Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules.

For patients with early multiple pulmonary nodules, it is essential, from a diagnostic perspective, to determine the spatial distribution, size, location, and relationship with surrounding lung tissue of these nodules throughout the entire lung. This is crucial for identifying the primary lesion and developing more scientifically grounded treatment plans for doctors. However, pattern recognition methods based on machine vision are susceptible to false positives and false negatives and, therefore, cannot fully meet clinical demands in this regard. Visualization methods based on maximum intensity projection (MIP) can better illustrate local and individual pulmonary nodules but lack a macroscopic and holistic description of the distribution and spatial features of multiple pulmonary nodules. Therefore, this study proposes a whole-lung 3D reconstruction method. It extracts the 3D contour of the lung using medical image processing technology against the background of the entire lung and performs 3D reconstruction of the lung, pulmonary artery, and multiple pulmonary nodules in 3D space. This method can comprehensively depict the spatial distribution and radiological features of multiple nodules throughout the entire lung, providing a simple and convenient means of evaluating the diagnosis and prognosis of multiple pulmonary nodules.

Diagnostic Accuracy of CT-Guided Percutaneous Pulmonary Biopsy for Distinguishing Benign and Malignant Solitary Pulmonary Nodules.

Background: Isolated pulmonary nodules (SPNs) are small, circular lesions within lung tissue, often challenging to diagnose due to their size and lack of typical imaging features. Timely diagnosis is crucial for treatment decisions. However, the difficulty in qualitative diagnosis necessitates clinical biopsies. Objective: This study aimed to assess the diagnostic accuracy of CT-guided percutaneous lung biopsy for SPNs and identify potential risk factors for malignancy. Methods: We conducted a retrospective analysis of 112 patients with SPNs who underwent CT-guided core needle biopsy (CT-CNB) between June 2020 and June 2022. Histological and cytological results were obtained for all patients, and clinical data and imaging characteristics were compared between benign and malignant SPN groups. Binary logistic regression was used to analyze risk factors for malignancy, and complications were observed. Results: Cytological and histological specimens were successfully obtained for all patients. The cohort consisted of 43 patients with benign SPNs and 69 with malignant SPNs. Among the malignant SPN group, 67 cases were confirmed via CT-CNB and 2 through surgery, resulting in a sensitivity of 97.10% and specificity of 100.00%. The malignant nodules comprised 45 adenocarcinomas, 14 squamous cell carcinomas, 8 metastatic tumors, and 2 small cell carcinomas. Notably, 2 initially diagnosed as malignant cases were found to have chronic inflammation on preoperative biopsy but revealed adenocarcinoma and squamous cell carcinoma post-surgery. The benign nodules encompassed 20 granulomatous inflammation cases, 15 chronic inflammation, 3 fungal granulomas, 2 hamartomas, and 1 fibrous tissue. Cytological smears exhibited a sensitivity of 81.3% and a specificity of 100.0% for malignancy. Significantly, age ≥60, elevated tumor markers, and specific imaging signs (burr, foliation, pleural pull) were identified as risk factors for malignant SPNs using Binary Logistic regression (all P < .05). Conclusions: CT-guided percutaneous lung biopsy demonstrates excellent diagnostic efficacy and safety for distinguishing benign and malignant SPNs.

Natural Language Processing to Identify Pulmonary Nodules and Extract Nodule Characteristics From Radiology Reports.

BACKGROUND: There is an urgent need for population-based studies on managing patients with pulmonary nodules. RESEARCH QUESTION: Is it possible to identify pulmonary nodules and associated characteristics using an automated method? STUDY DESIGN AND METHODS: We revised and refined an existing natural language processing (NLP) algorithm to identify radiology transcripts with pulmonary nodules and greatly expanded its functionality to identify the characteristics of the largest nodule, when present, including size, lobe, laterality, attenuation, calcification, and edge. We compared NLP results with a reference standard of manual transcript review in a random test sample of 200 radiology transcripts. We applied the final automated method to a larger cohort of patients who underwent chest CT scan in an integrated health care system from 2006 to 2016, and described their demographic and clinical characteristics. RESULTS: In the test sample, the NLP algorithm had very high sensitivity (98.6%; 95% CI, 95.0%-99.8%) and specificity (100%; 95% CI, 93.9%-100%) for identifying pulmonary nodules. For attenuation, edge, and calcification, the NLP algorithm achieved similar accuracies, and it correctly identified the diameter of the largest nodule in 135 of 141 cases (95.7%; 95% CI, 91.0%-98.4%). In the larger cohort, the NLP found 217,771 reports with nodules among 717,304 chest CT reports (30.4%). From 2006 to 2016, the number of reports with nodules increased by 150%, and the mean size of the largest nodule gradually decreased from 11 to 8.9 mm. Radiologists documented the laterality and lobe (90%-95%) more often than the attenuation, calcification, and edge characteristics (11%-14%). INTERPRETATION: The NLP algorithm identified pulmonary nodules and associated characteristics with high accuracy. In our community practice settings, the documentation of nodule characteristics is incomplete. Our results call for better documentation of nodule findings. The NLP algorithm can be used in population-based studies to identify pulmonary nodules, avoiding labor-intensive chart review.

The Utility of Indigo Carmine and Lipiodol Mixture for Preoperative Pulmonary Nodule Localization before Video-Assisted Thoracic Surgery.

PURPOSE: To evaluate the safety and efficacy of a mixture of indigo carmine and lipiodol (MIL) as a marker of pulmonary nodule before video-assisted thoracic surgery (VATS). MATERIALS AND METHODS: One hundred sixty-eight sessions of pulmonary marking were performed using MIL before VATS for 184 nodules (mean size, 1.2 ± 0.6 cm; range, 0.3-3.6 cm) on 157 patients (83 men and 74 women; median age, 66 years). The mean distance between the lung surface and the nodule was 0.8 ± 0.7 cm (range, 0-3.9 cm). MIL was injected near the nodule using a 23-gauge needle. Mean number of 1.2 ± 0.4 (range, 1-3) punctures were performed in a session for the target nodules, with mean number of 1.1 ± 0.3 (range, 1-3). Successful targeting, localization, and VATS were defined as achievement of lipiodol accumulation at the target site on computed tomography, detection of the nodule in the operative field by fluoroscopy or visualization of dye pigmentation, and complete resection of the target nodule with sufficient margin, respectively. RESULTS: The successful targeting rate was 100%, and the successful localization rate was 99.5%, with dye pigmentation for 160 nodules (87.0%) and intraoperative fluoroscopy for 23 nodules (12.5%). Successful VATS was achieved for 181 nodules (98.4%). Two nodules (1.1%) were not resectable, and surgical margin was positive in 1 nodule (0.5%). Complications requiring interventions occurred in 5 sessions (3.0%) and included pneumothorax with chest tube placement (n = 3) and aspiration (n = 2). No complication related to the injected MIL occurred. CONCLUSIONS: MIL was safe and useful for preoperative pulmonary nodule marking.

Marcación de nódulos pulmonares con lipiodol bajo tomografía computada: experiencia local y correlación anatomopatológica / Marking of pulmonary nodules with lipiodol by computerized tomography: local experience and anatomopathological correlation

El objetivo de este estudio es la descripción de la novedosa y poco invasiva técnica de marcación de pequeños nódulos pulmonares con lipiodol, guiado con TAC para su posterior resección por cirugía videotoracoscópica con apoyo radioscópico. Se trata de un estudio retrospectivo que incluye 51 pacientes consecutivos en un tiempo comprendido entre junio del 2012 a septiembre del 2017, obteniendo el diagnóstico final mediante la correlación anatomopatológica, representando los procesos malignos el 81% y los benignos el 19%. Mediante esta técnica se lograron identificar y extraer con éxito el 100% de los nódulos marcados, demostrándose la efectividad y seguridad del procedimiento por las mínimas complicaciones relacionadas.

The purpose of this study is describing a novel and minimally invasive technique of CT-guided marking of small pulmonary nodules with lipiodol prior to resection by videothoracoscopic surgery with radioscopic support. This is a retrospective study that includes 51 consecutive patients between June 2012 and September 2017, with the final diagnosis confirmed by pathology. Malignant nodules represented 81% of the cases with the remaining 19% being benign nodules. Through this technique, 100% of the marked nodules were successfully identified and extracted with few procedure related complications and no adverse clinical outcome, demonstrating the effectiveness and safety of the procedure.

The plasma glutamate concentration as a complementary tool to differentiate benign PET-positive lung lesions from lung cancer.

BACKGROUND: Pulmonary imaging often identifies suspicious abnormalities resulting in supplementary diagnostic procedures. This study aims to investigate whether the metabolic fingerprint of plasma allows to discriminate between patients with lung inflammation and patients with lung cancer. METHODS: Metabolic profiles of plasma from 347 controls, 269 cancer patients and 108 patients with inflammation were obtained by 1H-NMR spectroscopy. Models to discriminate between groups were trained by PLS-LDA. A test set was used for independent validation. A ROC curve was built to evaluate the diagnostic performance of potential biomarkers. RESULTS: Sensitivity, specificity, PPV and NPV of PET-CT to diagnose cancer are 96, 23, 76 and 71%. Metabolic profiles differentiate between cancer and inflammation with a sensitivity of 89%, a specificity of 87% and a MCE of 12%. Removal of the glutamate metabolite results in an increase of MCE (38%) and a decrease of both sensitivity and specificity (62%), demonstrating the importance of glutamate for discrimination. At the cut-off point 0.31 on the ROC curve, the relative glutamate concentration discriminates between cancer and inflammation with a sensitivity of 85%, a specificity of 81%, and an AUC of 0.88. PPV and NPV are 92 and 69%. In PET-positive patients with a relative glutamate level ≤ 0.31 the sensitivity to diagnose cancer reaches 100% with a PPV of 94%. In PET-negative patients, a relative glutamate level > 0.31 increases the specificity of PET from 23% to 58% and results in a high NPV of 100%. In case of discrepancy between SUVmax and the glutamate concentration, lung cancer is missed in 19% of the cases. CONCLUSION: This study indicates that the 1H-NMR-derived relative plasma concentration of glutamate allows discrimination between lung cancer and lung inflammation. A glutamate level ≤ 0.31 in PET-positive patients corresponds to the diagnosis of lung cancer with a higher specificity and PPV than PET-CT. Glutamate levels > 0.31 in patients with PET negative lung lesions is likely to correspond with inflammation. Caution is needed for patients with conflicting SUVmax values and glutamate concentrations. Confirmation is needed in a prospective study with external validation and by another analytical technique such as HPLC-MS.

Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines.

OBJECTIVES: To compare the PanCan model, Lung-RADS and the 1.2016 National Comprehensive Cancer Network (NCCN) guidelines for discriminating malignant from benign pulmonary nodules on baseline screening CT scans and the impact diameter measurement methods have on performances. METHODS: From the Danish Lung Cancer Screening Trial database, 64 CTs with malignant nodules and 549 baseline CTs with benign nodules were included. Performance of the systems was evaluated applying the system's original diameter definitions: Dlongest-C (PanCan), DmeanAxial (NCCN), both obtained from axial sections, and Dmean3D (Lung-RADS). Subsequently all diameter definitions were applied uniformly to all systems. Areas under the ROC curves (AUC) were used to evaluate risk discrimination. RESULTS: PanCan performed superiorly to Lung-RADS and NCCN (AUC 0.874 vs. 0.813, p = 0.003; 0.874 vs. 0.836, p = 0.010), using the original diameter specifications. When uniformly applying Dlongest-C, Dmean3D and DmeanAxial, PanCan remained superior to Lung-RADS (p < 0.001 - p = 0.001) and NCCN (p < 0.001 - p = 0.016). Diameter definition significantly influenced NCCN's performance with Dlongest-C being the worst (Dlongest-C vs. Dmean3D, p = 0.005; Dlongest-C vs. DmeanAxial, p = 0.016). CONCLUSIONS: Without follow-up information, the PanCan model performs significantly superiorly to Lung-RADS and the 1.2016 NCCN guidelines for discriminating benign from malignant nodules. The NCCN guidelines are most sensitive to nodule size definition. KEY POINTS: • PanCan model outperforms Lung-RADS and 1.2016 NCCN guidelines in identifying malignant pulmonary nodules. • Nodule size definition had no significant impact on Lung-RADS and PanCan model. • 1.2016 NCCN guidelines were significantly superior when using mean diameter to longest diameter. • Longest diameter achieved lowest performance for all models. • Mean diameter performed equivalently when derived from axial sections and from volumetry.

Comparative Effectiveness and Safety of Preoperative Lung Localization for Pulmonary Nodules: A Systematic Review and Meta-analysis.

BACKGROUND: An optimal method of preoperative localization for pulmonary nodules has yet to be established. This systematic review and meta-analysis aimed to compare the success and complication rates associated with three pulmonary nodule localization methods for video-assisted thoracoscopic surgery (VATS): hook-wire localization, microcoil localization, and lipiodol localization. METHODS: We searched the PubMed, MEDLINE, and EMBASE databases for prospective or retrospective English language studies of VATS localization in adult patients. A noncomparative, random effects model-based meta-analysis was performed to obtain pooled success and complication rates for the three localization methods. RESULTS: A total of 46 clinical studies were enrolled, including 30, 9, and 7 studies of hook-wire, microcoil, and lipiodol localization, respectively. The successful targeting rates for hook-wire, microcoil, and lipiodol localization were 0.98 (95% CI, 0.97-0.99), 0.98 (95% CI, 0.96-0.99), and 0.99 (95% CI, 0.98-1.00), respectively, with corresponding successful operative field targeting rates of 0.94 (95% CI, 0.91-0.96), 0.97 (95% CI, 0.95-0.98), and 0.99 (95% CI, 0.98-1.00), respectively. In addition, the successful VATS rates with hook-wire, microcoil, and lipiodol localization were 0.96 (95% CI, 0.94-0.97), 0.97 (95% CI, 0.94-0.99), and 0.99 (95% CI, 0.98-1.00), respectively. Regarding complications, hook-wire, microcoil, and lipiodol localization were associated with pneumothorax rates of 0.35 (95% CI, 0.28-0.43), 0.16 (95% CI, 0.07-0.34), and 0.31 (95% CI, 0.20-0.46), respectively and hemorrhage rates of 0.16 (95% CI, 0.11-0.23), 0.06 (95% CI, 0.03-0.11), and 0.12 (95% CI, 0.05-0.23), respectively. CONCLUSIONS: All three localization methods yielded similarly highly successful targeting rates. However, hook-wire localization had a relatively lower successful operative field targeting rate because of dislodgement or migration. Lipiodol localization had the highest overall success rate, and microcoil localization yielded the lowest complication rates.

A visual-search model observer for multislice-multiview SPECT images.

PURPOSE: Mathematical model observers are intended for efficient assessment of diagnostic image quality, but model-observer studies often are not representative of clinical realities. Model observers based on a visual-search (VS) paradigm may allow for greater clinical relevance. The author has compared the performances of several VS model observers with those of human observers and an existing scanning model observer for a study involving nodule detection and localization in simulated Tc-99m single-photon emission computed tomography (SPECT) lung volumes. METHODS: A localization receiver operating characteristic (LROC) study compared two iterative SPECT reconstruction strategies: an all-corrections (AllC) strategy with compensations for attenuation, scatter, and distance-dependent camera resolution and an "RC" strategy with resolution compensation only. Nodules in the simulation phantom were of three different relative contrasts. Observers in the study had access to the coronal, sagittal, and transverse displays of the reconstructed volumes. Three human observers each read 50 training volumes and 100 test volumes per reconstruction strategy. The same images were analyzed by a channelized nonprewhitening (CNPW) scanning observer and two VS observers. The VS observers implemented holistic search processes that identified focal points of Tc-99m uptake for subsequent analysis by the CNPW scanning model. The level of prior knowledge about the background structure in the images was a study variable for the model observers. Performance was scored by area under the LROC curve. RESULTS: The average human-observer performances were respectively 0.67 ± 0.04 and 0.61 ± 0.03 for the RC and AllC strategies. Given approximate knowledge about the background structure, both VS models scored 0.69 ± 0.08 (RC) and 0.66 ± 0.08 (AllC). The scanning observer reversed the strategy ranking in scoring 0.73 ± 0.08 with the AllC strategy and 0.64 ± 0.08 with the RC strategy. The VS observers exhibited less sensitivity to variations in background knowledge compared to the scanning observer. CONCLUSIONS: The VS framework has the potential to increase the clinical similitude of model-observer studies and to enhance the ability of existing model observers to quantitatively predict human-observer performance.

[Late revelation of air embolism after transthoracic needle biopsy]. / Embolie gazeuse de révélation tardive après ponction transpariétale pulmonaire.

INTRODUCTION: Percutaneous transthoracic needle biopsy is a useful and common procedure in the investigation of a lung nodule. The occurrence of air embolism after percutaneous transthoracic needle biopsy is extremely rare. CASE REPORT: We report a 62-year-old woman who presented with neurological signs including restlessness, meningeal signs and focal neurologic deficits 4 hours after percutaneous transthoracic lung biopsy, related to air embolism. The outcome was favorable with hyperbaric oxygen therapy. CONCLUSION: Percutaneous transthoracic needle biopsy complicated by air embolism has been rarely reported. It usually occurs within minutes after the biopsy. The late onset of this adverse event in our patient is exceptional. Air embolism occurs more frequently after biopsy of lung infiltrates compared to nodules. Occurrence of a pneumothorax or an intraalveolar haemorrhage following a percutaneous transthoracic needle biopsy may be warning manifestations and justify a close monitoring.

[Evaluation of an interactive breath-hold control system in CT-guided lung biopsy]. / Evaluation eines interaktiven Atemkontrollsystems bei der CT-gesteuerten Lungenbiopsie.

PURPOSE: In this study we assessed the effect of an interactive breath-hold control system on procedure time and technical success in transthoracic CT-guided lung biopsies. MATERIALS AND METHODS: In 36 patients (4 female, 32 male, mean age 65 years; range 33 - 88) with a pulmonary nodule, we performed CT-guided biopsy using a 18G Tru-cut needle (Cardinal Health, Dublin, UK) in a 64 row dual-source CT scanner (Somatom Definition, Siemens, Forchheim, Germany) using intermittent imaging of the needle. In half of the patients (2 female, 16 male, mean age 67 years), an interactive breath-hold control system (IBC) (Mayo Clinic Medical Devices, USA) was applied. No additional device was used in the control group. RESULTS: The biopsy was visually successful in all patients. The diameter of the target lesion was comparable in both groups (IBC: 30 +/- 19 mm; control: 28 +/- 15 mm). The number of imaging steps was significantly smaller (p < 0.05) and the intervention time was significantly shorter (p < 0.05) in the IBC group (IBC: 9 +/- 5 steps 17 +/- 10 min; control: 13 +/- 5 steps 26 +/- 12 min). CONCLUSION: Application of the IBC unit reduced the intervention time and radiation exposure in CT-guided Tru-cut biopsy of pulmonary nodules.

Massive systemic air embolism treated with hyperbaric oxygen therapy following CT-guided transthoracic needle biopsy of a pulmonary nodule.

A rare complication of computed tomography (CT)-guided biopsies of pulmonary lesions is systemic air embolism, with hyperbaric oxygen therapy being considered the mainstay of therapy. The authors describe the case of a 47-year-old man with a left upper lobe mass invading the chest wall who underwent CT-guided needle biopsy of a right lung base nodule to evaluate for metastatic disease. This procedure was complicated by massive systemic air embolism confirmed by CT scan. After initial resuscitative measures, the patient received on-site hyperbaric oxygen therapy and demonstrated no residual clinical sequelae from this complication.