Lung adenocarcinoma, the most prevalent histological subtype of lung cancer, has been steadily rising in global incidence [1]. In 2015, the World Health Organization proposed a classification system for invasive non-mucinous pulmonary adenocarcinoma (INMA) based on the predominant histological subtypes [2]. However, INMA exhibits histological heterogeneity, and this classification system may underestimate the impact of nonpredominant histological subtypes [3,4]. In 2021, the International Association for the Study of Lung Cancer (IASLC) proposed a novel grading system based on major subtypes and high-level components exceeding 20%; its prognostic value not only surpasses the histological subtype grading system but also outperforms training models incorporating pathological characteristics such as nuclear division, nuclear grading, cytological grading, airway spread, and necrosis [5], [6], [7], [8], [9], [10]. Moreover, studies have shown that the novel IASLC grading system can guide patients toward making appropriate surgical choices preoperatively and determine whether they can benefit from preoperative adjuvant treatment [11], [12], [13], [14], [15]. Although histopathology is the gold standard for diagnosing lung cancer, preoperative biopsy specimens do not fully reflect the biological characteristics of the lesion and may lead to a series of complications such as pneumothorax and bleeding [16]. Therefore, a convenient and non-invasive examination method for preoperatively identifying different INMA grades can guide patients in choosing appropriate treatment options and help predict patient prognosis.

Spectral computed tomography (CT), an advanced CT imaging technique, offers diverse quantitative parameters, including single-energy imaging, material density values, spectral curves, and effective atomic numbers, utilizing single-source instantaneous dual-kVp switching technology. This allows to acquire additional information concerning the internal histological and biological characteristics of lesions [17,18]. Iodine maps utilize X-rays of different energies with different attenuations of iodine-based substances to obtain images of the spatial distribution and quantitative parameters of iodine. This reflects the functional and biological characteristics of the lesions [19]. Furthermore, iodine maps are calculated using specific linear attenuation coefficients, rendering them unaffected by confounding factors such as metallic artifacts. This ensures the provision of precise quantitative parameters [20]. Significant progress has been made recently in spectral CT iodine quantification analysis for the diagnosis, differentiation, and evaluation of therapeutic efficacy of lung cancer [21], [22], [23], [24]. However, previous analyses of iodine maps often involved outlining the regions of interest (ROIs) at the maximum tumor level to obtain lesion enhancement [21,23]. As a mathematical method, histogram analysis provides quantitative parameters such as skewness, kurtosis, and percentiles. skewness and kurtosis characterize the symmetry and steepness of the distribution of iodine concentration (IC) on CT images, with their percentiles indicating the proportion of distinct tissue components within a tumor. These parameters facilitate a comprehensive evaluation of tumor heterogeneity [25,26]. Moreover, histogram analysis demonstrates good repeatability [27]. Histogram analysis is presently mainly based on the magnetic resonance imaging and conventional CT images of lesions [28], [29], [30], [31]. However, the use of iodine map histogram analysis based on spectral CT remains infrequent in clinical research. Furthermore, to the best of our knowledge, neither IC nor iodine map histograms have been used to evaluate the novel IASLC grade of INMA.

Therefore, the purpose of this study was to investigate the capabilities of whole-tumor iodine map histogram analysis and spectral CT parameters for discriminating between the different grades of INMA according to the novel IASLC grading system and to compare the diagnostic performances of both approaches in this regard.