CT patterns and serial CT Changes in lung Cancer patients post stereotactic body radiotherapy (SBRT)

Radiation Therapy for Lung Cancer: Imaging Appearances and Pitfalls

Radiation therapy is part of a multimodality treatment approach to lung cancer. The radiologist must be aware of both the expected and the unexpected imaging findings of the post-radiation therapy patient, including the time course for development of post- radiation therapy pneumonitis and fibrosis. In this review, a brief discussion of radiation therapy techniques and indications is presented, followed by an image-heavy differential diagnostic approach. The review focuses on computed tomography imaging examples to help distinguish normal postradiation pneumonitis and fibrosis from alternative complications, such as infection, local recurrence, or radiation-induced malignancy.

Factors associated with cavity formation after stereotactic body radiation therapy for peripheral early-stage lung cancer

PURPOSE

This retrospective study aimed to identify the factors associated with cavity formation after SBRT in peripheral early-stage lung cancer patients. We analyzed the occurrence of cavity changes after SBRT.

MATERIALS AND METHODS

We examined 99 cases with T1-T2aN0 peripheral non-small cell lung cancer treated with SBRT from 2004 to 2021. Patients underwent respiratory function tests, including diffusing capacity for carbon monoxide (DLco), before treatment. The median observation period was 35 months (IQR 18-47.5 months). Treatment involved fixed multi-portal irradiation in 67% of cases and VMAT in 33%. The total radiation doses ranged from 42 to 55 Gy, delivered over 4 to 5 fractions.

RESULTS

Cavity formation occurred in 14 cases (14.1%), appearing a median of 8 months after SBRT. The cavity disappeared in a median of 4 months after formation. High DLco and total radiation dose were identified as factors significantly associated with cavity formation. There have been no confirmed recurrences to date, but one patient developed a lung abscess.

CONCLUSION

Although cavity formation after SBRT for peripheral early-stage lung cancer is infrequent, it can occur. This study showed high DLco and total radiation dose to be factors significantly associated with cavity formation. These findings can be applied to optimizing radiation therapy (RT) and improving patient outcomes. Further research is needed to determine the optimal radiation dose for patients with near-normal DLco for whom surgery is an option. This study provides valuable insights into image changes after RT.

Characterisation of quantitative imaging biomarkers for inflammatory and fibrotic radiation-induced lung injuries using preclinical radiomics

BACKGROUND AND PURPOSE

Radiomics is a rapidly evolving area of research that uses medical images to develop prognostic and predictive imaging biomarkers. In this study, we aimed to identify radiomics features correlated with longitudinal biomarkers in preclinical models of acute inflammatory and late fibrotic phenotypes following irradiation.

MATERIALS AND METHODS

Female C3H/HeN and C57BL6 mice were irradiated with 20 Gy targeting the upper lobe of the right lung under cone-beam computed tomography (CBCT) image-guidance. Blood samples and lung tissue were collected at baseline, weeks 1, 10 & 30 to assess changes in serum cytokines and histological biomarkers. The right lung was segmented on longitudinal CBCT scans using ITK-SNAP. Unfiltered and filtered (wavelet) radiomics features (n = 842) were extracted using PyRadiomics. Longitudinal changes were assessed by delta analysis and principal component analysis (PCA) was used to remove redundancy and identify clustering. Prediction of acute (week 1) and late responses (weeks 20 & 30) was performed through deep learning using the Random Forest Classifier (RFC) model.

RESULTS

Radiomics features were identified that correlated with inflammatory and fibrotic phenotypes. Predictive features for fibrosis were detected from PCA at 10 weeks yet overt tissue density was not detectable until 30 weeks. RFC prediction models trained on 5 features were created for inflammation (AUC 0.88), early-detection of fibrosis (AUC 0.79) and established fibrosis (AUC 0.96).

CONCLUSIONS

This study demonstrates the application of deep learning radiomics to establish predictive models of acute and late lung injury. This approach supports the wider application of radiomics as a non-invasive tool for detection of radiation-induced lung complications.

ctDNA-based minimal residual disease detection in lung cancer patients treated with curative intended chemoradiotherapy using a clinically transferable approach

BACKGROUND

Reliable biomarkers are needed to identify tumor recurrence of non-small cell lung cancer (NSCLC) patients after chemoradiotherapy (CRT) with curative intent. This could improve consolidation therapy of progressing patients. However, the approach of existing studies has limited transferability to the clinic.

MATERIALS AND METHODS

A retrospective analysis of 135 plasma samples from 56 inoperable NSCLC patients who received CRT with curative intent was performed. Plasma samples collected at baseline, at the first check-up (average 1.6 months post-RT), and at the second check-up (average 4.5 months post-RT) were analyzed by deep sequencing with a commercially available cancer personalized profiling strategy (CAPP-Seq) using a tumor-agnostic approach.

RESULTS

Detection of circulating tumor DNA (ctDNA) at 4.5 months after therapy was significantly associated with higher odds of tumor recurrence (OR: 5.4 (CI: 1.1-31), Fisher's exact test: p-value = 0.022), and shorter recurrence-free survival (RFS) (HR: 4.1 (CI: 1.7-10); log-rank test: p-value = 9e-04). In contrast, detection of ctDNA at 1.6 months after therapy was not associated with higher odds of tumor recurrence (OR: 2.7 (CI: 0.67-12), Fisher's exact test: p-value = 0.13) or shorter RFS (HR: 1.5 (CI: 0.67-3.3); log-rank test: p-value = 0.32).

CONCLUSION

This study demonstrates that the detection of ctDNA can be used to identify minimal residual disease 4.5 months after CRT in NSCLC patients using a commercially available kit and a tumor-agnostic approach. Furthermore, the time point of collecting the plasma sample after CRT has decisive importance for the prognostic value of ctDNA.

MICRO ABSTRACT

This study analysed 135 plasma samples from 56 NSCLC patients treated with curative intent chemoradiotherapy using a tumor-agnostic approach. Detecting ctDNA at 4.5 months post-treatment was linked to higher recurrence odds, indicating ctDNA's potential as a biomarker for identifying residual disease after treatment with curative intent. Importantly, the study emphasizes the importance of timing for accurate ctDNA analysis results.

Spectrum of Imaging Patterns of Lung Cancer following Radiation Therapy

Radiation therapy using conventional or newer high-precision dose techniques, including three-dimensional conformal radiotherapy, intensity-modulated radiation therapy, stereotactic body radiation therapy, four-dimensional conformational radiotherapy, and proton therapy, is an important component of treating patients with lung cancer. Knowledge of the radiation technique used and the expected temporal evolution of radiation-induced lung injury, as well as patient-specific parameters such as previous radiotherapy, concurrent chemoradiotherapy, or immunotherapy, is important in image interpretation. This review discusses factors that affect the development and severity of radiation-induced lung injury and its radiological manifestations, as well as the differences between conventional and high-precision dose radiotherapy techniques.