Guideline on Management of Solitary Pulmonary Nodule

ACR Appropriateness Criteria® Incidentally Detected Indeterminate Pulmonary Nodule

Incidental pulmonary nodules are common. Although the majority are benign, most are indeterminate for malignancy when first encountered making their management challenging. CT remains the primary imaging modality to first characterize and follow-up incidental lung nodules. This document reviews available literature on various imaging modalities and summarizes management of indeterminate pulmonary nodules detected incidentally. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Is the Yedikule-solitary pulmonary nodule malignancy risk score sufficient to predict malignancy? An internal validation study

OBJECTIVES

We aimed to develop a malignancy risk score model for solitary pulmonary nodules (SPNs) using the demographic, radiological and clinical characteristics of patients in our centre. The model was then internally validated for malignancy risk estimation.

METHODS

A total of 270 consecutive patients who underwent surgery for SPN between June 2017 and May 2019 were retrospectively analysed. Using the receiver operating characteristic curve analysis, cut-off values were determined for radiological tumour diameter, maximum standardized uptake value and the Brock University probability of malignancy (BU-PM) model. The Yedikule-SPN malignancy risk model was developed using these cut-off values and demographic, radiological and clinical criteria in the first 180 patients (study cohort) and internally validated with the next 90 patients (validation cohort). The Yedikule-SPN model was then compared with the BU-PM model in terms of malignancy prediction.

RESULTS

Malignancy was reported in 171 patients (63.3%). Maximum standardized uptake value and BU-PM scores were sufficient to predict malignancy (P < 0.001 for both), while the effectiveness of nodule size determined on thoracic computed tomography did not reach statistical significance (P = 0.09). When the Yedikule-SPN model developed with the study cohort was applied to the validation cohort, it significantly predicted malignancy (area under the receiver operating characteristic curve: 0.883, 95% confidence interval: 0.827-0.957, P < 0.001). Comparison of patients in the validation group with Yedikule-SPN scores above (n = 53) and below (n = 37) the cut-off value of 65.75 showed that the malignancy rate was significantly higher among patients with Yedikule-SPN score over 65.75 (86.8% vs 21.6%, P < 0.001, odds ratio = 23.821, 95% confidence interval: 7.805-72.701). When compared with the BU-PM model in all patients, the Yedikule-SPN model tended to be a better predictor of malignancy (P = 0.06).

CONCLUSIONS

The internally validated Yedikule-SPN model is also a good predictor of the malignancy of SPN(s). Prospective and multicentre external validation studies with large patients' cohorts are needed.

Analysis of solitary pulmonary nodule after surgical resection in patients with 18F-FDG positron emission tomography integrated computed tomography in the preoperative work-up

INTRODUCTION

To analyse clinicopathological characteristics of patients operated for pulmonary solitary nodule (PSN) and 18F-FDG integrated PET-CT scan after surgical resection.

METHODOLOGY

Retrospective study on a prospective database of patients operated from January 2007 to October 2017 for PSN without preoperative diagnosis. Dependent variable was anatomopathological result (benign vs malignant) of PSN. Variables of the study were: age, sex, PET-CT uptake, SUVmax, smoking history, COPD, previous history of malignant disease, tumoral location, and tumour size on CT-scan.

RESULTS

A total of 305 patients were included in this study, 225 (73.8%) men, 80 (26.2%) women, mean age = 63.9 (range 29-86 years), mean size PSN = 1.68 (s.d. .65 cm), benign = 46 (15.1%), malignant = 258 (84.6%), type of resection: pulmonary wedge = 151 (49.5%), lobectomy = 141 (46.2%), segmentectomy = 12 (3.9%), exploratory intervention = 1 (0.3%). Postoperative mortality was 1.9%. COPD = 50.8% cases, previous cancer disease = 172 cases (56.4%), smoking history = 250 cases (82.0%), positive PET = 280 cases (91.8%), PSN in upper pulmonary fields = 204 cases (66.9%), median SUVmax = 3.4 (range 0-20.7). Backward stepwise binary logistic regression model showed that age, SUVmax, previous malignant disease and female sex were independent risk factors with statistical significance (p < .05). Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 94.6%, 23.4%, 87.1%, 44.0%, and 83.6% respectively. There were 14 false negative cases (4.6%) and 36 false positive cases (11.8%).

CONCLUSIONS

Age, SUVmax, previous malignant disease, and female sex were independent risk factors in our study. Each case should be individually evaluated in a multidisciplinary committee, and the patient's preferences or concerns should be kept in mind in decision-making. Surgical resection of PSN is not exempt from morbidity and mortality, even in sublobar or pulmonary wedge resection.

Solid Indeterminate Nodules with a Radiological Stability Suggesting Benignity: A Texture Analysis of Computed Tomography Images Based on the Kurtosis and Skewness of the Nodule Volume Density Histogram

Background

The number of incidental findings of pulmonary nodules using imaging methods to diagnose other thoracic or extrathoracic conditions has increased, suggesting the need for in-depth radiological image analyses to identify nodule type and avoid unnecessary invasive procedures.

Objectives

The present study evaluated solid indeterminate nodules with a radiological stability suggesting benignity (SINRSBs) through a texture analysis of computed tomography (CT) images.

Methods

A total of 100 chest CT scans were evaluated, including 50 cases of SINRSBs and 50 cases of malignant nodules. SINRSB CT scans were performed using the same noncontrast enhanced CT protocol and equipment; the malignant nodule data were acquired from several databases. The kurtosis (KUR) and skewness (SKW) values of these tests were determined for the whole volume of each nodule, and the histograms were classified into two basic patterns: peaks or plateaus.

Results

The mean (MEN) KUR values of the SINRSBs and malignant nodules were 3.37 ± 3.88 and 5.88 ± 5.11, respectively. The receiver operating characteristic (ROC) curve showed that the sensitivity and specificity for distinguishing SINRSBs from malignant nodules were 65% and 66% for KUR values >6, respectively, with an area under the curve (AUC) of 0.709 (p < 0.0001). The MEN SKW values of the SINRSBs and malignant nodules were 1.73 ± 0.94 and 2.07 ± 1.01, respectively. The ROC curve showed that the sensitivity and specificity for distinguishing malignant nodules from SINRSBs were 65% and 66% for SKW values >3.1, respectively, with an AUC of 0.709 (p < 0.0001). An analysis of the peak and plateau histograms revealed sensitivity, specificity, and accuracy values of 84%, 74%, and 79%, respectively.

Conclusions

KUR, SKW, and histogram shape can help to noninvasively diagnose SINRSBs but should not be used alone or without considering clinical data.

18F-FDG positron emission tomography in oncology: main indications

The development of molecular and functional imaging with new imaging techniques such as computed tomography, magnetic resonance imaging, and positron emission tomography (PET) among others, has greatly improved the detection of tumors, tumor staging, and the detection of possible recurrences. Furthermore, the combination of these different imaging modalities and the continual development of radiotracers for PET have advanced our understanding and knowledge of the different pathophysiological processes in cancer, thereby helping to make treatment more efficacious, improving patients' quality of life, and increasing survival. PET is one of the imaging techniques that has attracted the most interest in recent years for its diagnostic capabilities. Its ability to anatomically locate pathologic foci of metabolic activity has revolutionized the detection and staging of many tumors, exponentially broadening its potential indications not only in oncology but also in other fields such as cardiology, neurology, and inflammatory and infectious diseases.