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TexRAD - Breast Cancer
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TexRAD - Breast Cancer

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TexRAD is a software application that analyses the textures in existing radiological scans to assist the clinician in assessing the prognosis of patients with cancer. Currently applicable to ...

TexRAD is a software application that analyses the textures in existing radiological scans to assist the clinician in assessing the prognosis of patients with cancer. Currently applicable to colorectal, breast and lung cancers and we are offering licensing and collaboration opportunities for commercialisation and development of the technology.

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TexRAD - Breast Cancer TexRAD - Breast Cancer Presentation Transcript

  • Breast Homepage Breast Cancer Case Study | Demo | Evidence TexRAD screen shot of Breast lesion
  • Breast Case Study Breast Case Study Typical example: A female participant within a breast screening program undergoes an initial mammogram examination. Further diagnostic mammogram confirms presence of cancerous tissue. Core biopsy identified non-invasive ductal carcinoma in situ (DCIS) and the standard breast conservation excision was performed. Surprisingly, the final excised specimen provided evidence of invasive focus, routinely underestimated by core biopsy, resulting in additional surgical procedure involving the axilla TexRAD could have predicted the risk of invasive disease preoperatively from mammographic lesions assisting in treatment planning and optimal selection of biopsy or surgery 1 2 3 4 5 6 6 7 8 HOW? Case Study | Demo | Evidence
  • Breast CS 2 Breast Case Study How TexRAD supports clinician & patient in case study From routine mammographic images taken in the clinic TexRAD software uniquely extracts and measures fine , medium and coarse textures - in this example, from the breast lesion - and characterises differences in calcification architecture These texture differences can be used to preoperatively estimate the likelihood of invasive focus from among patients with DCIS This additional information may assist the clinician in better treatment planning and optimal selection of sentinel node biopsy or axillary surgery 1 2 3 4 5 6 6 7 8 Case Study | Demo | Evidence
  • Breast Demo 1 Breast - Demo 1 2 3 4 5 6 6 7 Case Study | Demo | Evidence TexRAD screen shot of Breast lesion 8
  • Breast Demo 2 Breast - Demo Breast TexRAD analysis of an obvious stellate mass as seen on a mammogram of a patient with core-biopsy proven breast cancer could estimate the risk of invasive disease 1 2 3 4 5 6 6 7 Case Study | Demo | Evidence 8
  • Breast Demo 3 Breast - Demo 1 2 3 4 5 6 6 7 Case Study | Demo | Evidence 8 Clinician’s Workflow
  • Breast Demo 4 STAGE 1 - Display the target clinical image of interest A TexRAD analysis is applied to the appropriate 2D mammographic image highlighting the breast lesion (tissue of interest - TOI). The specialist clinical consultant (e.g. Radiologist) will select the image containing this TOI. Breast - Demo 1 2 3 4 5 6 6 7 Case Study | Demo | Evidence 8
  • Breast Demo 5 STAGE 2 – Draw region of interest (ROI) to be analysed Using TexRAD’s graphical user interface tools, image window level/width can be altered to clearly delineate this TOI, interactive magnification/panning/centring can be used for better visualisation of this TOI. Clinician can choose an appropriate ROI tool (e.g. Polygon ROI) from a list of options based on the application. This ROI is super-imposed on the TOI within the original image. Breast - Demo 1 2 3 4 5 6 6 7 Case Study | Demo | Evidence 8
  • Breast Demo 6 Breast - Demo STAGE 3 – Texture Analysis TexRAD employs a novel algorithm (patent applied for) primarily to extracts subtle but prognostic metrics currently not available in clinic. The software also graphically displays clinically relevant fine, medium and coarse breast lesion textures separately (below) in addition to their fusion with the original mammographic image. 1 2 3 4 5 6 6 7 Case Study | Demo | Evidence 8
  • Breast Demo 7 STAGE 4 – TexRAD Spectroscopy Summarises the entire texture results graphically for the breast cancer patient. Clinician can easily interpret the results for a quick assessment. Breast - Demo 1 2 3 4 5 6 6 7 Case Study | Demo | Evidence 8
  • Breast Demo 8 STAGE 5 – Risk Stratification Report A risk stratification report specific to the breast cancer is generated, which should be used only to assist the clinician to make an accurate decision. The report contains patient ID and scan details, TexRAD analysis result, explanation and contact information. Breast - Demo SAMPLE REPORT ONLY FOR ILLUSTRATION 1 2 3 4 5 6 6 Case Study | Demo | Evidence 8 7
  • Breast Background 1 Breast - Background Facts about Breast Cancer Invasive cancer of the breast and DCIS can both present as focal lesions on mammography. Pure DCIS is not an invasive process and rarely metastasises to regional lymph nodes [1]. The introduction of mammographic breast screening has resulted in a dramatic increase in the diagnosis of DCIS and its detection rate has reached 15-20% of all mammographically detected cancers [2-4]. Based on core biopsy specimens, the standard surgical planning for DCIS is to offer breast conservation excision. 1 2 3 7 8 Case Study | Demo | Evidence 4 5 6
  • Breast Background 2 Breast - Background Facts about Breast Cancer However, the detection of DCIS on core biopsy is quite frequently followed by evidence of invasion within the final excision specimen. This occurs in 11-44% of patients and results in the need of second operative procedure involving the axilla [4, 5]. Therefore the main concern is whether any kind of axillary staging is indicated in patients preoperatively diagnosed with DCIS only. 1 2 3 7 8 Case Study | Demo | Evidence 4 5 6
  • Breast Background 3 Breast - Background Facts about Breast Cancer The most often employed axillary treatment option for patients with DCIS is to perform a sentinel node biopsy at the time of initial excision. Nevertheless it may lead to reoperation in cases of proven invasive focus on excision. Therefore an effective way of estimating the likelihood of an invasive focus preoperatively in patients diagnosed with DCIS would assist in better treatment planning and optimal use of sentinel node biopsy or axillary surgery. 1 2 3 7 8 Case Study | Demo | Evidence 4 5 6
  • Breast Evidence 1 Breast Evidence Clinical Evidence – ICIS 2007 [6] 1 2 7 8 Case Study | Demo | Evidence Graph indicates the relationship between relative fine to medium uniformity value and extent of disease (tumour type) from mammographic focal region of interest 3 4 5 6
  • Breast Evidence 2 Breast Evidence Clinical Evidence – ICIS 2007 [6] 1 2 7 8 Case Study | Demo | Evidence Graph indicates the inverse relationship between relative fine to coarse mean grey-level intensity value and oestrogen receptor (ER) status from mammographic focal region of interest 3 4 5 6
  • Breast Evidence 3 Breast Evidence Clinical Evidence – ICIS 2007 [6] 1 2 7 8 Case Study | Demo | Evidence Graph indicates the inverse relationship between relative medium to coarse mean grey-level intensity value and progesterone receptor (PR) status from mammographic focal region of interest 3 4 5 6
  • References - Breast
    • BREAST
    • 1. Yen TW, Hunt KK, et al. Predictors of Invasive Breast Cancer in Patients with an initial diagnosis of Ductal Carcinoma in Situ: A Guide to Selective Use of Sentinel Lymph Node Biopsy in Management of Ductal Carcinoma in Situ. J Am Coll Surg 2005; 200: 516-526.
    • 2. Lagios MD. Ductal carcinoma in situ. Pathology and treatment. Surg Clin North America 1990; 70, 853-871.
    • 3. Holland R, et al. Extent, distribution and mammographic/ histological correlations of breast ductal carcinoma in situ. Lancet 1990, 335, 519-522.
    • 4. Leonard GD, Swain SM. Ductal carcinoma in situ, complexities and challenges. Journal of the National Cancer Institute 2004; 96(12):906-20.
    • 5. Dillon MF, et al. Predictors of Invasive Disease in Breast Cancer When Core Biopsy Demonstrates DCIS Only. Journal of Surg Oncology 2006; 93, 559-563.
    • 6. Ganeshan B, Strukowska O, Miles KA, Young RCD, Chatwin CR. Texture analysis: A potential adjunct to computer assisted diagnosis (CAD) in mammography. In Cancer Imaging, ICIS 2007, Brugge, Belgium.
    References - Breast Cancer Colorectal | Lung | Breast | Prostate | Renal | Lung | Brain | DTA