Comparing fluorodeoxyglucose positron emission tomography with computed tomography in staging for nodal and distant metastasis in urothelial/bladder cancer

Objectives

We aim to assess the clinical value of 18F-fluorodeoxyglucose positron (18F-FDG-PET) scan in detecting nodal and distant metastasis compared with computed tomography (CT) scan in patients with urothelial carcinoma or bladder cancer, aiming to improve staging accuracy and thereby better prognosticate and determine therapy.

Methods

A retrospective review of 75 patients with invasive bladder cancer (≥T1) who were staged with both CT and 18F-FDG-PET within an 8-week interval was performed for the period between 2015 and 2020. Seventy-two per cent (54/75) had formal pelvic lymph node (LN) dissection or biopsy of lesions suspicious for metastases. FDG-PET definitions for positive sites were assessed depending on SUV Max (nodes with SUVmax >4 at any size, SUV > 2 for lymph nodes >8 mm, or any SUV if the lymph node was >10 mm on axial images). For CT scanning, enlarged LN by RECIST 1.1 criteria (>10 mm) as well as qualitative findings suggesting metastasis were considered positive. The analysis was based on the comparison of CT and 18F-FDG-PET findings to histopathology results from LN dissection or biopsies.

Results

Sensitivity, specificity, positive predictive values (PPV) and negative predictive value (NPV) of CT versus FDG-PET for detecting metastasis, in patients who underwent pelvic LN dissection or biopsy of lesions suspicious of metastases, were 46.6% (95% CI: 21%-70%) versus 60% (95% CI: 32%-84%), 100% (95% CI: 91%-100%) versus 83.78% (95% CI: 69%-94%), 100% (95% CI: 63%-100%) versus 60% (95% CI: 32%-84%), and 82.2% (95% CI: 68%-92%) versus 83.78% (95% CI: 69%-94%), respectively. 7/75 (9.3%) patients avoided cystectomy due to 18F-FDG-PET features of metastases that were not detected by CT.

Conclusion

FDG-PET may be more sensitive than CT for metastases in the staging of bladder cancer, which resulted in significant avoidance of aggressive local management in cases with occult metastasis.

Latin American Consensus for the Evaluation and Treatment of Patients With Metastatic/Locally Advanced Urothelial Carcinoma

PURPOSE

Urothelial cancer accounts for approximately 3% of new cancer cases worldwide, with a high burden of disease in countries with medium and low human development indexes where its incidence and mortality are increasing. The purpose of this consensus is to develop statements on the evaluation and treatment of locally advanced and metastatic urothelial carcinoma that would further guide the clinical practice in Latin America.

METHODS

A systematic review of the literature was conducted by an independent team of methodologists. Then, a modified Delphi method was developed with clinical specialists from different Latin American countries.

RESULTS

Forty-two consensus statements, based on evidence, were developed to address the staging, the evaluation (suitability for chemotherapy, risk assessment, and biomarkers), and systemic treatment (first-line and subsequent therapies) of locally advanced or metastatic urothelial carcinoma. The statements made in this consensus are suggested practice recommendations in the Latin American context; however, the importance of a complete and individualized patient evaluation as a guide for therapeutic selection is highlighted. The availability and affordability of support tools for the evaluation of the disease, as well as specific therapies, may limit the application of the best practices suggested.

RECOMMENDATIONS

Therapeutic decisions need to be tailored to the context-specific clinical setting and availability of resources. Local research is promoted to improve outcomes for patients with this challenging cancer in Latin America.

CT-Based Screening for Pulmonary Metastases in Head and Neck Squamous Cell Cancers: Diagnostic Accuracy and Cost Comparison with PET-CECT

This study's objective was to compare detection rates of radiograph, computed tomography (CT), and positron emission tomography-contrast-enhanced computed tomography (PET-CECT) for pulmonary metastasis/synchronous primary lung tumors in head and neck squamous cell cancer (HNSCC) and its association with clinico-radio-pathological factors. Our retrospective study included 837 HNSCC patients from January 2012 to December 2017. Lung nodules were characterized on CT as benign, indeterminate, and metastatic. The true detection rate and statistical significance of associated risk factors were calculated. Risk factors for metastasis were determined using univariate and multivariate logistic regression models. Seventy-five (8.9%) patients had pulmonary metastasis and 3 (0.3%) had second lung primary. Detection rate of pulmonary metastasis by CT was higher (sensitivity-97.3%, specificity-97.2%) as compared to radiograph (sensitivity 49% and specificity 89%). Correlation was found between pulmonary and extra-pulmonary metastasis and N classification (P = 0.01, P = 0.02) and positive low jugular node (P = 0.001, P = 0.001). Using PET-CECT in place of CT costed an extra outlay of 7,033,805 INR (95,551.85 USD) while detecting distant metastasis in only 4 (0.47%) extra cases. Chest CT is a useful pulmonary metastases screening tool in advanced HNSCC patients with reasonable imaging cost as compared to PET-CT.

Value of dual-layer spectral detector computed tomography in the diagnosis of benign/malignant solid solitary pulmonary nodules and establishment of a prediction model

Objective

This study aimed to investigate the role of spectral detector computed tomography (SDCT) quantitative parameters and their derived quantitative parameters combined with lesion morphological information in the differential diagnosis of solid SPNs.

Methods

This retrospective study included basic clinical data and SDCT images of 132 patients with pathologically confirmed SPNs (102 and 30 patients in the malignant and benign groups, respectively). The morphological signs of SPNs were evaluated and the region of interest (ROI) was delineated from the lesion to extract and calculate the relevant SDCT quantitative parameters, and standardise the process. Differences in qualitative and quantitative parameters between the groups were statistically analysed. A receiver operating characteristic (ROC) curve was constructed to evaluate the efficacy of the corresponding parameters in the diagnosis of benign and malignant SPNs. Statistically significant clinical data, CT signs and SDCT quantitative parameters were analysed using multivariate logistic regression to determine the independent risk factors for predicting benign and malignant SPNs, and the best multi-parameter regression model was established. Inter-observer repeatability was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots.

Results

Malignant SPNs differed from benign SPNs in terms of size, lesion morphology, short spicule sign, and vascular enrichment sign (P< 0.05). The SDCT quantitative parameters and their derived quantitative parameters of malignant SPNs (SAR_40keV, SAR_70keV, Δ_40keV, Δ_70keV, CER_40keV, CER_70keV, NEF_40keV, NEF_70keV, λ, NIC, NZ_eff) were significantly higher than those of benign SPNs (P< 0.05). In the subgroup analysis, most parameters could distinguish between benign and adenocarcinoma groups (SAR_40keV, SAR_70keV, Δ_40keV, Δ_70keV, CER_40keV, CER_70keV, NEF_40keV, NEF_70keV, λ, NIC, and NZ_eff), and between benign and squamous cell carcinoma groups (SAR_40keV, SAR70_keV, Δ_40keV, Δ_70keV, NEF_40keV, NEF_70keV, λ, and NIC). However, there were no significant differences between the parameters in the adenocarcinoma and squamous cell carcinoma groups. ROC curve analysis indicated that NIC, NEF_70keV, and NEF_40keV had higher diagnostic efficacy for differentiating benign and malignant SPNs (area under the curve [AUC]:0.869, 0.854, and 0.853, respectively), and NIC was the highest. Multivariate logistic regression analysis showed that size (OR=1.138, 95% CI 1.022-1.267, P=0.019), Δ_70keV (OR=1.060, 95% CI 1.002-1.122, P=0.043), and NIC (OR=7.758, 95% CI 1.966-30.612, P=0.003) were independent risk factors for the prediction of benign and malignant SPNs. ROC curve analysis showed that the AUC of size, Δ_70keV, NIC, and a combination of the three for differential diagnosis of benign and malignant SPNs were 0.636, 0.846, 0.869, and 0.903, respectively. The AUC for the combined parameters was the largest, and the sensitivity, specificity, and accuracy were 88.2%, 83.3% and 86.4%, respectively. The SDCT quantitative parameters and their derived quantitative parameters in this study exhibited satisfactory inter-observer repeatability (ICC: 0.811-0.997).

Conclusion

SDCT quantitative parameters and their derivatives can be helpful in the differential diagnosis of benign and malignant solid SPNs. The quantitative parameter, NIC, is superior to the other relevant quantitative parameters and when NIC is combined with lesion size and Δ_70keV value for comprehensive diagnosis, the efficacy could be further improved.

French AFU Cancer Committee Guidelines - Update 2022-2024: Muscle-Invasive Bladder Cancer (MIBC)

OBJECTIVE

To update the CCAFU recommendations for the management of muscle invasive bladder carcinoma (MIBC).

METHODS

A systematic review (Medline) of the literature from 2020 to 2022 was performed taking account of the diagnosis, treatment options and surveillance of NMIBC and MIBC, while evaluating the references with their levels of evidence.

RESULTS

MIBC is diagnosed after the most complete tumour resection possible. MIBC grading is based on CTU along with chest CT. Multiparametric pelvic MRI could be an alternative. Cystectomy with extensive lymphadenectomy is the gold standard treatment for non-metastatic MIBC. It should be preceded by platinum-based neoadjuvant chemotherapy in patients in good general health with satisfactory renal function. Enterocystoplasty is proposed in men and women in the absence of contraindications and when the urethral resection is negative on extemporaneous examination. Otherwise, transileal cutaneous ureterostomy is the recommended method of urinary diversion. Inclusion of all patients in an ERAS (Enhanced Recovery After Surgery) protocol is recommended. For metastatic MIBC, first line treatment with platinum-based chemotherapy (GC or MVAC) is recommended, if general health (PS>1) and renal function (clearance>60mL/min) so allow (only 50% of the cases). Pembrolizumab immunotherapy has demonstrated an overall survival benefit in second-line treatment.

CONCLUSION

Updating the ccAFU recommendations should contribute to improving patient management, as well as the diagnosis and decision-making concerning MIBC treatment.

An Automatic Random Walker Algorithm for Segmentation of Ground Glass Opacity Pulmonary Nodules

Automatic and accurate segmentation of ground glass opacity (GGO) nodules still remains challenging due to inhomogeneous interiors, irregular shapes, and blurred boundaries from different patients. Despite successful applications in the image processing domains, the random walk has some limitations for segmentation of GGO pulmonary nodules. In this paper, an improved random walker method is proposed for the segmentation of GGO nodules. To calculate a new affinity matrix, intensity, spatial, and texture features are incorporated. It strengthens discriminative power between two adjacent nodes on the graph. To address the problem of robustness in seed acquisition, the geodesic distance is introduced and a novel local search strategy is presented to automatically acquire reliable seeds. For segmentation, a label constraint term is introduced to the energy function of original random walker, which alleviates the accumulation of errors caused by the initial seeds acquisition. Massive experiments conducted on Lung Images Dataset Consortium (LIDC) demonstrate that the proposed method achieves visually satisfactory results without user interactions. Both qualitative and quantitative evaluations also demonstrate that the proposed method obtains better performance compared with conventional random walker method and state-of-the-art segmentation methods in terms of the overlap score and F-measure.

Pediatric Pulmonary Nodules: Imaging Guidelines and Recommendations

Incidental pulmonary nodules are not infrequently identified on computed tomography imaging in the pediatric population and can be a challenge in suggesting appropriate follow-up recommendations. An evidence-based and practical imaging approach for diagnosis and appropriate directed management is essential for optimal patient care. This article provides an up-to-date review of the pediatric pulmonary nodule literature and suggests a practical algorithm to manage pulmonary nodules in the pediatric population.

VGG19 Network Assisted Joint Segmentation and Classification of Lung Nodules in CT Images

Pulmonary nodule is one of the lung diseases and its early diagnosis and treatment are essential to cure the patient. This paper introduces a deep learning framework to support the automated detection of lung nodules in computed tomography (CT) images. The proposed framework employs VGG-SegNet supported nodule mining and pre-trained DL-based classification to support automated lung nodule detection. The classification of lung CT images is implemented using the attained deep features, and then these features are serially concatenated with the handcrafted features, such as the Grey Level Co-Occurrence Matrix (GLCM), Local-Binary-Pattern (LBP) and Pyramid Histogram of Oriented Gradients (PHOG) to enhance the disease detection accuracy. The images used for experiments are collected from the LIDC-IDRI and Lung-PET-CT-Dx datasets. The experimental results attained show that the VGG19 architecture with concatenated deep and handcrafted features can achieve an accuracy of 97.83% with the SVM-RBF classifier.

A larval granuloma in the lung: An extremely rare phenomenon

The formation of pulmonary nodules is associated with benign or malignant pathologies. Based on the sizes, growth rates, and morphological features of nodules, surgical treatment or follow-up can be performed. Pulmonary nodules are frequently encountered in the practice of thoracic surgery. A 37-year-old male patient who had a 2.0x1.9 cm nodule in the right lung was followed. His medical history revealed no chronic disease. During follow-up, the sizes of the nodule increased and, therefore, it was removed by wedge resection. The pathological examination result was reported as a larval granuloma. In conclusion, larval granulomas in the lung are extremely rare phenomena and should be further examined.

Routine Preoperative Bone Scintigraphy Has Limited Impact on the Management of Patients with Invasive Bladder Cancer

BACKGROUND

According to current guidelines, bone scintigraphy is not routinely indicated in patients with invasive bladder cancer prior to radical cystectomy unless specific symptoms are present. These guidelines, however, are based on sparse data of low quality.

OBJECTIVE

To assess the clinical impact of routine staging bone scintigraphy on further patient management.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective, single-center study of 1287 consecutive patients, who were scheduled to undergo radical cystectomy due to invasive bladder cancer between January 2000 and December 2017, was conducted. All patients were prospectively followed up according to our institutional protocol.

INTERVENTION

Bone scintigraphy as staging imaging prior to radical cystectomy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary endpoint was the change in intended patient management. Secondary endpoints were the need for additional imaging, the diagnostic performance of baseline bone scintigraphy, and the association between clinical and radiological findings on bone metastases and survival. Logistic and Cox regression models were used for univariate and multivariate analyses.

RESULTS AND LIMITATIONS

Of 1287 patients scheduled for radical cystectomy, 1148 (89%) underwent bone scintigraphy as staging imaging. Overall, baseline bone scintigraphy led to a change in the intended management in 19/1148 (1.7%) patients. Additional imaging was performed in 44/1148 (4%) patients. Although positive bone scintigraphy findings were associated with the occurrence/development of bone metastases, the diagnostic performance of baseline bone scintigraphy was generally poor (positive predictive value, negative predictive value, sensitivity, and specificity were 56%, 89%, 27%, and 96%, respectively). Higher clinical tumor stage and the nonperformance of cystectomy had negative impacts on cancer-specific survival and overall survival, while positive bone scintigraphy was associated with worse cancer-specific survival. This study was limited by its retrospective nature and the lack of follow-up bone scintigraphy in all patients.

CONCLUSIONS

These results demonstrate the limited value of bone scintigraphy in the staging of invasive bladder cancer and do not support its routine use.

PATIENT SUMMARY

In this study, we looked at the clinical impact of bone scintigraphy on the diagnostics of patients with invasive bladder cancer. We found that routine staging bone scintigraphy had limited impact on further patient management. We conclude that bone scintigraphy should not be part of routine staging in patients with invasive bladder cancer.

Unboxing AI - Radiological Insights Into a Deep Neural Network for Lung Nodule Characterization

RATIONALE AND OBJECTIVES

To explain predictions of a deep residual convolutional network for characterization of lung nodule by analyzing heat maps.

MATERIALS AND METHODS

A 20-layer deep residual CNN was trained on 1245 Chest CTs from National Lung Screening Trial (NLST) trial to predict the malignancy risk of a nodule. We used occlusion to systematically block regions of a nodule and map drops in malignancy risk score to generate clinical attribution heatmaps on 103 nodules from Lung Image Database Consortium image collection and Image Database Resource Initiative (LIDC-IDRI) dataset, which were analyzed by a thoracic radiologist. The features were described as heat inside nodule -bright areas inside nodule, peripheral heat continuous/interrupted bright areas along nodule contours, heat in adjacent plane -brightness in scan planes juxtaposed with the nodule, satellite heat - a smaller bright spot in proximity to nodule in the same scan plane, heat map larger than nodule bright areas corresponding to the shape of the nodule seen outside the nodule margins and heat in calcification.

RESULTS

These six features were assigned binary values. This feature vector was fedinto a standard J48 decision tree with 10-fold cross-validation, which gave an 85 % weighted classification accuracy with a 77.8% True Positive (TP) rate, 8% False Positive (FP) rate for benign cases and 91.8% TP and 22.2% FP rates for malignant cases. Heat Inside nodule was more frequently observed in nodules classified as malignant whereas peripheral heat, heat in adjacent plane, and satellite heat were more commonly seen in nodules classified as benign.

CONCLUSION

We discuss the potential ability of a radiologist to visually parse the deep learning algorithm generated "heat map" to identify features aiding classification.

Added Value of Bone Suppression Image in the Detection of Subtle Lung Lesions on Chest Radiographs with Regard to Reader's Expertise

BACKGROUND

Chest radiographs (CXR) are the most commonly used imaging techniques by various clinicians and radiologists. However, detecting lung lesions on CXR depends largely on the reader's experience level, so there have been several trials to overcome this problem using post-processing of CXR. We investigated the added value of bone suppression image (BSI) in detecting various subtle lung lesions on CXR with regard to reader's expertise.

METHODS

We applied a software program to generate BSI in 1,600 patients in the emergency department. Of them, 80 patients with subtle lung lesions and 80 patients with negative finding on CXR were retrospectively selected based on the subtlety scores on CXR and CT findings. Ten readers independently rated their confidence in deciding the presence or absence of a lung lesion at each of 960 lung regions on the two separated imaging sessions: CXR alone vs. CXR with BSI.

RESULTS

The additional use of BSI for all readers significantly increased the mean area under the curve (AUC) in detecting subtle lung lesions (0.663 vs. 0.706; P < 0.001). The less experienced readers were, the more AUC differences increased: 0.067 (P < 0.001) for junior radiology residents; 0.064 (P < 0.001) for non-radiology clinicians; 0.044 (P < 0.001) for senior radiology residents; and 0.019 (P = 0.041) for chest radiologists. The additional use of BSI significantly increased the mean confidence regarding the presence or absence of lung lesions for 213 positive lung regions (2.083 vs. 2.357; P < 0.001) and for 747 negative regions (1.217 vs. 1.195; P = 0.008).

CONCLUSION

The use of BSI increases diagnostic performance and confidence, regardless of reader's expertise, reduces the impact of reader's expertise and can be helpful for less experienced clinicians and residents in the detection of subtle lung lesions.

Computer-Aided Detection of Pulmonary Nodules in Computed Tomography Using ClearReadCT

This study evaluates the accuracy of a computer-aided detection (CAD) application for pulmonary nodular lesions (PNL) in computed tomography (CT) scans, the ClearReadCT (Riverain Technologies). The study was retrospective for 106 biopsied PNLs from 100 patients. Seventy-five scans were Contrast-Enhanced (CECT) and 25 received no enhancer (NECT). Axial reconstructions in soft-tissue and lung kernel were applied at three different slice thicknesses, 0.75 mm (CECT/NECT n = 25/6), 1.5 mm (n = 18/9) and 3.0 mm (n = 43/18). We questioned the effect of (1) enhancer, (2) kernel and (3) slice thickness on the CAD performance. Our main findings are: (1) Vessel suppression is effective and specific in both NECT and CECT. (2) Contrast enhancement significantly increased the CAD sensitivity from 60% in NECT to 80% in CECT, P = 0.025 Fischer's exact test. (3) The CAD sensitivity was 84% in 3 mm slices compared to 68% in 0.75 mm slices, P > 0.2 Fischer's exact test. (4) Small lesions of low attenuation were detected with higher sensitivity. (5) Lung kernel reconstructions increased the false positive rate without affecting the sensitivity (P > 0.05 McNemar's test). In conclusion, ClearReadCT showed an optimized sensitivity of 84% and a positive predictive value of 67% in enhanced lung scans with thick, soft kernel reconstructions. NECT, thin slices and lung kernel reconstruction were associated with inferior performance.

Recommendations for follow-up of muscle-invasive bladder cancer patients: A consensus by the international bladder cancer network

RATIONALE

Several guidelines exist that address treatment of patients with nonmetastatic muscle-invasive bladder cancer (MIBC). However, most only briefly mention follow-up strategies for patients and hence the treating physician is often left to infer on what the preferred follow-up schema would be for an individual patient. Herein, we aim to synthesize recommendations for follow-up of patients with MIBC for easy reference.

METHODS

A multidisciplinary MIBC expert panel from the International Bladder Cancer Network was assembled to critically assess currently available major guidelines on surveillance of MIBC patients. Recommendations for follow-up were extracted and critically evaluated. Important considerations for guideline assessment included both aspects of oncological and functional follow-up-frequency of visits, the use of different imaging modalities, the role of cytology and molecular markers, and the duration of follow-up.

OUTCOME

An International Bladder Cancer Network expert consensus recommendation was constructed for the follow-up of patients with MIBC based on the currently available evidence-based data.

Improved Detection of Small Pulmonary Nodules Through Simultaneous MR/PET Imaging

Magnetic resonance (MR)/PET scanners provide an imaging platform that enables simultaneous acquisition of MR and PET data in perfect spatial and temporal registration. This feature allows improving image quality for the MR and PET images obtained during the course of an examination. In this work the authors demonstrate the use of prospective MR-based motion tracking information for removing motion blur in MR/PET images of small pulmonary nodules. The theoretical basis for the algorithms is presented alongside clinical examples of its use.

Improved Detection of Small Pulmonary Nodules Through Simultaneous MR/PET Imaging

Magnetic resonance (MR)/PET scanners provide an imaging platform that enables simultaneous acquisition of MR and PET data in perfect spatial and temporal registration. This feature allows improving image quality for the MR and PET images obtained during the course of an examination. In this work the authors demonstrate the use of prospective MR-based motion tracking information for removing motion blur in MR/PET images of small pulmonary nodules. The theoretical basis for the algorithms is presented alongside clinical examples of its use.

Role of Computer Aided Diagnosis (CAD) in the detection of pulmonary nodules on 64 row multi detector computed tomography

AIMS AND OBJECTIVES

To determine the overall performance of an existing CAD algorithm with thin-section computed tomography (CT) in the detection of pulmonary nodules and to evaluate detection sensitivity at a varying range of nodule density, size, and location.

MATERIALS AND METHODS

A cross-sectional prospective study was conducted on 20 patients with 322 suspected nodules who underwent diagnostic chest imaging using 64-row multi-detector CT. The examinations were evaluated on reconstructed images of 1.4 mm thickness and 0.7 mm interval. Detection of pulmonary nodules, initially by a radiologist of 2 years experience (RAD) and later by CAD lung nodule software was assessed. Then, CAD nodule candidates were accepted or rejected accordingly. Detected nodules were classified based on their size, density, and location. The performance of the RAD and CAD system was compared with the gold standard that is true nodules confirmed by consensus of senior RAD and CAD together. The overall sensitivity and false-positive (FP) rate of CAD software was calculated.

OBSERVATIONS AND RESULTS

Of the 322 suspected nodules, 221 were classified as true nodules on the consensus of senior RAD and CAD together. Of the true nodules, the RAD detected 206 (93.2%) and 202 (91.4%) by the CAD. CAD and RAD together picked up more number of nodules than either CAD or RAD alone. Overall sensitivity for nodule detection with the CAD program was 91.4%, and FP detection per patient was 5.5%. The CAD showed comparatively higher sensitivity for nodules of size 4-10 mm (93.4%) and nodules in hilar (100%) and central (96.5%) location when compared to RAD's performance.

CONCLUSION

CAD performance was high in detecting pulmonary nodules including the small size and low-density nodules. CAD even with relatively high FP rate, assists and improves RAD's performance as a second reader, especially for nodules located in the central and hilar region and for small nodules by saving RADs time.

Pulmonary nodule size evaluation with chest tomosynthesis and CT: a phantom study

OBJECTIVE

We compared digital tomosynthesis (TOMO) and chest CT in terms of assessing the sizes of nodules located in zones where evaluation by simple radiography is limited.

METHODS

A total of 48 images comprising phantom nodules of four sizes in six different locations were used. Nodule size measurement errors for measurements using TOMO and CT images compared with the actual size from each observer were calculated. The inter- and intraobserver repeatability of the measured values and the agreement between the two techniques were assessed using the method described by Bland and Altman.

RESULTS

The mean measurement errors for all of the nodules and four observers were -0.84 mm [standard deviation (SD), 0.60 mm] on TOMO and -0.18 mm (SD, 0.71 mm) on CT images. The mean measurement errors for the different observers ranged from -1.11 to -0.55 mm for TOMO and from -0.39 to 0.08 mm for CT. Assessing the agreement between nodule size measurements using TOMO and CT resulted in mean measurement errors of -0.65 mm, with a 95% limit of agreement of -2.53 to 1.22 mm for comparison of TOMO with CT.

CONCLUSION

Our results suggest that nodule sizes obtained using TOMO and chest CT are comparable, even for nodules located in areas where the size measurement is limited on simple radiography.

ADVANCES IN KNOWLEDGE

TOMO and CT can be used interchangeably, even for nodules located in a blind area on simple radiography.

Evaluation and management of pulmonary nodules: state-of-the-art and future perspectives

INTRODUCTION

The imaging evaluation of pulmonary nodules, often incidentally detected on imaging examinations performed for other clinical reasons, is a frequently encountered clinical circumstance. With advances in imaging modalities, both the detection and characterization of pulmonary nodules continue to evolve and improve.

AREAS COVERED

This article will review the imaging modalities used to detect and diagnose benign and malignant pulmonary nodules, with a focus on computed tomography (CT), which continues to be the mainstay for evaluation. The authors discuss recent advances in the lung nodule management, and an algorithm for the management of indeterminate pulmonary nodules.

EXPERT OPINION

There are set of criteria that define a benign nodule, the most important of which are the lack of temporal change for 2 years or more, and certain benign imaging criteria, including specific patterns of calcification or the presence of fat. Although some indeterminate pulmonary nodules are immediately actionable, generally those approaching 1 cm or larger in diameter, at which size the diagnostic accuracy of tools such as positron emission tomography (PET)/CT, single photon emission CT (SPECT) and biopsy techniques are sufficient to warrant their use. The majority of indeterminate pulmonary nodules are under 1 cm, for which serial CT examinations through at least 2 years for solid nodules and 3 years for ground-glass nodules, are used to demonstrate either benign biologic behavior or otherwise. The management of incidental pulmonary nodules involves a multidisciplinary approach in which radiology plays a pivotal role. Newer imaging and postprocessing techniques have made this a more accurate technique eliminating ambiguity and unnecessary follow-up.

Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making

The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and “weak” local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

Differentiation between malignant and benign solitary pulmonary nodules: use of volume first-pass perfusion and combined with routine computed tomography

PURPOSE

To evaluate the capability of first-pass volume perfusion computed tomography (PCT) for differentiation of solitary pulmonary nodules (SPNs) and to compare that of combination of PCT and routine CT with CT alone for the differentiation.

MATERIALS AND METHODS

Our institutional review board approved this study and informed consent was obtained. With nine excluded, 65 consecutive patients having a SPN with histopathologic proof or follow-up underwent a 30s PCT using the deconvolution model were evaluated. Kruskal-Wallis tests and receiver operating characteristics (ROC) analysis were underwent. Four radiologists assessed nodules independently and retrospectively. Diagnostic capability was compared for CT alone and PCT plus CT. ROC analysis, McNemar test, and weighted kappa statistics were performed.

RESULTS

Significant differences were found in parameters between malignant and benign nodules (p<0.0001 for blood flow, blood volume, and permeability surface area product), SPNs were more likely to be malignant by using threshold values of more than 55 ml/100 g/min, 2.5 ml/100 g, and 10 ml/100 g/min, respectively. PCT plus CT was significantly better in overall sensitivity (93%, p=0.004) and accuracy (94%, p=0.003) compared to CT alone, not specificity (96%). Area under the curve for ROC analyses of PCT plus CT was significantly larger than that of CT alone (p=0.018). Mean weighted kappa for PCT plus CT was 0.715, that for CT alone was 0.447.

CONCLUSION

Volume first-pass PCT can distinguish SPNs. Using PCT plus routine CT may be more sensitive and accurate for differentiating malignant from benign nodules than CT alone and allows more confidence and constancy.

¹⁸F-fluoro-deoxy-glucose focal uptake in very small pulmonary nodules: fact or artifact? Case reports

Background

¹⁸F-fluoro-deoxy-glucose (¹⁸ F-FDG) positron emission tomography integrated/combined with computed tomography (PET-CT) provides the best diagnostic results in the metabolic characterization of undetermined solid pulmonary nodules. The diagnostic performance of ¹⁸ F-FDG is similar for nodules measuring at least 1 cm and for larger masses, but few data exist for nodules smaller than 1 cm.

Case presentation

We report five cases of oncologic patients showing focal lung ¹⁸ F-FDG uptake on PET-CT in nodules smaller than 1 cm. We also discuss the most common causes of ¹⁸ F-FDG false-positive and false-negative results in the pulmonary parenchyma.

In patient 1, contrast-enhanced CT performed 10 days before PET-CT did not show any abnormality in the site of uptake; in patient 2, high-resolution CT performed 1 month after PET showed a bronchiole filled with dense material interpreted as a mucoid impaction; in patient 3, contrast-enhanced CT performed 15 days before PET-CT did not identify any nodules; in patients 4 and 5, contrast-enhanced CT revealed a nodule smaller than 1 cm which could not be characterized. The ¹⁸ F-FDG uptake at follow-up confirmed the malignant nature of pulmonary nodules smaller than 1 cm which were undetectable, misinterpreted, not recognized or undetermined at contrast-enhanced CT.

Conclusion

In all five oncologic patients, ¹⁸ F-FDG was able to metabolically characterize as malignant those nodules smaller than 1 cm, underlining that: ¹⁸ F-FDG uptake is not only a function of tumor size but it is strongly related to the tumor biology; functional alterations may precede morphologic abnormalities. In the oncologic population, especially in higher-risk patients, PET can be performed even when the nodules are smaller than 1 cm, because it might give an earlier characterization and, sometimes, could guide in the identification of alterations missed on CT.

Pulmonary nodule registration: rigid or nonrigid?

PURPOSE

The primary aim of this study is to investigate the performance difference of rigid and nonrigid registration schemes in matching corresponding pulmonary nodules depicted on sequential chest computed tomography (CT) examinations.

METHODS

A gradient descent based rigid registration algorithm with scaling was developed and it handled the involved geometric transformations (i.e., translation, rescaling, shearing, and rotation) separately instead of optimizing them in a single pass. Given two lung CT examinations, the scaling and translation parameters were simply estimated from the lung volume dimensions (e.g., size and mass center), while the rotation parameters were optimized progressively using gradient descent. To investigate the performance difference of rigid and nonrigid schemes in pulmonary nodule registration, the well-known nonrigid Demons algorithm was implemented and tested along with the developed schemes against 60 diverse low-dose clinical lung CT examinations with average 2-yr follow-up scans. A verified cancer and its correspondence in the follow-up scan as well as their spatial locations (mass center) were identified in each examination. In addition to the computational efficiency, the accuracy of these registration procedures was assessed by computing the Euclidean distances between the corresponding nodules after the registration. To demonstrate the advantage of the developed algorithm, the authors also implemented a fast iterative closest point (ICP) based rigid algorithm and compared their performance.

RESULTS

Our experiments on the collected chest CT examinations showed that the nodule registration errors in 3D Euclidean distance for the developed rigid affine approach, the traditional ICP algorithm, and the refining nonrigid Demons algorithm were 9.6, 9.8, and 10.0 mm, respectively, and the corresponding computational costs in time were 5, 300, and 55 s, respectively.

CONCLUSIONS

A rigid solution may be preferred in practice for the pulmonary nodule registration in longitudinal studies because of its relatively high efficiency and sufficient accuracy for the clinical need.

Diffusion-weighted imaging of the chest

Diffusion-weighted imaging (DWI) is feasible in the chest with currently available MR imaging scanners, although it is technically demanding. Although there is scarce clinical experience, the use of DWI has shown promising results in the characterization of pulmonary nodules, in lung cancer characterization and staging, and in the evaluation of mediastinal and pleural pathology. Ongoing research opens a door to noninvasive evaluation of heart fibers by means of diffusion-tensor imaging. Another area under investigation is the use of DWI of hyperpolarized gases as an early biomarker of pulmonary disease.

CT characteristics of lung nodules present at diagnosis of extrapulmonary malignancy in children

OBJECTIVE

The purpose of this study was to evaluate the CT characteristics of lung nodules present at diagnosis of extrapulmonary malignancies in children.

MATERIALS AND METHODS

We performed a retrospective analysis of CT images of children seen in our oncology service over a 6-year period. We included all children diagnosed with a non-CNS solid extrapulmonary malignancy or lymphoma who had also undergone chest CT at presentation. Images were reviewed for the presence of lung nodules; if present, the following nodular characteristics were recorded: sidedness, number, distribution, CT attenuation, shape, margins, calcification, and size. When available, pathology results were correlated with the nodules found on CT.

RESULTS

One hundred eleven infants and children (age range, 14 days-17 years 10 months; median age, 11 years 8 months) had lung nodules on CT. The nodules showed a variety of patterns, but the most common findings were bilateral lung nodules (71 of 111 patients), between two and 10 in number (60 patients), peripheral distribution (98 patients), < or = 5 mm (48 patients), oval shape (45 patients), solid attenuation (74 patients), smoothly marginated (91 patients), and noncalcified (107 patients). Twenty-seven patients underwent biopsy. Seventeen biopsies showed benign lesions and nine, malignant lesions; the results for the remaining biopsy were inconclusive. In the subgroup of lung nodules that underwent biopsy, none of the CT characteristics was able to differentiate benignity from malignancy.

CONCLUSION

Lung nodules in children with extrapulmonary malignancies showed a variety of patterns on CT. In the subgroup of lung nodules that underwent biopsy, none of the nodule features studied on CT reliably differentiated benignity from malignancy.