge: From Manual Review to Standardized, Shareable Data

Across research teams, several bottlenecks were consistently identified:

1. Throughput limitations

Manual microscopy cannot keep pace with modern multi-project tissue pipelines. Brightfield digitization had to be fast enough to become the default, not an exception.

2. Multiplex openness—no “kit lock-in”

TSA panels evolve rapidly: antibodies, dyes, and channel combinations change frequently. The platform needed to remain open to commonly used TSA fluorophores and flexible enough for future expansion.

3. Signal fidelity for weak markers and high-plex panels

TME studies often involve dim or spatially sparse signals. Reliable quantification requires efficient filters, stable illumination, and sensitive detection—especially when comparing cohorts or batches.

4. End-to-end analysis, not just images

Beyond image capture, the core needed to support cell segmentation, co-localization, intensity quantification, and spatial statistics, transforming WSI into quantitative, publishable conclusions.

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The KFBIO Solution: A Standardized Data Engine for Morphology + Multiplex IF

Rather than treating the system as a standalone scanner, the CAS Morphology Core adopted KFBIO’s platform as a standardized data engine connecting:

sample → staining → scanning → analysis → output

1) High-speed brightfield scanning for routine scale

Using a line-scan architecture, the system is optimized for throughput:

• 15 × 15 mm at 20× in ≤15 seconds
• 40× in ≤40 seconds

This enables routine H&E and IHC digitization to support:

• High-throughput archiving and remote review
• Centralized QC and standardized annotation
• Dataset generation for computational pathology and AI research

2) TSA-ready multiplex fluorescence with open channels

The platform supports up to 10 customizable whole-slide fluorescence channels, with band selection configurable to match experimental design and future panel expansion.

Configurable full-band LED excitation allows researchers to independently tune spectral lines—balancing signal intensity and photostability across dyes.

3) High-efficiency filters for quantitative confidence

For multiplex quantification, the optical stack emphasizes spectral cleanliness:

• Chroma filter sets
• Support for customized multi-pass filters
• Transmission up to 99% with OD6 blocking, minimizing bleed-through and improving contrast

4) Sensitive sCMOS detection for weak signals

A scientific sCMOS camera provides:

• 180–1100 nm spectral response
• Up to 95% quantum efficiency at 560 nm, improving detection of dim TME and TLS-related markers

5) Precise channel alignment for co-localization

To avoid false biology caused by misregistration, the system is engineered for high repeatability:

• Referenced positioning resolution at the 20 nm level
• Multi-channel offset controlled to below one pixel, supporting reliable spatial and co-expression analyses

6) Open export for downstream analysis

To support collaboration across teams and software ecosystems, the platform enables export in common formats:

• Brightfield: KFB / TIF / SVS / DCM
• Fluorescence: KFBF / QPTIFF

This openness allows seamless integration with preferred image analysis pipelines and quantitative tools.

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Workflow in Practice: TLS-Driven TME Profiling with TSA mIF

In daily operation, TLS-focused TME studies follow a standardized path:

1. Panel design & TSA multiplex staining
   Immune compartments (B cells, T cells, APCs) are phenotyped in relation to tumor and stromal regions.
2. Whole-slide fluorescence acquisition
   Channel sets are optimized for the dyes in use, leveraging efficient filters and sensitive detection.
3. Quality control & alignment checks
   Pixel-level repeatability ensures spatial analyses reflect biology, not registration artifacts.
4. Quantification & spatial analysis
   Cell segmentation, co-localization, intensity metrics, and spatial statistics convert TLS observations into comparable metrics across samples and cohorts.

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Why This Matters for a Morphology Core

By unifying ultra-fast brightfield digitization with an open, high-efficiency multiplex fluorescence workflow, the CAS Morphology Core gains a single platform that supports both daily routine throughput and advanced immune spatial biology.

More importantly, it enables what a modern morphology center is ultimately responsible for:

Standardized, reproducible data capture that can be shared, re-analyzed, and trusted—across projects, teams, and time.

KF-FL-005 KF-FL-020 KF-FL-120 KF-FL-400