Computed tomography/magnetic resonance imaging for mandibular boundary invasion of oral squamous cell carcinoma assessment.

BACKGROUND: The range of mandibular invasion by a tumour needs to be determined accurately to minimize unnecessary damage to the mandible. This study aimed to compare tumour boundary lines on computed tomography/magnetic resonance (CT/MR) images with those from pathological findings during the preoperative assessment of mandibular invasion by oral squamous cell carcinoma (OSCC). By comparing the methods, the potential of CT/MR for this application could be further elucidated. METHODS: Eight patients with OSCC were imaged with CT/MR, mandibular specimens were collected, and the material site was measured. Haematoxylin-eosin staining was used for histopathological assessment. The presence and boundaries of bone invasion were evaluated. The CT/MR and histopathological boundaries of bone invasion were delineated and merged to compare and calculate the deviation of CT/MR and histopathological boundaries using the Fréchet distance. RESULTS: The mean Fréchet distance between the CT and pathological tumour boundaries was 2.69 mm (standard error 0.46 mm), with a minimum of 1.18 mm, maximum of 3.64 mm, median of 3.10 mm, and 95% confidence interval of 1.40-3.97 mm. The mean Fréchet distance between the tumour boundaries on the MR and pathological images was 3.07 mm (standard error 0.56 mm), with a minimum of 1.53 mm, maximum of 4.74 mm, median of 2.90 mm, and 95% confidence interval of 1.53-4.61 mm. CONCLUSIONS: CT/MR imaging can provide an effective preoperative assessment of mandibular invasion of OSCC. Pathology images can be positioned on CT/MR scans with the help of computer software to improve the accuracy of the findings. The introduction of the Fréchet distance to compare tumour boundary lines is conducive to computer image diagnosis of tumour invasion of jaw boundaries.

Nutritional assessment and prognosis of oral cancer patients: a large-scale prospective study.

BACKGROUND: To evaluate and compare the prognostic performance of four nutritional indicators body mass index (BMI), serum albumin (ALB), prognostic nutritional index (PNI) and nutritional risk index (NRI) in oral cancer patients, and to predict the response to chemotherapy in patients with different nutritional status. METHODS: This prospective study which involved 1395 oral cancer patients was conducted in Fujian, China from September 2007 to November 2018. The BMI, PNI and NRI were calculated according to the following formulas: BMI = weight / height2 (kg/m2), PNI = albumin (g/l) + 0.005 × lymphocyte (count/µl) and NRI = (1.519 × albumin, g/l) + (41.7× present/ideal body weight), respectively. The univariate and multivariate Cox proportional hazards models were used to compare the prognostic value of BMI, ALB, PNI and NRI in overall survival (OS) in oral cancer. RESULTS: Patients with BMI < 18.5 kg/m2 (VS 18.5 kg/m2 ≤ BMI < 24 kg/m2) had a poor survival outcome (HR = 1.585; 95% CI: 1.207-2.082 ). ALB, PNI, NRI were inversely correlated with OS of oral cancer (HR = 0.716; 95% CI: 0.575-0.891; HR = 0.793; 95% CI: 0.633-0.992; HR = 0.588; 95% CI: 0.469-0.738, respectively). In addition, the prognostic predictive performance of NRI was superior to BMI or ALB or PNI. Interestingly, compared with patients with better nutritional status, chemotherapy was significantly associated with poorer OS in malnourished oral cancer patients. CONCLUSIONS: BMI, ALB, PNI and NRI are of prognostic value in patients with oral cancer and the prognostic performance of NRI was superior to BMI or ALB or PNI. Malnutrition (BMI < 18.5 kg/m2 or ALB< 40 g/l or PNI < 49.3 or NRI < 97.5) could predict an unfavorable response to chemotherapy in oral cancer patients.