NCT04708483

Brief Summary

DCE-CT of thoracic tumors as an early biomarker for treatment monitoring in comparison with morphologic criteria.

  1. 1.Rationale of the clinical investigation
  2. 2.Objective of the study
  3. 3.To define internal system parameters and perfusion parameter thresholds that maximize the accuracy of the outcomes and to define the correct category (PD, SD, PR, CR); and
  4. 4.To compare the predicted categorization to the assessed RECIST1.1 categorization.
  5. 5.Endpoints 3.1.Primary Endpoint The primary endpoint is to directly compare the biomarker of the HF analysis software at week 3 (+- 1 week) and week 8 (+- 3 weeks) with the eventually reported Progression-Free Survival (PFS) intervals and Overall Survival (OS) in this study. PFS intervals are determined by the clinician and are based on RECIST1.1 and additional clinical and biochemical progression markers. The focus will be on evaluating the accuracy of the prediction as well as how early the prediction was correct.
  6. 6.The internal parameters for the HF biomarker, e.g. magnitude of the Ktrans decrease, and the change in volume of unhealthy tissue, need to be determined to define the classification (PD, SD, PR and CR) by the HF analysis software. These parameters are optimized to optimally predict the classification according to PFS and OS. This will be done by splitting the data into a train and test set to ensure generalization.
  7. 7.The classification of the HF analysis software will be compared to the purely morphological classification by RECIST1.1 to identify correlation. Furthermore, some cases will be investigated where the HF analysis performs noticeably better or worse than RECIST1.1 in predicting PFS and OS. Finally, the difference in time to the first correct prediction is compared between HF and RECIST1.1.

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
100

participants targeted

Target at P50-P75 for not_applicable

Timeline
Completed

Started Jan 2021

Typical duration for not_applicable

Geographic Reach
1 country

1 active site

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

January 4, 2021

Completed
3 days until next milestone

Study Start

First participant enrolled

January 7, 2021

Completed
7 days until next milestone

First Posted

Study publicly available on registry

January 14, 2021

Completed
1.8 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

October 31, 2022

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2022

Completed
Last Updated

February 9, 2021

Status Verified

February 1, 2021

Enrollment Period

1.8 years

First QC Date

January 4, 2021

Last Update Submit

February 8, 2021

Conditions

Cancer, LungPerfusion Computed Tomography Target LesionCancer LiverMetastatic Lung CancerMetastatic Liver Cancer

Keywords

Dynamic contrast-enhanced imagingDCE

Outcome Measures

Primary Outcomes (2)

  • The primary endpoint is to directly correlate the biomarker of the HF analysis software at week 3 (+- 1 week) with the eventually reported Progression-Free Survival (PFS) intervals and Overall Survival (OS) in this study.

    The HF biomarker is calculated from DCE perfusion and permeability metrics such as arterial blood flow fraction (alpha), total blood plasma flow (F\_p), volume transfer coefficient (K-trans), extracellular volume ratio reflecting vascular permeability (v\_e) and plasma volume ratio (v\_p). Additionally, semi-quantitative DCE signal metrics, such as signal enhancement and time until contrast agent arrival, may also be taken into account. PFS intervals are determined by the clinician and are based on RECIST1.1 and additional clinical and biochemical progression markers. The focus will be on evaluating the accuracy of the prediction as well as how early the prediction was correct.

    1 year

  • The primary endpoint is to directly correlate the biomarker of the HF analysis software at week 8 (+- 3 weeks) with the eventually reported Progression-Free Survival (PFS) intervals and Overall Survival (OS) in this study.

    The HF biomarker is calculated from DCE perfusion and permeability metrics such as arterial blood flow fraction (alpha), total blood plasma flow (F\_p), volume transfer coefficient (K-trans), extracellular volume ratio reflecting vascular permeability (v\_e) and plasma volume ratio (v\_p). Additionally, semi-quantitative DCE signal metrics, such as signal enhancement and time until contrast agent arrival, may also be taken into account. PFS intervals are determined by the clinician and are based on RECIST1.1 and additional clinical and biochemical progression markers. The focus will be on evaluating the accuracy of the prediction as well as how early the prediction was correct.

    1 year

Secondary Outcomes (2)

  • The secondary endpoint is to find an optimal classification system based on changes in DCE perfusion and permeability parameters to classify a treatment response as (PD, SD, PR and CR).

    1 year

  • The classification of the HF analysis software will be compared to the purely morphological classification by RECIST1.1 to identify correlation.

    1 year

Study Arms (1)

Malignant thoracic tumoral pathology.

EXPERIMENTAL

Patients suffering from primary malignant thoracic tumoral pathology or second line patients having had a therapy pause of at least 6 weeks.

Device: Extra DCE-CT scan

Interventions

Extra DCE-CT scanDEVICE

DCE-CT of thoracic tumors as an early biomarker for treatment monitoring in comparison with morphologic criteria.

Also known as: Perfusion scan
Malignant thoracic tumoral pathology.

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Patients suffering from primary malignant thoracic tumoral pathology or second line patients having had a therapy pause of at least 6 weeks; at least one tumoral lesion/component should have ≥15mm in diameter.
  • All patients willing to participate and to sign the informed consent.

You may not qualify if:

  • All patients younger than 18-years-old.
  • Documented allergy for iodine.
  • Neutropenia (absolute White Blood Cell count ≤ 1.5 × 109/l).
  • Thrombopenia (absolute platelet count ≤ 100 × 109/l).
  • Renal insufficiency: serum creatinine ≥ 1.5× the upper limit of normal (ULN); 24-hours creatinine clearance ≤ 50ml/min).
  • Serum bilirubine ≥ 1,5 x ULN, AST ≥ 2,5 x ULN, ALT ≥ 2,5x ULN.
  • Brain metastases

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

University Hospital, Ghent

Ghent, East-Flanders, 9000, Belgium

RECRUITING

Related Publications (5)

  • Hwang SH, Yoo MR, Park CH, Jeon TJ, Kim SJ, Kim TH. Dynamic contrast-enhanced CT to assess metabolic response in patients with advanced non-small cell lung cancer and stable disease after chemotherapy or chemoradiotherapy. Eur Radiol. 2013 Jun;23(6):1573-81. doi: 10.1007/s00330-012-2755-0. Epub 2013 Jan 9.

    PMID: 23300040BACKGROUND

  • Korn RL, Crowley JJ. Overview: progression-free survival as an endpoint in clinical trials with solid tumors. Clin Cancer Res. 2013 May 15;19(10):2607-12. doi: 10.1158/1078-0432.CCR-12-2934.

    PMID: 23669420BACKGROUND

  • Strauch LS, Eriksen RO, Sandgaard M, Kristensen TS, Nielsen MB, Lauridsen CA. Assessing Tumor Response to Treatment in Patients with Lung Cancer Using Dynamic Contrast-Enhanced CT. Diagnostics (Basel). 2016 Jul 21;6(3):28. doi: 10.3390/diagnostics6030028.

    PMID: 27455330RESULT

  • Even AJG, Reymen B, La Fontaine MD, Das M, Mottaghy FM, Belderbos JSA, De Ruysscher D, Lambin P, van Elmpt W. Clustering of multi-parametric functional imaging to identify high-risk subvolumes in non-small cell lung cancer. Radiother Oncol. 2017 Dec;125(3):379-384. doi: 10.1016/j.radonc.2017.09.041. Epub 2017 Nov 6.

    PMID: 29122363RESULT

  • Qiao PG, Zhang HT, Zhou J, Li M, Ma JL, Tian N, Xing XD, Li GJ. Early evaluation of targeted therapy effectiveness in non-small cell lung cancer by dynamic contrast-enhanced CT. Clin Transl Oncol. 2016 Jan;18(1):47-57. doi: 10.1007/s12094-015-1335-6. Epub 2015 Aug 5.

    PMID: 26243393RESULT

MeSH Terms

Conditions

Lung NeoplasmsCarcinoma, HepatocellularLiver Neoplasms

Interventions

Ventilation-Perfusion Scan

Condition Hierarchy (Ancestors)

Respiratory Tract NeoplasmsThoracic NeoplasmsNeoplasms by SiteNeoplasmsLung DiseasesRespiratory Tract DiseasesAdenocarcinomaCarcinomaNeoplasms, Glandular and EpithelialNeoplasms by Histologic TypeDigestive System NeoplasmsDigestive System DiseasesLiver Diseases

Intervention Hierarchy (Ancestors)

Radionuclide ImagingDiagnostic ImagingDiagnostic Techniques and ProceduresDiagnosisDiagnostic Techniques, RadioisotopeRespiratory Function TestsDiagnostic Techniques, Respiratory System

Study Officials

  • Veerle Surmont, Prof, MD

    University Hospital, Ghent

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Maarten Van Hoorickx

CONTACT

+32483308781maarten@hyperfusion.ai

Kenneth Coenegrachts, MD, PhD

CONTACT

+32 496 87 57 28‬kenneth@hyperfusion.ai

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
DIAGNOSTIC
Intervention Model
SINGLE GROUP
Model Details: Morphologic criteria are being compared with analysis of functional (perfusion) CT imaging.
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

January 4, 2021

First Posted

January 14, 2021

Study Start

January 7, 2021

Primary Completion

October 31, 2022

Study Completion

December 31, 2022

Last Updated

February 9, 2021

Record last verified: 2021-02

Data Sharing

IPD Sharing
Will not share

Locations

BE(1)