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Stephen Harrow
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P1.09 - Pathology (ID 173)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Pathology
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.09-08 - Registration of Pre-Operative Lung Cancer PET/CT Scans with Post-Operative Histopathology Maps (ID 1703)
09:45 - 18:00 | Author(s): Stephen Harrow
- Abstract
Background
Currently there is insufficient data describing the cellular make-up of a tumour in relation to its functional imaging. This research project focuses on registering pre-operative PET/CT scans from lung cancer patients to their post-operative histology slides, enabling clinicians to draw spatial correlations between the tumour’s metabolic fingerprint and its actual histopathology map.
Method
Between January and June 2018 the research team identified and recruited 9 patients diagnosed with primary NSCLC and referred for radical lobectomy, across NHS Greater Glasgow and Clyde sites. Each participant was scanned in a combined PET/CT scanner prior to surgery, as per standard of care. The resected lobe was fixed in formalin for a minimum of 48 hours and injected with a 4% agar solution through the airways to stiffen the tissue and facilitate slicing. Once solid, the whole lobe was placed in a purpose-built slicing rig and dissected at regular 5-millimetre intervals. Each slice was photographed using a digital camera, then processed using a microtome and stained using immunohistochemistry (IHC) methods.
Virtual 3D tumour models were reconstructed from the CT and gross pathology images and registered using a linear affine transformation algorithm in Matlab 2017b (The MathWorks Inc, US). Real CT data was subsequently deformed using the same transformation matrix to match the gross pathology cutting planes. Histology slides were also aligned to the block-face photographs by applying a non-linear registration algorithm, constrained by one-to-one correspondences between common landmarks (i.e. edges, vessels, airways) identified on both image datasets.
Result
An average Dice similarity coefficient of 83% was obtained for the CT-to-pathology tumour model registration. Due to the quasi-spherical shape of most tumours, the orientation was found to be wrong in 3 cases, despite high overlapping scores. Therefore, we introduced a weighted registration algorithm that considers fiducial markers located in and around the tumour (e.g. airways or vessels) to ensure correct orientation. The figure below shows a sample slice of a transformed CT volume (A,B) which is matched to its corresponding gross pathology photograph (C), with overlapped histopathology data.
Conclusion
Building on the preliminary results presented last year in IASLC WCLC 2018, this proof-of-concept study has managed to spatially match pre-operative CT tumour data with its actual histopathology map, and we are in the process of extrapolating these results to 4D FDG PET data. This acquired knowledge shall provide an informed targeted approach for future radiotherapy studies.
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P2.01 - Advanced NSCLC (ID 159)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Advanced NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.01-08 - Clinical Trial in Progress: CONCORDE - A Phase 1B Study of Novel Agents in Combination with Conventional Radiotherapy in NSCLC (ID 600)
10:15 - 18:15 | Author(s): Stephen Harrow
- Abstract
Background
The majority of patients with locally advanced non-small cell lung cancer (NSCLC) treated with curative intent receive radiotherapy (RT) as part of their treatment. Despite considerable technological advances in RT delivery, the survival of these patients has barely changed over the last 60 years. A major factor in this failure to improve outcomes is the relative radioresistance of NSCLC. Attempts to overcome radioresistance by escalating RT doses have demonstrated inferior outcome likely secondary to normal tissue toxicity. Therefore an alternate approach is to exploit genetic dependencies in the DNA damage response of NSCLC, using biological inhibitors to selectively radiosensitise tumours whilst sparing normal tissues. The CONCORDE study is a multi-arm phase 1B platform study to investigate the combination of radical RT with DNA damage response inhibitors (DDR-i) targeting five different proteins: PARP, ATR, WEE1, ATM, DNA-PK.
Method
CONCORDE is a hypothesis-driven combination study of novel therapeutics and RT using an innovative adaptive early-phase trial design. The study will address two main research questions:
- What are the recommended phase 2 doses (RP2D) of individual DDR-i in combination with curative RT in patients with stage IIB/III NSCLC?
- What are the safety profiles of individual DDR-i combined with curative RT in this population?
Key inclusion criteria are stage IIB and III NSCLC planned to receive curative intent RT doses (+/- neoadjuvant chemotherapy) and PS 0-1. Participants will be randomised on a 3:1 basis between DDR-i with RT or RT alone. Patients receiving RT alone will be pooled across the arms to provide contemporary data on toxicity. All patients will receive external beam RT with a planned dose of 60 Gy in 30 fractions.
The study will use a Bayesian adaptive model-based approach to dose-escalation, with separate Time-To-Event Continual Reassessment Method (TiTE-CRM) models in each experimental arm. The primary endpoints are dose-limiting toxicities occurring within 12 months of the start of radiotherapy. Secondary endpoints include safety and toxicity (acute and late toxicity up to 2 years including using patient reported outcome (PRO) measures), treatment compliance, and best overall response (using RECIST 1.1, progression-free, and overall survival).
Correlative studies will be carried out to identify biomarkers of toxicity and response. We have secured high-level agreement from leading pharmaceutical partners to invest in 5 treatment arms and funding approval from Cancer Research UK is pending. The first participant is estimated to commence treatment in late 2019
Result
Section not applicable
Conclusion
Section not applicable
