- ICH GCP
- US Clinical Trials Registry
- Klinisk forsøg NCT02482181
Diffusion Weighted Magnetic Resonance Imaging for the Characterization of Solitary Pulmonary Lesions (DWIMRICSPL)
Studieoversigt
Status
Betingelser
Detaljeret beskrivelse
When a patient is diagnosed with a lung lesion, the differential diagnosis is important, since the treatment is determined by the lesion character. The goal in the evaluation of solitary pulmonary lesions is to distinguish malignant lesions from benign lesions in as non-invasive a manner as possible. As computed tomography is widely used, the diagnosis of solitary pulmonary lesions has become easier. The size, features of the edges, shape, internal structure (calcification, fat content, cavitation, etc.), density, satellite nodule, growth rate and contrast involvement of the lesion are important properties which help to distinguish benign lesions from malignant ones. However, as the distinction is not absolute at all times, other imaging methods such as positron emission tomography and magnetic resonance are preferred. The importance of this issue is the high five-year survival rate in early-diagnosed lung cancer cases.
Diffusion is the randomized microscopic motion of water molecules. It is known that diffusion is a sensitive parameter of tissue characterization at a microscopic level. Nowadays, diffusion is measured in vivo with diffusion weighted MRI and ADC measurements.
Diffusion weighted imaging has a wide use on oncologic patients for the purpose of diagnosis. In addition, it is used in the distinction of acute cerebral infarction and epidermoid or arachnoid cysts. Recently, it has also been used in the characterization of cystic or solid lesions in the thoracic cavity. In this study, the investigators aimed to evaluate the accuracy of differentiation of solitary pulmonary lesions.
Undersøgelsestype
Tilmelding (Faktiske)
Kontakter og lokationer
Studiesteder
-
-
-
Edi̇rne, Kalkun, 22400
- Trakya University Hospital
-
-
Deltagelseskriterier
Berettigelseskriterier
Aldre berettiget til at studere
Tager imod sunde frivillige
Køn, der er berettiget til at studere
Prøveudtagningsmetode
Studiebefolkning
Beskrivelse
Inclusion Criteria:
- All patients had a solitary pulmonary nodule or mass.
Exclusion Criteria:
-
Studieplan
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
Hvad måler undersøgelsen?
Primære resultatmål
Resultatmål |
Tidsramme |
|---|---|
|
On diffusion weighted images, the signal intensities of the lesions were visually compared to the SI of the thoracic spinal cord using a 5-point scale.
Tidsramme: 1 year
|
1 year
|
Samarbejdspartnere og efterforskere
Sponsor
Efterforskere
- Studieleder: HAKAN GENÇHELLAÇ, MD, TURKEY,EDİRNE ,TRAKYA UNİVERSİTY HOSPİTAL
Publikationer og nyttige links
Datoer for undersøgelser
Studer store datoer
Studiestart
Primær færdiggørelse (Faktiske)
Studieafslutning (Faktiske)
Datoer for studieregistrering
Først indsendt
Først indsendt, der opfyldte QC-kriterier
Først opslået (Skøn)
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Skøn)
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidst verificeret
Mere information
Begreber relateret til denne undersøgelse
Yderligere relevante MeSH-vilkår
Andre undersøgelses-id-numre
- TRAKYA22
Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .
Kliniske forsøg med Thorax Cancer
-
University of VirginiaAfsluttet
-
Tanta UniversityAfsluttet
-
Tanta UniversityAfsluttet
-
Endospan Ltd.AfsluttetThorax aortaaneurisme | Thorax aortabuesygdomSchweiz, Italien, Tjekkiet
-
Mayo ClinicIkke rekrutterer endnu
-
University Medical Center GroningenAfsluttet
-
Duke Vascular, Inc.Ukendt
-
Cairo UniversityIkke rekrutterer endnu
-
New York Institute of TechnologyIkke rekrutterer endnuThorax kyfoseForenede Stater