ConductVision Organoid Monitor

Tumor organoids, monitored 24/7

In a pilot, ConductVision counts your tumor organoids and follows each one's growth, growth arrest and regrowth, from images taken every 5 to 15 minutes.

Plan a pilotWhat a pilot records
Brightfield image of rectal cancer organoids of varied sizes, most of them solid and rounded, a few large and irregular, and others out of focus at different depths.
Adapted from Yu et al. 2025 · CC BY 4.0

24/7 monitoring

What a pilot records for each tumor organoid

ConductVision records each measure for every visible organoid, keyed by plate, well, organoid ID and time.

MeasureWhat it showsHow often
Every organoid
Area
A brightfield image of spheroids, each outlined in yellow by OrganoSeg, a published tool, above three of them numbered beside the area OrganoSeg measured for each.
Adapted from Borten et al. 2018 · CC BY 4.0

The projected area of each organoid, with its longest and shortest diameters

Every 5 to 15 minutes
Growth rate
Phase-contrast images of an untreated cyst in a polycystic kidney disease organoid on days 1, 3, 7 and 14, growing from a small sphere to one that fills the frame.
Adapted from Gulieva et al. 2025 · CC BY 4.0

How fast each organoid grows or shrinks, per hour and per day

Every 5 to 15 minutes
Shape
Brightfield image of colorectal cancer organoids, round and irregular, each outlined in yellow by OrganoSeg, a published tool.
Adapted from Borten et al. 2018 · CC BY 4.0

How round, long or irregular each outline is

Every 5 to 15 minutes
Movement
Time-lapse microscope image of chicken embryo intestinal organoids in a gel, with dashed lines tracing how far six of them moved during the first day of culture.
Adapted from Pierzchalska et al. 2019 · CC BY 4.0

How far and how fast each organoid moves, where organoids are free to move

Every 5 to 15 minutes
Fusion
Time-lapse microscope images of chicken embryo intestinal organoids in a gel, in which two organoids, outlined in red and yellow, move together and fuse into one.
Adapted from Pierzchalska et al. 2019 · CC BY 4.0

Two organoids joining into one, with both parent IDs kept

Each time it happens
Fragmentation
Brightfield images of airway organoids 0, 24 and 48 hours after infection with a respiratory virus, breaking up over that time, beside mock-infected organoids at 48 hours.
Adapted from Stroulios et al. 2022 · CC BY 4.0

Organoids splitting or shedding pieces, each piece keeping its parent ID

Each time it happens
Structural collapse
Phase-contrast images of one polycystic kidney disease organoid cyst given 30 µM everolimus on days 0, 1, 3 and 14, shrinking from a round cyst to a small dark mass by day 1.
Adapted from Gulieva et al. 2025 · CC BY 4.0

A sudden loss of area, roundness or boundary, with a clip of the change

Each time it happens
Tumor organoids
Count
A microscope image of organoids, some of them touching, beside the same field with each organoid filled in its own color by OrganoID, a published tool, the touching ones included.
Adapted from Matthews et al. 2022 · CC BY 4.0

How many visible organoids each well holds, as they form, fuse and break up

Every 5 to 15 minutes
Treatment response
Live-imaging pictures of human pancreatic cancer organoids, untreated and given 1000 nM gemcitabine, at 0 and 100 hours, where the treated well holds fewer organoids and more debris.
Adapted from Ferreira et al. 2024 · CC BY 4.0

Growth arrest, shrinkage and response latency after a treatment, normalized to each organoid's own baseline and your controls

Every 5 to 15 minutes
Regression and regrowth
Brightfield images of colorectal cancer organoids grown from a patient-derived cell line, just after SN-38 treatment and on regrowth days 2, 4 and 8, growing back without the drug.
Adapted from Nakano et al. 2025 · CC BY 4.0

Regression, regrowth and recurrent growth after a first response

Every 5 to 15 minutes
Protrusions and gross invasion
Differential interference contrast time-lapse images of one neuroblastoma organoid from a patient-derived xenograft at 0, 24, 48 and 96 hours, as it sends branching strands into the gel.
Adapted from Gavin et al. 2021 · CC BY 4.0

Large protrusions, and gross invasion into the surrounding gel, where the camera resolves them

Every 5 to 15 minutes
Differences between organoids
Line chart of area against time for four organoids over 92 hours, each growing at its own pace.
Adapted from Matthews et al. 2022 · CC BY 4.0

The share of organoids growing, stable and shrinking in each well, beside the well average

Every 5 to 15 minutes

When a fusion, fragmentation or structural collapse begins, the camera images that well every minute until the change ends. Fragmentation and structural collapse describe what the camera sees in each organoid's outline, not whether its cells are alive.

Beyond the camera

What needs higher magnification or a dye

  • Individual cells
  • Cell division (mitosis)
  • Single cells invading the gel
  • Molecular markers
Everything a camera cannot measure

Evidence

What published studies found in tumor organoids

Other research groups measured these in microscope images of patient-derived organoids.

Brightfield image of cystic pancreatic cancer organoids in an extracellular matrix dome, each filled with a color where the analysis outlined it as one object.
Adapted from Deben et al. 2023 · CC BY 4.0

Count and area without dyes

OrBITS monitored patient-derived organoids over time at all stages of growth from brightfield images alone, without a fluorescent dye.1 Its organoid counts and areas correlated strongly with Hoechst nuclear staining over a broad range of sizes.1

Chart of a growth rate metric for two pancreatic cancer organoid lines across gemcitabine doses, high at the lowest doses and below zero at the highest.
Adapted from Deben et al. 2023 · CC BY 4.0

Growth rate

Deben and colleagues, whose OrBITS study included two genetically validated pancreatic cancer organoid lines, advise a growth rate-based metric to measure organoid drug responses more accurately and consistently.1

Live-imaging pictures of mouse pancreatic cancer organoids, untreated and given 1000 nM gemcitabine, at 0 and 100 hours, where the treated well holds fewer organoids and more debris.
Adapted from Ferreira et al. 2024 · CC BY 4.0

Stalled or shrinking organoids

To tell cytostatic from cytotoxic responses, Deben and colleagues added a fluorescent dye that marks damaged cells to their brightfield imaging.1 A pilot uses no dyes, so it reports when an organoid stalls, shrinks, fragments or collapses, but cannot say whether the drug stopped its growth or killed it.

Microscope images of colorectal cancer organoids at 52, 82, 88 and 94 hours of culture, in which a collapsed organoid swelled again and fused with its neighbor into one.
Adapted from Yan et al. 2024 · CC BY 4.0

Fusion

In OrBITS time-lapses, organoid counts dropped over time as organoids merged or fused.1 A pilot gives each fused organoid a new ID that records both parents, so the count stays traceable.

Brightfield images of rectal cancer organoids from one line on day 15 after 0, 4, 8 and 16 Gy of X-rays, smaller and more scattered at the higher doses.
Adapted from Yu et al. 2025 · CC BY 4.0

Structure scored by an observer

Yu and colleagues imaged rectal cancer organoids every 3 days for 15 days after X-ray doses, and a trained observer scored each structure as complete or disrupted.2 The score judged the integrity of each structure, independent of organoid size.2

Transmitted-light stills from three days of time-lapse imaging of patient-derived colorectal cancer organoids with mutant KRAS, one given vehicle, which grew, and one given afatinib and selumetinib, which kept its size.
Adapted from Verissimo et al. 2016 · CC BY 4.0

Label-free drug responses

Larsen and colleagues optimized a pan-cancer tumor organoid platform on cultures from over 1,000 patients.3 Their neural network measured tumor organoids' drug responses from label-free light-microscopy images, across solid cancers.3

Transmitted-light stills from three days of time-lapse imaging of patient-derived colorectal cancer organoids, one given vehicle, which grew, and one given afatinib and selumetinib, which lost its smooth outline.
Adapted from Verissimo et al. 2016 · CC BY 4.0

Each organoid's response

Spiller and colleagues tracked how individual patient-derived tumor organoids responded to drugs, in brightfield images taken at several time points without vital dyes.4

Camera specification

The cameras a pilot uses

Microscope images of the same patient-derived intestinal organoids when forskolin was added and one hour later, when their lumens had filled with fluid.
Adapted from Lefferts et al. 2024 · CC BY 4.0

Around the clock

  • A full stack of focal planes for every well, every 5 to 15 minutes
Brightfield image of mouse pancreas organoids, each with one large lumen, averaged from ten focal planes taken at 1.29 µm per pixel.
Adapted from Hof et al. 2021 · CC BY 4.0

Image

  • 2 µm or less per pixel
Human intestinal organoids in transmitted light, the dye-free imaging that OrgaSegment, a published tool, was built to analyze.
Adapted from Lefferts et al. 2024 · CC BY 4.0

Light

  • Brightfield LED light, with no dyes or labels
Images of one human cortical organoid taken inside an incubator at 0, 43 and 86 hours, growing larger, beside a chart of its area at each time point.
Adapted from Ly et al. 2021 · CC BY 4.0

Incubator

  • Inside your incubator, or in a chamber beside it that keeps the same conditions
Full camera specification

References

  1. Deben C, De La Hoz EC, Compte ML, et al. (2023). OrBITS: label-free and time-lapse monitoring of patient derived organoids for advanced drug screening. Cellular Oncology.
  2. Yu H, Lin C, Chen F, et al. (2025). Dose response test of patient-derived cancer organoids to irradiation. Frontiers in Oncology.
  3. Larsen BM, Kannan M, Langer LF, et al. (2021). A pan-cancer organoid platform for precision medicine. Cell Reports.
  4. Spiller ER, Ung N, Kim S, et al. (2021). Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response. Frontiers in Oncology.
  5. Borten MA, Bajikar SS, Sasaki N, et al. (2018). Automated brightfield morphometry of 3D organoid populations by OrganoSeg. Scientific Reports.
  6. Gulieva RE, Ahmadvand P, Freedman BS (2025). A novel rapalog shows improved safety vs. efficacy in a human organoid model of polycystic kidney disease. Stem Cell Reports.
  7. Pierzchalska M, Panek M, Grabacka M (2019). The migration and fusion events related to ROCK activity strongly influence the morphology of chicken embryo intestinal organoids. Protoplasma.
  8. Stroulios G, Brown T, Moreni G, et al. (2022). Apical-out airway organoids as a platform for studying viral infections and screening for antiviral drugs. Scientific Reports.
  9. Matthews JM, Schuster B, Kashaf SS, et al. (2022). OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics. PLOS Computational Biology.
  10. Ferreira N, Kulkarni A, Agorku D, et al. (2024). OrganoIDNet: a deep learning tool for identification of therapeutic effects in PDAC organoid-PBMC co-cultures from time-resolved imaging data. Cellular Oncology.
  11. Nakano K, Oki E, Yamazaki M, et al. (2025). Colorectal cancer cell line-derived organoid model with stem cell properties captures the regrowing state of residual cancer cells after neoadjuvant chemotherapy. Cell Death Discovery.
  12. Gavin C, Geerts N, Cavanagh B, et al. (2021). Neuroblastoma Invasion Strategies Are Regulated by the Extracellular Matrix. Cancers.
  13. Yan H, Wu T, Li X, et al. (2024). Establishment of the microscope incubation system and its application in evaluating tumor treatment effects through real-time live cellular imaging. Frontiers in Bioengineering and Biotechnology.
  14. Verissimo CS, Overmeer RM, Ponsioen B, et al. (2016). Targeting mutant RAS in patient-derived colorectal cancer organoids by combinatorial drug screening. eLife.
  15. Lefferts JW, Kroes S, Smith MB, et al. (2024). OrgaSegment: deep-learning based organoid segmentation to quantify CFTR dependent fluid secretion. Communications Biology.
  16. Hof L, Moreth T, Koch M, et al. (2021). Long-term live imaging and multiscale analysis identify heterogeneity and core principles of epithelial organoid morphogenesis. BMC Biology.
  17. Ly VT, Baudin PV, Pansodtee P, et al. (2021). Picroscope: low-cost system for simultaneous longitudinal biological imaging. Communications Biology.

Plan a tumor organoid pilot

Tell us about your tumor organoids, your plates, your treatments and the response you want timed.

Plan a pilotAll organoid models