Tumour response in non‐small‐cell lung cancer patients treated with chemoradiotherapy – Can spectral CT predict recurrence?

Abstract

Introduction: Tumour response in lung cancer treatment is monitored by measuring lesion size in computed tomography (CT). Spectral CT (SCT) offers additional information on tumour tissue besides morphology. We evaluated SCT iodine content (IC) and performed spectral slope analysis to assess the response of non-small-cell lung cancer (NSCLC) to chemoradiotherapy (CRT). Methods: Eighty-three patients with advanced NSCLC treated by CRT prospectively underwent single-phase, contrast-enhanced SCT. Evaluation of all patients included treatment response (RECIST 1.1), quantitative measurements as well as SCT IC determination and spectral slope analysis in NSCLC primaries. Measurements were performed at the maximum cross-diameter of tumours and in areas with high iodine values (hotspot analysis). Iodine difference (DIC) was calculated. Secondary outcome parameters were IC and spectral slopes in mediastinal lymph nodes (n = 61). Results: Twenty-four patients (29%) showed complete remission after CRT. Thirty-four patients (41%) had stable disease (SD SCT ) or partial regression (PR SCT ). Progressive disease (PD SCT ) was seen in 25 patients (30%). Hotspot analysis showed significantly higher iodine values in PD SCT than in SD SCT /PR SCT (P < 0.001). Ten patients (12%) with initially stable disease in SCT showed progressive disease during follow-up for up to 18 months (PD FU ). These patients also had significantly higher hotspot iodine values and DIC in the initial scan compared to patients with SD throughout the follow-up period (SD FU ) (29%) (P < 0.001). Enlarged lymph nodes showed significantly lower iodine content and a lower spectral slope pitch than normal-sized nodes (P = 0.003 to 0.029). Conclusion: Spectral CT-derived iodine content of NSCLC following CRT may help in predicting recurrence. Hotspot analysis and iodine heterogeneity allow the identification of residual vascularisation as an indicator of vital tumour tissue, indicating that IC might be a suitable imaging biomarker for predicting tumour progression. Iodine content and spectral slope analysis might also help in identifying metastatic lymph nodes.

Assessment of Solitary Pulmonary Nodules Based on Virtual Monochrome Images and Iodine-Dependent Images Using a Single-Source Dual-Energy CT with Fast kVp Switching

“…Some authors indicated the possible role of DECT iodine quantification in the evaluation of metabolic activity of the lung tumor. DECT iodine concentration was described as a possible substitute to 18F-FDG PET/CT in the evaluation of the lung tumor response to treatment [34,35], as an imaging biomarker of residual tumor vitality to predict tumor progression [36] or to predict the effects of chemotherapy in patients with advanced lung adenocarcinoma [37]. Ren et al [34] indicated the possible role of iodine-related quantification in DECT in the evaluation of the lung cancer response to treatment (radiotherapy alone or chemoradiotherapy) as a feasible substitute to 18 FDG PET-CT examination in such cases.…”

Subjective and Objective Assessment of Monoenergetic and Polyenergetic Images Acquired by Dual-Energy CT in Breast Cancer

“…In addition, quantitative parameters can be obtained from DECT, namely the normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit (HU) curve (λHU, HU per kiloelectron volt [keV]), and the normalized effective atomic number (nZeff). These quantitative parameters are useful for tumor detection, lesion characterization, and assessment of treatment response (12)(13)(14). The few studies that have used individual quantitative parameters have shown that the iodine concentration is significantly higher in tumors than in normal breast tissue and pectoral muscle (9).…”

Spectral CT Hybrid Images in the Diagnostic Evaluation of Hypervascular Abdominal Tumors—Potential Advantages in Clinical Routine

“…Diagnostics 2021, 11, x 2 of 10 the detection of tumor lesions [4][5][6][7][8][9][10]. Furthermore, VMIs and IMs have shown some potential to improve the diagnostic performance of CT in the differentiation of several types of tumors and pathologies and therapy monitoring in these patients [11][12][13][14].…”