Simply revolutionizing the way cancer cells are being detected during a cancer surgery
Seeing the unseen
CHAMP Microscope™ is a quick and user-friendly solution providing medical doctors with accurate information about the surgical margin during cancer surgery. UV-laser is used to image the surface of freshly excised thick tissue samples. The specific wavelength chosen can generate rich endogenous contrast between cell nuclei and cytoplasm, providing a solid foundation for CHAMP to visualize individual cells without tissue slicing and chemical staining.
Pushing the limits of virtual staining
Deep-CHAMP™ is a semi-supervised deep learning algorithm that virtually stains grayscale CHAMP images into highly accurate histological images that simulate images obtained in the conventional one-week comprehensive report. By virtually staining the grayscale CHAMP images into the classical purplish H&E stained images typically used in clinical pathology, no additional training is required for pathologists since they do not need to change the way they interpret and diagnose patients.
Enabling on-site diagnosis inside the surgical theatre
95% similarity between Deep-CHAMP images and the clinical gold standard
Reducing diagnostic time from 30 minutes down to 3 minutes
Cancer margin assessment
Not knowing whether all cancer cells have been successfully excised from a patient during surgery is a problem cancer surgeons have recognized for many years. Frozen sectioning remains to be a key procedure for intraoperative surgical margin assessment. Such a procedure requires the tissue specimen to be processed and labeled which has a negative impact on the tissue properties, thus significantly reducing the quality of the histological images. It is no secret that images of a lower quality make it more difficult for pathologists to give an accurate diagnosis.
In one out of five cases, there is a discrepancy between the intraoperative testing results and the post pathological histopathology. If traces of cancer are found at the surgical margin, patients have to undergo a re-excision surgery.
Grayscale-CHAMP image showing metastatic cancer cells found in the lymph node. Invasive micropapillary carcinoma (IMPC), a rare variant of invasive ductal carcinoma (IDC); cancer cell cluster.
Re-excision surgeries is not a sustainable practice since it increases the burden of the healthcare system. Hospitals have already spent tons of clinical resources to tackle this issue, and the problem is likely to grow since the number of estimated cancer surgery procedures will increase by 5 million in 2040 . Pathologists and surgeons genuinely need a solution that can generate high-resolution images rapidly during surgery and provide them with accurate information on the cancer margin.
PhoMedics brings them a solution that challenges the status quo, providing intraoperative pathological information without the need for any tissue processing or labeling. The potent combination of hardware and software can give medical doctors precisely the information that they need, whenever they need it. The images on the right show how our CHAMP images can visualize metastasized cancer in just three minutes.
Virtually stained using Deep-CHAMP™ showing metastatic cancer cells found in the lymph node, Invasive micropapillary carcinoma (IMPC), a rare variant of invasive ductal carcinoma (IDC); cancer cell cluster
Breakthrough in thick tissue imaging
Breaking the conventional trade-off: There is a well-known trade-off between the field of view (FOV), spatial resolution, and depth of focus (DOF) in conventional microscopy. In simple terms, it is difficult to capture a large area without sacrificing some of the resolutions. Fresh tissue samples excised by surgeons typically have a rough surface and can be relatively large in size. Such a surface makes it hard to use a high magnification objective lens with its shallow DOF and restricted FOV to rapidly capture high-resolution images over a large tissue surface.
CHAMP Microscope™ interior
Computational High-Throughput Autofluorescence Microscopy by Pattern Illumination (CHAMP)
CHAMP is a non-invasive imaging technology that adopts ultraviolet (UV) laser to image the surface of freshly excised tissue. A specific wavelength of ultraviolet light was chosen to generate intrinsic signals that contain valuable information such as the cell's morphology and biomolecular properties. The ability to capture the shape and distribution of the cells made it possible for pathologists to identify abnormalities in specimens, which are the tell-tale signs of diseases such as cancer.
The depth of focus is increased using a low-magnification objective lens (LMOL) and, therefore, grants CHAMP a higher tolerance towards the sample's surface roughness. Meanwhile, LMOL provides a larger field of view which reduces the tissue scanning time. However, the resolution of the cellular images is limited by the small numerical aperture (NA) in LMOL. In light of that, PhoMedics adopted pattern illumination to modulate and retrieve high-frequency signals, allowing the reconstruction of high-resolution images and thus, breaking the conventional trade-off between depth of focus, the field of view, and spatial resolution.
By utilizing the synergistic combination of UV-light, LMOL, and pattern illumination, our CHAMP Microscope™ is capable of capturing high-resolution cellular images within 3 minutes.
Designed for optimization
All our solutions are developed and designed with the users in mind. A human-centered design approach is adopted to understand how end-users genuinely interact with our technology. Our vision is that the users' journey should be as simple as possible and generate the best results with only minimal training required for operation.
Breast cancer is the most common cancer type among females. According to the Global Cancer Observatory, over 2,2 million women were diagnosed with breast cancer in 2020 . There are three primary types of breast cancer, invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and ductal carcinoma in situ (DCIS). Margin visualization is a common element during breast-conserving surgeries (BCS), accounting for 44,5% of all breast cancer surgeries in the United States .
Grayscale-CHAMP image showing breast tissue structure. (A) Adipose Tissue. (D) Duct. (L) Lobule. (S) Stroma.
A virtually stained H&E image transformed from a grayscale-CHAMP image. (A) Adipose Tissue. (D) Duct. (L) Lobule. (S) Stroma.
A real H&E image from the corresponding region. (A) Adipose Tissue. (D) Duct. (L) Lobule. (S) Stroma.
Lung cancer is one of the most deadly cancer types among both men and women. The two primary types of lung cancer are Non-Small Cell Lung Cancer (NSCLC) and Small Cell Lung Cancer (SCLC). Patients diagnosed with an early-stage NSCLC are likely to undergo a surgery as a preferred treatment option .
A grayscale-CHAMP image of a large-cell carcinoma tissue. (F) Fibrous tissue (most likely caused by desmoplasia). (L) Lymphocytes surrounding cancer cells. (C) Cancer cells from large cell carcinoma.
A virtually stained H&E image transformed from a grayscale-CHAMP image. (F) Fibrous tissue (most likely caused by desmoplasia). (L) Lymphocytes surrounding cancer cells. (C) Cancer cells from large cell carcinoma.
A real H&E stained image from the corresponding region. (F) Fibrous tissue (most likely caused by desmoplasia). (L) Lymphocytes surrounding cancer cells. (C) Cancer cells from large cell carcinoma.
The PhoMedics research team has been working closely with experienced medical doctors, surgeons, and pathologists during the development phase of CHAMP Microscope™. Their opinions and feedback are invaluable and make it possible to create solutions that fit their needs. We would not be where we are today without our research and clinical collaborating hospitals and their dedicated staff. We want to highlight their contribution and say thank you for a great partnership that will hopefully continue for many years to come.
Queen Mary Hospital
Prince of Wales Hospital
North District Hospital
 Perera S, Jacob S, Wilson B et. Al. Global demand for cancer surgery and an estimate of the optimal surgical and anesthesia workforce between 2018 and 2040: a population-based modeling study
Lancet Oncol. 2021 vol 22, Issue 2
 Zhang, Y., Kang, L., Wong, I.H.M., Dai, W., Li, X., Chan, R.C.K., Hsin, M.K.Y. and Wong, T.T.W. High-Throughput, Label-Free and Slide-Free Histological Imaging by Computational Microscopy and Unsupervised Learning. Advanced Science, 2021. https://doi.org/10.1002/advs.202102358.
 The Global Cancer Observatory (GLOBOCAN), 2020. Cancer today, Estimated number of new cases in 2020, worldwide, females, all ages. [Online] Available at: http://gco.iarc.fr/today
 ACS. 2020. Breast Cancer Facts & Figures 2019-2020 [Online]. American Cancer Society. Available: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/breast-cancer-facts-and-figures/breast-cancer-facts-and-figures-2019-2020.pdf
 American Cancer Society, 2019. What is lung cancer? [Online].https://www.cancer.org/cancer/lung-cancer/about/what-is.html