-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
-
Cosmetic Ingredient
- Water Treatment Chemical
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
Lung cancer is one of the most common cancers and the leading cause of cancer deaths worldwide
.
Among them , adenocarcinoma is the most common histological subtype
Lung cancer is one of the most common cancers and the leading cause of cancer deaths worldwide
Recently, image-based radiomics has attracted more and more attention as an emerging method to quantify tumor heterogeneity, and may provide potential clinical imaging features for patient stratification
Recently, he published in a journal Radiology study the use of CT radiation group learning model based on different region of interest (VOIs), including tumor and peritumoral area , assessing their prognosis to improve clinical stage I lung adenocarcinoma accuracy entity , To provide more accurate guidance for the clinic and assist the clinic to predict the prognosis of early-stage lung cancer patients more accurately, and to provide data support for the formulation of individualized and refined treatment plans earlier
This retrospective study included patients with clinical stage I solid lung adenocarcinoma from two hospitals (center 1 and center 2)
A total of 334 patients were enrolled (204 and 130 in No.
The figure performs multivariate Cox regression analysis on selected radiomic features in four regions: aGTV, bPTV0~+3, cPTV-3~+3, dPTV0~+6 .
.
Means p<0.
05, * means p<0.
01, ** means p<0.
001, *** means p<0.
0001, determined by DeLong test .
.
Means p<0.
This study shows that , compared with the VOI based on 3mm or 6mm inside and outside the tumor, the radiomic model based on the visible tumor boundary of 6mm (PTV-3~+3) predicts the prognosis of clinical stage I solid lung adenocarcinoma Aspect is more accurate
Original source :
Kunfeng Liu , Kunwei Li , Tingfan Wu ,et al .
Improving the accuracy of prognosis for clinical stage I solid lung adenocarcinoma by radiomics models covering tumor per se and peritumoral changes on CT.
DOI: 10.
Liu Kunfeng Kunwei of Li Tingfan Wu , et Al 10.
1007 / s00330-021-08194-0 10.
1007 / s00330-021-08194-0 in this message
