A prediction model for lung metastases in patients with indeterminate pulmonary nodules in newly diagnosed colorectal cancer.

INTRODUCTION: Multidisciplinary teams treating patients with newly diagnosed Colorectal Cancer (CRC) often encounter the appearance of Indeterminate Pulmonary Nodules (IPNs) that warrants follow-up with repetitive medical imaging and anxiety for patients. We determined the incidence of IPNs in patients with newly diagnosed CRC and developed and validated a model for individualized risk prediction of IPNs being lung metastases. MATERIAL AND METHODS: Newly diagnosed CRC who underwent surgery between November 2011 to June 2014 were included to create the risk model, developed using both clinical experience and statistical selection. Discrimination and calibration slopes of the risk score were evaluated in an independent temporal validation sample. A nomogram is presented to assist clinicians in estimating an individual risk score. RESULTS: Out of 2111 CRC patients staged with chest CT, 204 (9.6%) had IPNs and 54/204 (26%) had lung metastases. We identified 4 predictors: "location of primary tumour", "pathological nodal stage", "size of the largest nodule" and "extrapulmonary synchronous metastases at diagnosis". Discrimination of the final model in the validation sample was demonstrated by the difference in mean predicted risk between progressed cases en non-progressed cases (49% versus 21%, p = <0.001). CONCLUSION: A prediction model with 4 clinical risk factors can be used to assist multidisciplinary teams in the prediction of individualized risk of lung metastases and imaging strategy in patients with IPNs and newly diagnosed colorectal cancer. The model performed well in new patients not included in the model development.

Prediction of pulmonary metastasis in esophageal carcinoma patients with indeterminate pulmonary nodules.

BACKGROUND: Indeterminate pulmonary nodules (IPNs) are common after surgery for esophageal cancer. The paucity of data on postoperative IPNs for esophageal cancer causes a clinical dilemma. OBJECTIVE: The aim of this study was to identify the characteristics and clinical significance of IPNs after radical esophagectomy for metastatic esophageal cancer, determine the risk factors for pulmonary metastasis, and construct a risk score model to standardize the appropriate time to either follow up or treat the patient. METHODS: All consecutive patients with esophageal squamous cell carcinoma (ESCC) who underwent radical surgery between 2013 and 2016 were included in this retrospective study. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors and develop risk score models. RESULTS: A total of 816 patients were enrolled in the study. During a median follow-up period of 45 months, IPNs were detected in 221 (27.1%) patients, of whom 66 (29.9%) were diagnosed with pulmonary metastases. The following five variables maintained prognostic significance after multivariate analyses: the pathologic N category, number of IPNs, shape of IPNs, time of detection of IPNs, and size of IPNs. The Pulmonary Metastasis Prediction Model (PMPM) scale ranges from 0 to 15 points, and patients with higher scores have a higher probability of pulmonary metastases. The Hosmer-Lemeshow test showed a good calibration performance of the clinical prediction model (χ2 = 8.573, P = 0.380). After validation, the PMPM scale showed good discrimination with an AUC of 0.939. CONCLUSION: A PMPM scale for IPNs in patients who underwent esophagectomy for ESCC may be clinically useful for diagnostic and therapeutic decision-making.

Analysis of the interactions between small pulmonary nodules, clinical factors and the risk of malignancy in the chest following diagnosis of head and neck cancer.

BACKGROUND: This study aims to investigate radiological and clinical factors which predict malignancy in indeterminate pulmonary nodules in patients with head and neck cancer (HNC). METHODS: Prospective data were collected in 424 patients who were reviewed in the NHS Lothian HNC multidisciplinary meeting from May 2016 to May 2018. Staging and follow-up CT chest imaging were reviewed to identify and assess pulmonary nodules in all patients. RESULTS: About 61.8% of patients had at least one pulmonary nodule at staging CT. In total, 25 patients developed malignancy in the chest. Metastatic disease in the chest was significantly associated with unknown or negative p16 status (p < .0005). Pleural indentation and spiculation were associated with indeterminate nodules, subsequently being shown to represent metastatic disease (p > .0005 and p = .046, respectively). CONCLUSION: Negative or unknown p16 status was associated with an increased propensity to develop metastatic disease in the chest in patients with HNC.

Prognostic significance of the ratio of surgically resected to radiologically detected lung nodules in patients with metastatic osteosarcoma.

The factors that affect the prognosis of patients' metastatic osteosarcoma are still poorly understood. In this study, we investigated a new prognostic factor, the ratio of surgically resected to radiologically detected osteosarcoma lung nodules (SR/RD), which may have predictive value. PATIENTS AND METHODS: Data from patients with metastatic osteosarcoma who underwent metastasectomy between January 2009 and December 2020, in a single center, were reviewed. The relationships between survival and the SR/RD ratio, timing of lung metastases, number of nodules, laterality, and presence of tumor necrosis at first metastasectomy were investigated. RESULTS: Among the 125 metastatic osteosarcoma patients, 80 patients had an SR/RD ratio ≤1. The median duration of follow-up was 72 months, ranging from 6 to 118 months. The five-year overall survival (OS) and postmetastasectomy event-free survival (EFS) for all patients were 36.5% and 18.1%, respectively. The five-year OS of patients with a low SR/RD ratio was 49.6% and that of patients with a high SR/RD ratio was 11.8 (P = 0.001). The two-year postmetastasectomy EFS rates of the high and low ratio groups were 24.1% and 9.4%, respectively (P = 0.001). The SR/RD ratio, number of nodules, and tumor necrosis had significant effects on OS and postmetastasectomy EFS in univariate analysis. A Cox proportional hazard model demonstrated that tumor necrosis and an SR/RD ratio >1 were associated with OS (HR = 1.8 and 2.01) and postmetastasectomy EFS (HR = 1,69 and 1.97). CONCLUSIONS: A high SR/RD ratio of greater than 1 and poor tumor necrosis were significantly associated with poor survival among patients with metastatic osteosarcoma who had lung metastasectomy. The high SR/RD ratio may be a surrogate outcome for incomplete metastatic tumor resection.

Dealing with indeterminate pulmonary nodules in colorectal cancer patients; a systematic review.

INTRODUCTION: Indeterminate pulmonary nodules (IPNs) are frequently encountered on staging computed tomography (CT) in colorectal cancer (CRC) patients and they create diagnostic dilemmas. This systematic review and pooled analysis aims to estimate the incidence and risk of malignancy of IPNs and provide an overview of the existing literature on IPNs in CRC patients. MATERIALS AND METHODS: EMBASE, Pubmed and the Cochrane database were searched for papers published between January 2005 and April 2020. Studies describing the incidence of IPNs and the risk of malignancy in CRC patients and where the full text was available in the English language were considered for inclusion. Exclusion criteria included studies that used chest X-ray instead of CT, liver metastasis cohorts, studies with less than 60 CRC patients and reviews. RESULTS: A total of 18 studies met the inclusion criteria, involving 8637 patients. Pooled analysis revealed IPNs on staging chest CT in 1327 (15%) of the CRC patients. IPNs appeared to be metastatic disease during follow up in 16% of these patients. Regional lymph node metastases, liver metastases, location of the primary tumour in the rectum, larger IPN size and multiple IPNs are the five most frequently reported parameters predicting the risk of malignancy of IPNs. CONCLUSION: A risk stratification model for CRC patients with IPNs is warranted to enable an adequate selection of high risk patients for IPN follow up and to diminish the use of unnecessary repetitive chest CT-scans in the many low risk patients.

Indeterminate Pulmonary Nodules in Osteosarcoma Are Associated With Increased Risk of Pulmonary Metastasis.

Osteosarcoma is the most common primary malignant bone tumor in children. In addition to pulmonary metastasis, computed tomography frequently detects indeterminate pulmonary nodules (IPN). We conducted this study to determine the clinical significance of IPN in terms of progression to pulmonary metastasis and its impact on survival. It was a retrospective cohort study of pediatric nonmetastatic osteosarcoma patients treated from January 2005 to December 2018. Baseline computed tomography scans were reviewed for the presence of IPN (defined as a single nodule of <10 mm or ≥3 nodules of <5 mm). Subsequent scans were reviewed for the development of pulmonary metastasis. Of 155 patients, 31.6% (n=49) had IPN at baseline. A total of 43% (n=21) of those with IPN subsequently progressed to pulmonary metastasis compared with only 26% (n=28) of those without IPN (P<0.001) with a relative risk of 1.6 (1.03 to 2.5) in the IPN group. Patients with ≥3 IPN at baseline were at significantly greater risk of pulmonary metastasis as compared with <3 IPN (P=0.013). Overall and event-free survival in patients with and without IPN was 58% and 35%, and 72% and 46%, respectively. Our results suggest that patients with IPN may be at greater risk for progressing to pulmonary metastasis.

Clinical significance of subcentimeter pulmonary nodules in patients undergoing hepatectomy for colorectal liver metastases.

BACKGROUND AND OBJECTIVES: The clinical significance of lung metastases regarded as subcentimeter pulmonary nodules (SPN) before hepatectomy for colorectal liver metastases (CLM) has not been assessed well. METHODS: The data from 569 patients undergoing hepatectomy for CLM from 2010 to 2016 were reviewed. The presence and final diagnosis of SPN were analyzed for their association with overall survival (OS). RESULTS: A total of 143 patients had SPN (25.1%). SPN were proved to be lung metastases in 43 patients (30.1%). Before hepatectomy, lung metastases were suspected in 25 patients (sensitivity: 58%; specificity: 100%). The 5-year OS of patients with lung metastases (45.4%) was worse than that of those with no pulmonary nodules (60.9%, P = .003). There was no significant difference in the 5-year OS between the patients with lung metastases diagnosed after hepatectomy (48.7%) and before hepatectomy (41.2%, P = .432). The 5-year OS of patients who underwent surgery for lung metastases after hepatectomy (60.5%) was similar to that of those with no pulmonary nodules and benign pulmonary nodules (60.9%, P = .6310; 44.0%, P = .899). CONCLUSION: Although diagnostic sensitivity for SPN before hepatectomy is low, timing of diagnosis does not affect OS. Conclusive lung resection offers OS similar to that of patients without lung metastases.

Linear mixed-effects models for estimation of pulmonary metastasis growth rate: implications for CT surveillance in patients with sarcoma.

OBJECTIVES: Sarcoma patients often undergo surveillance chest CT for detection of pulmonary metastases. No data exist on the optimal surveillance interval for chest CT. The aim of this study was to estimate pulmonary metastasis growth rate in sarcoma patients. METHODS: This was a retrospective review of 95 patients with pulmonary metastases (43 patients with histologically confirmed metastases and 52 with clinically diagnosed metastases) from sarcoma treated at an academic tertiary-care center between 01 January 2000 and 01 June 2019. Age, sex, primary tumor size, grade, subtype, size and volume of the pulmonary metastasis over successive chest CT scans were recorded. Two metastases per patient were chosen if possible. Multivariate linear mixed-effects models with random effects for each pulmonary metastasis and each patient were used to estimate pulmonary metastasis growth rate, evaluating the impact of patient age, tumor size, tumor grade, chemotherapy and tumor subtype. We estimated the pulmonary metastasis volume doubling time using these analyses. RESULTS: Maximal primary tumor size at diagnosis (LRT statistic = 2.58, df = 2, p = 0.275), tumor grade (LRT statistic = 1.13, df = 2, p = 0.567), tumor type (LRT statistic = 7.59, df = 6, p = 0.269), and patient age at diagnosis (LRT statistic = 0.735, df = 2, p = 0.736) were not statistically significant predictors of pulmonary nodule growth from baseline values. Chemotherapy decreased the rate of pulmonary nodule growth from baseline (LRT statistic = 7.96, df = 2, p = 0.0187). 95% of untreated pulmonary metastases are expected to grow less than 6 mm in 6.4 months. There was significant intrapatient and interpatient variation in pulmonary metastasis growth rate. Pulmonary metastasis volume growth rate was best fit with an exponential model in time. The volume doubling time for pulmonary metastases assuming an exponential model in time was 143 days (95% CI (104, 231) days). CONCLUSIONS: Assuming a 2 mm nodule is the smallest reliably detectable nodule by CT, the data suggest that an untreated pulmonary metastasis is expected to grow to 8 mm in 8.4 months (95% CI (4.9, 10.2) months). Tumor size, grade and sarcoma subtype did not significantly alter pulmonary metastasis growth rate. However, chemotherapy slowed the pulmonary metastasis growth rate. ADVANCES IN KNOWLEDGE: CT surveillance intervals for pulmonary metastases can be estimated based on metastasis growth rate. There was significant variation in the pulmonary metastasis growth rate between metastases within patient and between patients. Pulmonary nodule volume growth followed an exponential model, linear in time.

The yield of chest computed tomography in patients with locally advanced pancreatic cancer.

OBJECTIVE: To evaluate the incidence of pulmonary metastases on chest computed tomography (CT) in patients with locally advanced pancreatic cancer (LAPC). METHODS: All patients diagnosed with LAPC in a single tertiary center (Erasmus MC) between October 2011 and December 2017 were reviewed. The staging chest CT scan and follow-up chest CT scans were evaluated. Pulmonary nodules were divided into three categories: apparent benign, too small to characterize, and apparent malignant. RESULTS: In 124 consecutive patients diagnosed with LAPC, 119 (96%) patients underwent a staging chest CT scan at the initial presentation. In 88 (74%) patients no pulmonary nodules were found; in 16 (13%) patients an apparent benign pulmonary nodule was found, and in 15 (13%) patients a pulmonary nodule too small to characterize was found. Follow-up chest CT scan(s) were performed in 111 (93%) patients. In one patient with either no pulmonary nodule or an apparent benign pulmonary nodule at initial staging, an apparent malignant pulmonary nodule was found on a follow-up chest CT scan. However, a biopsy of the nodule was inconclusive. Of 15 patients in whom a pulmonary nodule too small to characterize was found at staging, 12 (80%) patients underwent a follow-up CT scan; in 4 (33%) of these patients, an apparent malignant pulmonary nodule was found. CONCLUSION: In patients with LAPC in whom at diagnosis a chest CT scan revealed either no pulmonary nodules or apparent benign pulmonary nodules, routine follow-up chest CT scans is not recommended. Patients with pulmonary nodules too small to characterize are at risk to develop apparent malignant pulmonary nodules during follow-up.

The diagnostic significance of pulmonary nodules on CT thorax in chondrosarcoma of bone.

AIM: To provide a diagnostic approach to pulmonary nodules in patients with chondrosarcoma. MATERIALS AND METHODS: A search of the oncology database at a specialist orthopaedic oncology referral centre was performed to identify all patients who were treated surgically for chondrosarcoma between January 2007 and December 2018. Reports from the computed tomography (CT) examinations of the thorax of these patients were reviewed. In patients who had pulmonary nodules/metastases identified on CT, data on the primary chondrosarcoma and pulmonary nodule characteristics were collected. RESULTS: Twenty point two percent of patients had a pulmonary nodule identified on either initial or follow-up staging CT of the thorax, of which 8.1% were pulmonary metastases. Patients with grade 3 and dedifferentiated chondrosarcoma were more likely to have pulmonary metastases than patients with grade 1/2 chondrosarcoma. The time interval to developing metastases was shorter in patients with grade 2/3 and dedifferentiated chondrosarcoma versus patients with grade 1 chondrosarcoma. A low proportion of patients with grade 1 chondrosarcoma developed metastases (12.5%), all of which were identified at the time of a local recurrence. Nodules ≥10mm, nodules with lobulate margins, nodules containing irregular or subtle calcification, and nodules seen bilaterally or both centrally and peripherally were more likely to represent pulmonary metastases than benign nodules. CONCLUSION: The diagnostic significance of pulmonary nodules (i.e., whether they represent pulmonary metastases or not) can be predicted by taking into account a number of factors, in particular, the histological grade of the patient's chondrosarcoma, the size and margins of the nodules, and the presence of subtle/irregular calcification.

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance.

OBJECTIVES: To evaluate the diagnostic performance of a deep learning algorithm for automated detection of small 18F-FDG-avid pulmonary nodules in PET scans, and to assess whether novel block sequential regularized expectation maximization (BSREM) reconstruction affects detection accuracy as compared to ordered subset expectation maximization (OSEM) reconstruction. METHODS: Fifty-seven patients with 92 18F-FDG-avid pulmonary nodules (all ≤ 2 cm) undergoing PET/CT for oncological (re-)staging were retrospectively included and a total of 8824 PET images of the lungs were extracted using OSEM and BSREM reconstruction. Per-slice and per-nodule sensitivity of a deep learning algorithm was assessed, with an expert readout by a radiologist/nuclear medicine physician serving as standard of reference. Receiver-operator characteristic (ROC) curve of OSEM and BSREM were assessed and the areas under the ROC curve (AUC) were compared. A maximum standardized uptake value (SUVmax)-based sensitivity analysis and a size-based sensitivity analysis with subgroups defined by nodule size was performed. RESULTS: The AUC of the deep learning algorithm for nodule detection using OSEM reconstruction was 0.796 (CI 95%; 0.772-0.869), and 0.848 (CI 95%; 0.828-0.869) using BSREM reconstruction. The AUC was significantly higher for BSREM compared to OSEM (p = 0.001). On a per-slice analysis, sensitivity and specificity were 66.7% and 79.0% for OSEM, and 69.2% and 84.5% for BSREM. On a per-nodule analysis, the overall sensitivity of OSEM was 81.5% compared to 87.0% for BSREM. CONCLUSIONS: Our results suggest that machine learning algorithms may aid detection of small 18F-FDG-avid pulmonary nodules in clinical PET/CT. AI performed significantly better on images with BSREM than OSEM. KEY POINTS: • The diagnostic value of deep learning for detecting small lung nodules (≤ 2 cm) in PET images using BSREM and OSEM reconstruction was assessed. • BSREM yields higher SUVmaxof small pulmonary nodules as compared to OSEM reconstruction. • The use of BSREM translates into a higher detectability of small pulmonary nodules in PET images as assessed with artificial intelligence.

An extremely rare case of adrenocortical cancer with cannon ball pulmonary metastasis.

Multiple pulmonary nodules on chest X-ray, known commonly as cannon ball secondaries, are the classical presentation of hematogenous dissemination of a malignant tumor to the lungs. This almost always indicates an advanced stage of the disease with a very grim outlook in terms of cure or survival. In this case report, we present a patient with very extensive cannon ball lung metastases due to adrenocortical carcinoma with a more favorable prognosis. This is the first case described in the literature of cannonball lung metastases from adrenocortical tumor in a man.

Near-infrared intraoperative imaging for minimally invasive pulmonary metastasectomy for sarcomas.

BACKGROUND: Complete pulmonary metastasectomy for sarcoma metastases provides patients an opportunity for long-term survival and possible cure. Intraoperative localization of preoperatively identified metastases and identification of occult lesions can be challenging. In this trial, we evaluated the efficacy of near-infrared (NIR) intraoperative imaging using second window indocyanine green during metastasectomy to identify known metastases and to detect occult nodules. METHODS: Thirty patients with pulmonary nodules suspicious for sarcoma metastases were enrolled in an open-label, feasibility study (NCT02280954). All patients received intravenous indocyanine green (5 mg/kg) 24 hours before metastasectomy. Patients 1 through 10 (cohort 1) underwent metastasectomy via thoracotomy to assess fluorescence patterns of nodules detected by traditional methods (preoperative imaging and intraoperative visualization/bimanual palpation). After confirming reliability within cohort 1, patients 11 through 30 (cohort 2) underwent video-assisted thoracic surgery metastasectomy with NIR imaging. RESULTS: In cohort 1, 14 out of 16 preoperatively identified pulmonary metastases (87.5%) displayed tumor fluorescence. Nonfluorescent metastases were deeper than fluorescent metastases (2.1 cm vs 1.3 cm; P = .03). Five out of 5 metastases identified during thoracotomy displayed fluorescence. NIR imaging identified 3 additional occult lesions in this cohort. In cohort 2, 33 out of 37 known pulmonary metastases (89.1%) displayed fluorescence. Nonfluorescent tumors were deeper than 2.0 cm (P = .007). NIR imaging identified 24 additional occult lesions. Of 24 occult lesions, 21 (87.5%) were confirmed metastases and the remaining 3 nodules were lymphoid aggregates. CONCLUSIONS: NIR intraoperative imaging with indocyanine green (5 mg/kg and 24 hours before surgery) localizes known sarcoma pulmonary metastases and identifies otherwise occult lesions. This approach may be a useful intraoperative adjunct to improve metastasectomy.

Indeterminate Pulmonary Nodules at Diagnosis in Rhabdomyosarcoma: Are They Clinically Significant? A Report From the European Paediatric Soft Tissue Sarcoma Study Group.

PURPOSE: To evaluate the clinical significance of indeterminate pulmonary nodules at diagnosis (defined as ≤ 4 pulmonary nodules < 5 mm or 1 nodule measuring ≥ 5 and < 10 mm) in patients with pediatric rhabdomyosarcoma (RMS). PATIENTS AND METHODS: We selected patients with supposed nonmetastatic RMS treated in large pediatric oncology centers in the United Kingdom, France, Italy, and the Netherlands, who were enrolled in the European Soft Tissue Sarcoma Study Group (E pSSG) RMS 2005 study. Patients included in the current study received a diagnosis between September 2005 and December 2013, and had chest computed tomography scans available for review that were done at time of diagnosis. Local radiologists were asked to review the chest computed tomography scans for the presence of pulmonary nodules and to record their findings on a standardized case report form. In the E pSSG RMS 2005 Study, patients with indeterminate pulmonary nodules were treated identically to patients without pulmonary nodules, enabling us to compare event-free survival and overall survival between groups by log-rank test. RESULTS: In total, 316 patients were included; 67 patients (21.2%) had indeterminate pulmonary nodules on imaging and 249 patients (78.8%) had no pulmonary nodules evident at diagnosis. Median follow-up for survivors (n = 258) was 75.1 months; respective 5-year event-free survival and overall survival rates (95% CI) were 77.0% (64.8% to 85.5%) and 82.0% (69.7% to 89.6%) for patients with indeterminate nodules and 73.2% (67.1% to 78.3%) and 80.8% (75.1% to 85.3%) for patients without nodules at diagnosis ( P = .68 and .76, respectively). CONCLUSION: Our study demonstrated that indeterminate pulmonary nodules at diagnosis do not affect outcome in patients with otherwise localized RMS. There is no need to biopsy or upstage patients with RMS who have indeterminate pulmonary nodules at diagnosis.