CT-based Radiomic Signature Can Identify Adenocarcinoma Lung Tumor Histology
Lung cancer remains the leading cause of cancer related mortality worldwide, with more than 1.5 million related deaths annually. Lung cancer is divided into two main groups: Small Cell Lung Carcinoma (SCLC) and Non-Small Cell Lung Carcinoma (NSCLC), with prevalence of ~20% and 80% respectively. NSCLC is further subdivided into adenocarcinoma (the most common), squamous cell carcinoma (SCC), and large cell carcinoma. Furthermore, each subtype is likely to have specific mutations, which could be targeted for treatment.
Medical imaging and radiomics feature extraction represent a candidate alternative to conventional tissue biopsy, a theory that is investigated in this study.
調査の概要
研究の種類
入学 (予想される)
連絡先と場所
研究場所
-
-
Limburg
-
Maastricht、Limburg、オランダ、6229ER
- Maastricht University
-
-
参加基準
適格基準
就学可能な年齢
- 子
- 大人
- 高齢者
健康ボランティアの受け入れ
受講資格のある性別
サンプリング方法
調査対象母集団
説明
Inclusion Criteria:
- Availability of diagnostic non-contrast enhanced CT scan.
- Availability of histologic tumor analysis results
Exclusion Criteria:
-
研究計画
研究はどのように設計されていますか？
デザインの詳細
コホートと介入
グループ/コホート |
介入・治療 |
|---|---|
|
Maastro (Lung1)
Open source dataset available at TCIA.org.
The cohort includes CT scans of 422 patients diagnosed with NSCLC.
|
Radiomics -the high throughput extraction of quantitative features from medical imaging- extract features that might potentially decode biologic tumor information, which might ultimately reduce the need to use invasive procedure, such as tissue biopsy.
他の名前：
|
|
UCSF
A cohort of patients diagnosed with NSCLC at UCSF medical center.
It includes CT scans of 165 patients.
|
Radiomics -the high throughput extraction of quantitative features from medical imaging- extract features that might potentially decode biologic tumor information, which might ultimately reduce the need to use invasive procedure, such as tissue biopsy.
他の名前：
|
|
Radboud
A cohort of patients diagnosed with NSCLC at Radboud medical center.
It includes CT scans of 255 patients.
|
Radiomics -the high throughput extraction of quantitative features from medical imaging- extract features that might potentially decode biologic tumor information, which might ultimately reduce the need to use invasive procedure, such as tissue biopsy.
他の名前：
|
|
Stanford
Open source dataset available at TCIA.org.
The cohort includes CT scans of 211 patients diagnosed with NSCLC.
|
Radiomics -the high throughput extraction of quantitative features from medical imaging- extract features that might potentially decode biologic tumor information, which might ultimately reduce the need to use invasive procedure, such as tissue biopsy.
他の名前：
|
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Lung histology
時間枠：December 2019
|
Is the tumor under investigation an adenocarcinoma of the lung?
|
December 2019
|
協力者と研究者
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (予想される)
研究の完了 (予想される)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。