Microscopic disease extension in three dimensions for non-small-cell lung cancer: development of a prediction model using pathology-validated positron emission tomography and computed tomography features.
OBJECTIVE
One major uncertainty in radiotherapy planning of non-small-cell lung cancer concerns the definition of the clinical target volume (CTV), meant to cover potential microscopic disease extension (MDE) around the macroscopically visible tumor. The primary aim of this study was to establish pretreatment risk factors for the presence of MDE. The secondary aim was to establish the impact of these factors on the accuracy of positron emission tomography (PET) and computed tomography (CT) to assess the total tumor-bearing region at pathologic examination (CTV(path)).


METHODS
34 patients with non-small-cell lung cancer who underwent CT and PET before lobectomy were included. Specimens were examined microscopically for MDE. The gross tumor volume (GTV) on CT and PET (GTV(CT) and GTV(PET), respectively) was compared with the GTV and the CTV at pathologic examination, tissue deformations being taken into account. Using multivariate logistic regression, image-based risk factors for the presence of MDE were identified, and a prediction model was developed based on these factors.


RESULTS
MDE was found in 17 of 34 patients (50%). The MDE did not exceed 26 mm in 90% of patients. In multivariate analysis, two parameters (mean CT tumor density and GTV(CT)) were significantly associated with MDE. The area under the curve of the two-parameter prediction model was 0.86. Thirteen tumors (38%, 95% CI: 24-55%) were identified as low risk for MDE, being potential candidates for reduced-intensity therapy around the GTV. In the low-risk group, the effective diameter of the GTV(CT/PET) accurately represented the CTV(path). In the high-risk group, GTV(CT/PET) underestimated the CTV(path) with, on average, 19.2 and 26.7 mm, respectively.


CONCLUSIONS
CT features have potential to predict the presence of MDE. Tumors identified as low risk of MDE show lower rates of disease around the GTV than do high-risk tumors. Both CT and PET accurately visualize the CTV(path) in low-risk tumors but underestimate it in high-risk tumors.
van Loon
Judith
J
Department of Radiation Oncology, Maastro Clinic, GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, the Netherlands. Judith.vanloon@maastro.nl
Siedschlag
Christian
C
Stroom
Joep
J
Blauwgeers
Hans
H
van Suylen
Robert-Jan
RJ
Knegjens
Joost
J
Rossi
Maddalena
M
van Baardwijk
Angela
A
Boersma
Liesbeth
L
Klomp
Houke
H
Vogel
Wouter
W
Burgers
Sjaak
S
Gilhuijs
Kenneth
K
D000230:Adenocarcinoma / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D018196:Carcinoma, Adenosquamous / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000473:pathology* / Q000532:radiotherapy; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology* / Q000532:radiotherapy; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009361:Neoplasm Invasiveness / Q000000981:diagnostic imaging / Q000473:pathology*; D009426:Netherlands; D049268:Positron-Emission Tomography / Q000379:methods; D011300:Preoperative Care / Q000379:methods; D019275:Radiopharmaceuticals; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D012044:Regression Analysis; D012307:Risk Factors; D014057:Tomography, X-Ray Computed / Q000379:methods; D047368:Tumor Burden
D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18