Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning

Abstract

Background: Lymphovascular invasion (LVI) and perineural invasion (PNI) are important prognostic factors for gastric cancer (GC) that indicate an increased risk of metastasis and poor outcomes. Accurate preoperative prediction of LVI/PNI status could help clinicians identify high-risk patients and guide treatment decisions. However, prior models using conventional computed tomography (CT) images to predict LVI or PNI separately have had limited accuracy. Spectral CT provides quantitative enhancement parameters that may better capture tumor invasion. We hypothesized that a predictive model combining clinical and spectral CT parameters would accurately preoperatively predict LVI/PNI status in GC patients.

Aim: To develop and test a machine learning model that fuses spectral CT parameters and clinical indicators to predict LVI/PNI status accurately.

Methods: This study used a retrospective dataset involving 257 GC patients (training cohort, n = 172; validation cohort, n = 85). First, several clinical indicators, including serum tumor markers, CT-TN stages and CT-detected extramural vein invasion (CT-EMVI), were extracted, as were quantitative spectral CT parameters from the delineated tumor regions. Next, a two-step feature selection approach using correlation-based methods and information gain ranking inside a 10-fold cross-validation loop was utilized to select informative clinical and spectral CT parameters. A logistic regression (LR)-based nomogram model was subsequently constructed to predict LVI/PNI status, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC).

Results: In both the training and validation cohorts, CT T3-4 stage, CT-N positive status, and CT-EMVI positive status are more prevalent in the LVI/PNI-positive group and these differences are statistically significant (P < 0.05). LR analysis of the training group showed preoperative CT-T stage, CT-EMVI, single-energy CT values of 70 keV of venous phase (VP-70 keV), and the ratio of standardized iodine concentration of equilibrium phase (EP-NIC) were independent influencing factors. The AUCs of VP-70 keV and EP-NIC were 0.888 and 0.824, respectively, which were slightly greater than those of CT-T and CT-EMVI (AUC = 0.793, 0.762). The nomogram combining CT-T stage, CT-EMVI, VP-70 keV and EP-NIC yielded AUCs of 0.918 (0.866-0.954) and 0.874 (0.784-0.936) in the training and validation cohorts, which are significantly higher than using each of single independent factors (P < 0.05).

Conclusion: The study found that using portal venous and EP spectral CT parameters allows effective preoperative detection of LVI/PNI in GC, with accuracy boosted by integrating clinical markers.

Keywords: Gastric cancer; Lymphovascular invasion; Perineural invasion; Spectral computed tomography.

Figure 1

Flowchart of the inclusion and exclusion criteria. LVI: Lymphovascular invasion; PNI: Perineural invasion; CT: Computed tomography.

Figure 2

Example of a computed tomography-detected extramural vein invasion score on computed tomography images of gastric cancer patients. A: Score 0: The tumor has not penetrated the gastric wall, and there are no extramural vessels beside the lesion (arrow) in the transverse position of the venous phase (VP); B: Score 1: The transverse view of the VP shows that the tumor has permeated the gastric wall, and there are no extramural vessels beside the lesion (arrow); C: Score 2: In the VP, the coronal lesion has penetrated the gastric wall, and there are tortuous blood vessels connected with the lesion (arrow), but no tumor density shadow is observed in the vascular lumen; D: Score 3: The transverse view of the VP shows that the mass has penetrated through the gastric wall, the involved blood vessels appear slightly tortuous and dilated, and the tumor density shadow is visible (arrow); E: Score 4: In the coronary view of the VP, the tumor permeated the gastric wall, the extramural vascular lumen was significantly dilated, and a slight low-density filling defect was visible inside (arrow).

Figure 3

Example of the energy spectrum data measurement. A: 70 keV single-energy image; B: The iodine base image; C: The energy spectrum curve. Elliptical regions of interests were drawn at the largest level of the lesion in the lesser curvature of the gastric horn, as shown in A and B.

Figure 4

Technical study pipeline. CT-EMVI: Computed tomography-detected extramural vein invasion; CT: Computed tomography.

Figure 5

Comparative imaging and spectral analysis of pathological gastric adenocarcinoma in two patients with different lymphovascular and perineural invasion status. A and B: Patient 1: The patient was a 75-year-old female with pathological gastric adenocarcinoma, and both lymphovascular invasion (LVI) and perineural invasion (PNI) were negative (HE, × 200); the equilibrium phase (EP) transverse view shows that the gastric cancer (GC) lesion was immersed in the submucosal low-density layer, and the infiltration depth was more than 50% of the lesion; however, the low-density zone was still visible with an intact outer membrane. No suspicious metastatic lymph nodes were found on the computed tomography (CT) image, and no extramural blood vessels were found around the lesion. The CT stage was CT-T2N0, and CT-detected extramural vein invasion (CT-EMVI) was 0 and negative. The slopes of the energy spectrum curves in the EP were K40-70 = 3.43, IC = 18.46 (100 μg/cm³), normalized iodine concentration (NIC) = 0.40, and effective atomic number (Zeff) = 8.68; C and D: Patient 2: The patient was a 77-year-old male with pathological gastric adenocarcinoma, and both LVI and PNI were positive (HE, × 200). The GC lesion in the transverse position in the equilibrium stage permeated the gastric wall, and a cord-like thickened vascular shadow was observed in the fat space around the lesion. An endovascular low-density filling defect (black arrow) was observed. Enlarged lymph nodes were observed around the lesion, the short diameter was 7 mm (orange arrow), the CT stage was CT-T4aN1, and the CT-EMVI score was 4, indicating positivity. The slopes of the energy spectrum curves in the EP are K40-70 = 5.18, IC = 27.41 (100 μg/cm³), NIC = 0.59, and Zeff = 9.14; E: The energy spectrum curve shows that the CT value at 40-140 keV in patient 2 is greater than that in patient 1, and the value of the slope is greater. The spectral parameters of patient 2 are greater than those of patient 1.

Figure 6

Comprehensive analysis of predictive models. A: Individual nomogram; B: Calibration curve; C: Decision curve analysis of the training cohort; D: Receiver operating characteristic (ROC) curves of the application of the nomogram, VP-70 keV, EP-NIC, CT-T and CT-EMVI to the training cohort. The DeLong test showed that the differences were significant between the nomogram and each single independent factor; E: ROC curve of the application of the nomogram to the training cohort and the validation cohort. CT-EMVI: Computed tomography-detected extramural vein invasion; VP-70 keV: Single-energy computed tomography value of 70 keV in the venous phase; EP-NIC: Ratio of the standardized iodine concentration in the equilibrium phase; ROC: Receiver operating characteristic; AUC: Area under the receiver operating characteristic curve.