Artificial neural networks analysis predicts long-term fistula function in hemodialysis patients following percutaneous transluminal angioplasty.

Kidney failure is particularly common in the United States, where it affects over 700,000 individuals. It is typically treated through repeated sessions of hemodialysis to filter and clean the blood. Hemodialysis requires vascular access, in about 70% of cases through an arteriovenous fistula (AVF) surgically created by connecting an artery and vein. AVF take 6 weeks or more to mature. Mature fistulae often require intervention, most often percutaneous transluminal angioplasty (PTA), also known as fistulaplasty, to maintain the patency of the fistula. PTA is also the first-line intervention to restore blood flow and prolong the use of an AVF, and many patients undergo the procedure multiple times. Although PTA is important for AVF maturation and maintenance, research into predictive models of AVF function following PTA has been limited. Therefore, in this paper we hypothesize that based on patient-specific information collected during PTA, a predictive model can be created to help improve treatment planning. We test a set of rich, multimodal data from 28 patients that includes medical history, AVF blood flow, and interventional angiographic imaging (specifically excluding any post-PTA measurements) and build deep hybrid neural networks. A hybrid model combining a 3D convolutional neural network with a multi-layer perceptron to classify AVF was established. We found using this model that we were able to identify the association between different factors and evaluate whether the PTA procedure can maintain primary patency for more than 3 months. The testing accuracy achieved was 0.75 with a weighted F1-score of 0.75, and AUROC of 0.75. These results indicate that evaluating multimodal clinical data using artificial neural networks can predict the outcome of PTA. These initial findings suggest that the hybrid model combining clinical data, imaging and hemodynamic analysis can be useful to treatment planning for hemodialysis. Further study based on a large cohort is needed to refine the accuracy and model efficiency.

A multitask approach for automated detection and segmentation of thyroid nodules in ultrasound images.

An increase in the incidence and diagnosis of thyroid nodules and thyroid cancer underscores the need for a better approach to nodule detection and risk stratification in ultrasound (US) images that can reduce healthcare costs, patient discomfort, and unnecessary invasive procedures. However, variability in ultrasound technique and interpretation makes the diagnostic process partially subjective. Therefore, an automated approach that detects and segments nodules could improve performance on downstream tasks, such as risk stratification. Ultrasound studies were acquired from 280 patients at UCLA Health, totaling 9888 images, and annotated by collaborating radiologists. Current deep learning architectures for segmentation are typically semi-automated because they are evaluated solely on images known to have nodules and do not assess ability to identify suspicious images. However, the proposed multitask approach both detects suspicious images and segments potential nodules; this allows for a clinically translatable model that aptly parallels the workflow for thyroid nodule assessment. The multitask approach is centered on an anomaly detection (AD) module that can be integrated with any UNet architecture variant to improve image-level nodule detection. Of the evaluated multitask models, a UNet with a ImageNet pretrained encoder and AD achieved the highest F1 score of 0.839 and image-wide Dice similarity coefficient of 0.808 on the hold-out test set. Furthermore, models were evaluated on two external validations datasets to demonstrate generalizability and robustness to data variability. Ultimately, the proposed architecture is an automated multitask method that expands on previous methods by successfully both detecting and segmenting nodules in ultrasound.

A pictorial review of genitourinary infections and inflammations.

Various infectious and inflammatory diseases affect the genitourinary system. This paper provides a review of multiple common and uncommon infectious and inflammatory conditions affecting the genitourinary system and some associated complications. These include acute infectious cystitis, emphysematous cystitis, acute pyelonephritis, emphysematous pyelonephritis, renal and perinephric abscesses, pyonephrosis, xanthogranulomatous pyelonephritis, epididymo-orchitis, vasitis, prostatitis, pelvic inflammatory disease, renal hydatid infection, renal tuberculosis, actinomycosis, Erdheim-Chester Disease, IgG4-Related Kidney Disease, urethritis and urethral strictures, ureteritis cystica, and genitourinary fistulas. Radiologists should be aware of these diseases' complications and management. Uncommon conditions must be considered when evaluating the genitourinary system.

RECIST 1.1 Target Lesion Categorical Response in Metastatic Renal Cell Carcinoma: A Comparison of Conventional versus Volumetric Assessment.

Purpose To investigate Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) approximations of target lesion tumor burden by comparing categorical treatment response according to conventional RECIST versus actual tumor volume measurements of RECIST target lesions. Materials and Methods This is a retrospective cohort study of individuals with metastatic renal cell carcinoma enrolled in a clinical trial (from 2003 to 2017) and includes individuals who underwent baseline and at least one follow-up chest, abdominal, and pelvic CT study and with at least one target lesion. Target lesion volume was assessed by (a) Vmodel, a spherical model of conventional RECIST 1.1, which was extrapolated from RECIST diameter, and (b) Vactual, manually contoured volume. Volumetric responses were determined by the sum of target lesion volumes (Vmodel-sum TL and Vactual-sum TL, respectively). Categorical volumetric thresholds were extrapolated from RECIST. McNemar tests were used to compare categorical volume responses. Results Target lesions were assessed at baseline (638 participants), week 9 (593 participants), and week 17 (508 participants). Vmodel-sum TL classified more participants as having progressive disease (PD), compared with Vactual-sum TL at week 9 (52 vs 31 participants) and week 17 (57 vs 39 participants), with significant overall response discordance (P < .001). At week 9, 25 (48%) of 52 participants labeled with PD by Vmodel-sum TL were classified as having stable disease by Vactual-sum TL. Conclusion A model of RECIST 1.1 based on a single diameter measurement more frequently classified PD compared with response assessment by actual measured tumor volume. Keywords: Urinary, Kidney, Metastases, Oncology, Tumor Response, Volume Analysis, Outcomes Analysis ClinicalTrials.gov registration no. NCT01865747 © RSNA, 2023 Supplemental material is available for this article.

Contrast-enhanced ultrasound for abdominal image-guided procedures.

INTRODUCTION: Since FDA approval for contrast-enhanced ultrasound (CEUS), clinical applications have increased to include diagnostic imaging of hepatic, renal, and other abdominal lesions. The modality has also demonstrated utility in certain image-guided procedures. Intravascular ultrasound contrast agents use microbubbles to improve visibility of solid tumors. Lesions not well seen on grayscale or Doppler ultrasound may become amenable to CEUS-guided biopsy or ablation. MATERIALS AND METHODS: This pictorial essay provides eleven examples to illustrate the current use of CEUS in a variety of abdominal image-guided procedures. Hepatic, renal, peritoneal, and soft tissue cases are presented. CONCLUSION: CEUS can improve visualization and targeting in abdominal image-guided procedures, without nephrotoxicity or radiation exposure.

A Multitask Approach for Automated Detection and Segmentation of Thyroid Nodules in Ultrasound Images.

An increase in the incidence and diagnosis of thyroid nodules and thyroid cancer underscores the need for a better approach to nodule detection and risk stratification in ultrasound (US) images that can reduce healthcare costs, patient discomfort, and unnecessary invasive procedures. However, variability in ultrasound technique and interpretation makes the diagnostic process partially subjective. Therefore, an automated approach that detects and segments nodules could improve performance on downstream tasks, such as risk stratification.Current deep learning architectures for segmentation are typically semi-automated because they are evaluated solely on images known to have nodules and do not assess ability to identify suspicious images. However, the proposed multitask approach both detects suspicious images and segments potential nodules; this allows for a clinically translatable model that aptly parallels the workflow for thyroid nodule assessment. The multitask approach is centered on an anomaly detection (AD) module that can be integrated with any U-Net architecture variant to improve image-level nodule detection. Ultrasound studies were acquired from 280 patients at UCLA Health, totaling 9,888 images, and annotated by collaborating radiologists. Of the evaluated models, a multi-scale UNet (MSUNet) with AD achieved the highest F1 score of 0.829 and image-wide Dice similarity coefficient of 0.782 on our hold-out test set. Furthermore, models were evaluated on two external validations datasets to demonstrate generalizability and robustness to data variability. Ultimately, the proposed architecture is an automated multitask method that expands on previous methods by successfully both detecting and segmenting nodules in ultrasound.

Patient-level thyroid cancer classification using attention multiple instance learning on fused multi-scale ultrasound image features.

For patients with thyroid nodules, the ability to detect and diagnose a malignant nodule is the key to creating an appropriate treatment plan. However, assessments of ultrasound images do not accurately represent malignancy, and often require a biopsy to confirm the diagnosis. Deep learning techniques can classify thyroid nodules from ultrasound images, but current methods depend on manually annotated nodule segmentations. Furthermore, the heterogeneity in the level of magnification across ultrasound images presents a significant obstacle to existing methods. We developed a multi-scale, attention-based multiple-instance learning model which fuses both global and local features of different ultrasound frames to achieve patient-level malignancy classification. Our model demonstrates improved performance with an AUROC of 0.785 (p<0.05) and AUPRC of 0.539, significantly surpassing the baseline model trained on clinical features with an AUROC of 0.667 and AUPRC of 0.444. Improved classification performance better triages the need for biopsy.

Pretreatment visceral metastases in castration resistant metastatic prostate cancer: role in prediction versus actual site of disease progression.

BACKGROUND: To evaluate the anatomic site(s) of initial disease progression in patients with castration resistant metastatic prostate cancer (mCRPC) in the presence or absence of pre-treatment visceral metastases while on systemic therapy. METHODS: This is a retrospective cohort study of mCRPC patients who have baseline and at least one follow up bone scan and CT chest, abdomen and pelvis (CAP). Disease progression was determined by RECIST and/or ≥ 30% increase in automated bone scan lesion area score. Kaplan-Meier plot was used to estimate the median progression free survival and log-rank tests were used to compare anatomic sites. RESULTS: Of 203 patients, 61 (30%) had pre-treatment visceral metastases. Patients with baseline visceral disease were 1.5 times more likely to develop disease progression (HR = 1.53; 95% CI, 1.03-2.26). Disease progression was a result of worsening bone scan disease (42% (16/38)) versus visceral (32% (12/38)) or lymph node disease (3% (1/38)) by CT or a combination thereof (23% (9/38)). Median time to progression (TTP) did not differ by anatomic location of initial progression (p = 0.86). Development of new lesions occurred in 50% of those visceral patients with soft tissue only progression and was associated with a significantly longer TTP (3.1 months (2.8-4.3 months) than those with worsening of pre-existing lesions (1.8 months (1.6-2.7 months); p = 0.04. CONCLUSIONS: Patients with pre-treatment visceral metastases in mCRPC are more likely to experience disease progression of bone disease with the initial anatomic site of progression similar to those without baseline visceral involvement.

The Effect Modification of Ultrasound Risk Classification on Molecular Testing in Predicting the Risk of Malignancy in Cytologically Indeterminate Thyroid Nodules.

Background: Thyroid nodules with indeterminate cytology are increasingly subjected to molecular testing. We evaluated the diagnostic performances of Afirma Genomic Sequencing Classifier (GSC) and ThyroSeq v3 in thyroid nodules with high versus low/intermediate suspicion ultrasound classification. Methods: In this prospective cohort study, we analyzed all Bethesda III and IV thyroid nodules that underwent fine-needle aspiration biopsies in the University of California Los Angeles Health System from July 2017 to April 2020. All patients underwent molecular testing with Afirma GSC or ThyroSeq v3 as part of an institutional randomized trial (NCT02681328). Nodules were categorized according to the American Thyroid Association (ATA) ultrasound risk classification. The benign call rate and the positive predictive value of molecular testing were compared between ATA high suspicion versus all other categories. Results: A total of 343 patients with 375 indeterminate thyroid nodules were included. The malignancy rate in ATA high suspicion nodules was not significantly increased by a suspicious Afirma GSC result (77.8% for all ATA high suspicion nodules vs. 87.5% for nodules with ATA high suspicion and suspicious Afirma GSC results, positive likelihood ratio [LR] = 2.0, 95% confidence interval [CI 0.5-8.0], p = 1.0) or by a positive ThyroSeq v3 result (80.0% vs. 80.0%, positive LR = 1.0 [CI 1.0-1.0], p = 1.0). The rate of malignancy in ATA low/intermediate suspicion nodules increased from 21.0% to 56.3% with a suspicious Afirma GSC result (positive LR = 4.8 [CI 3.4-6.9], p < 0.0001) and decreased to 3.8% with a benign Afirma GSC result (negative LR = 0.1 [CI 0.07-0.3], p < 0.0001). Similarly, the rate of malignancy in ATA low/intermediate suspicion nodules increased from 24.3% to 66.7% with a positive ThyroSeq v3 result (positive LR = 6.2 [CI 4.0-9.7], p < 0.0001) and decreased to 2.1% with a negative ThyroSeq v3 result (negative LR = 0.07 [CI 0.02-0.3], p < 0.0001). Conclusions: Afirma GSC and ThyroSeq v3 performed well in ruling out malignancy in sonographically low/intermediate suspicion thyroid nodules but has limited diagnostic value in sonographically high suspicion nodules. Molecular testing can prognosticate more aggressive thyroid cancers, which can inform treatment decisions.

Gynecologic tumor board: a radiologist's guide to vulvar and vaginal malignancies.

Primary vulvar and vaginal cancers are rare female genital tract malignancies which are staged using the 2009 International Federation of Gynecology and Obstetrics (FIGO) staging. These cancers account for approximately 2,700 deaths annually in the USA. The most common histologic subtype of both vulvar and vaginal cancers is squamous cell carcinoma, with an increasing role of the human papillomavirus (HPV) in a significant number of these tumors. Lymph node involvement is the hallmark of FIGO stage 3 vulvar cancer while pelvic sidewall involvement is the hallmark of FIGO stage 3 vaginal cancer. Imaging techniques include computed tomography (CT), positron emission tomography (PET)-CT, magnetic resonance imaging (MRI), and PET-MRI. MRI is the imaging modality of choice for preoperative clinical staging of nodal and metastatic involvement while PET-CT is helpful with assessing response to neoadjuvant treatment and for guiding patient management. Determining the pretreatment extent of disease has become more important due to modern tailored operative approaches and use of neoadjuvant chemoradiation therapy to reduce surgical morbidity. Moreover, imaging is used to determine the full extent of disease for radiation planning and for evaluating treatment response. Understanding the relevant anatomy of the vulva and vaginal regions and the associated lymphatic pathways is helpful to recognize the potential routes of spread and to correctly identify the appropriate FIGO stage. The purpose of this article is to review the clinical features, pathology, and current treatment strategies for vulvar and vaginal malignancies and to identify multimodality diagnostic imaging features of these gynecologic cancers, in conjunction with its respective 2009 FIGO staging system guidelines.

Quality improvement time-saving intervention to increase use of a clinical decision support tool to reduce low-value diagnostic imaging in a safety net health system.

IMPORTANCE: Electronic health record (EHR) clinical decision support (CDS) tools can provide evidence-based feedback at the point of care to reduce low-value imaging. Success of these tools has been limited partly due to lack of engagement by busy clinicians. OBJECTIVE: Measure the impact of a time-saving quality improvement intervention to increase engagement with a CDS tool for low back pain imaging ordering. DESIGN, SETTING AND PARTICIPANTS: We conducted a quasi-experimental difference-in-differences analysis at (BLINDED), examining back pain imaging orders from 29 May 2015 to 07 January 2016. The intervention site was (BLINDED) Emergency Medicine/Urgent Care Center (n=5736) and control sites included all other (BLINDED) hospitals and clinics (n=1621). In May 2015, the Department of Health Services installed a CDS tool that triggered a survey when clinicians ordered an imaging test, generating an 'appropriateness score' based on the American College of Radiology guidelines. Clinicians often bypassed the tool, resulting in 'unscored' tests. INTERVENTION: To increase clinician engagement with the tool and decrease the rate of unscored imaging tests, a new policy was implemented at the intervention site on 15 August 2015. If clinicians completed the CDS survey and scored an appropriateness score >3, they could forego a previously mandatory telephone call for pre-imaging utilisation review with the radiology department. MAIN OUTCOMES AND MEASURES: We used EHR data to measure pre-post-intervention differences in: (1) percentage of unscored tests and (2) percentage of tests with high appropriateness scores (>7). RESULTS: Percentage of unscored tests decreased from 69.4% to 10.4% at the intervention site and from 50.6% to 34.8% at the control sites (between-group difference: -23.3%, p<0.001). Percentage of high scoring tests increased from 26.5% to 75.0% at the intervention site and from 17.2% to 22.7% at the control sites (between-group difference: 19%, p<0.001). CONCLUSION: Workflow time-saving interventions may increase physician engagement with CDS tools and have potential to improve practice patterns.

Diagnostic Value of Molecular Testing in Sonographically Suspicious Thyroid Nodules.

OBJECTIVE: Molecular testing can refine the diagnosis for the 20% of thyroid fine-needle aspiration biopsies that have indeterminate cytology. We assessed the diagnostic accuracy of molecular testing based on ultrasound risk classification. METHODS: This retrospective cohort study analyzed all thyroid nodules with indeterminate cytology at an academic US medical center (2012-2016). All indeterminate nodules underwent reflexive molecular testing with the Afirma Gene Expression Classifier (GEC). Radiologists performed blinded reviews to categorize each nodule according to the American Thyroid Association (ATA) ultrasound classification and the American College of Radiology Thyroid Imaging, Reporting and Data System. GEC results and diagnostic performance were compared across ultrasound risk categories. RESULTS: Of 297 nodules, histopathology confirmed malignancy in 65 (22%). Nodules by ATA classification were 8% high suspicion, 44% intermediate, and 48% low/very low suspicion. A suspicious GEC result was more likely in ATA high-suspicion nodules (81%) than in nodules of all other ATA categories (57%; P = .04). The positive predictive value (PPV) of GEC remained consistent across ultrasound categories (ATA high suspicion, 64% vs all other ATA categories, 48%; P = .39). The ATA high-suspicion category had higher specificity than a suspicious GEC result (93% vs 51%; P < .01). A suspicious GEC result did not increase specificity for the ATA high-suspicion category. CONCLUSION: The PPV of molecular testing remained consistent across ultrasound risk categories. However, a suspicious GEC result was very likely in ATA high-suspicion nodules and did not improve specificity in this sonographic category.

BRCA and Beyond: Comprehensive Image-rich Review of Hereditary Breast and Gynecologic Cancer Syndromes.

In addition to the well-characterized BRCA1 and BRCA2 hereditary breast and ovarian cancer syndromes, many other syndromes that are associated with genetic mutations predispose individuals to an increased risk of breast and gynecologic malignancies. Many mutated genes encode for tumor-suppressor products and are inherited in an autosomal dominant manner. Mutations markedly increase an individual's lifetime risk of cancers in different organ systems, depending on the associated syndrome. These syndromes include Lynch syndrome, the most common hereditary cause of endometrial cancer, and Peutz-Jeghers syndrome, which increases the risks of breast cancer, ovarian cancer, and cervical adenoma malignum. Li-Fraumeni syndrome and Cowden syndrome increase the risk of breast cancer, and Gorlin syndrome increases the risk of ovarian fibromas. With advances in genetic testing, clinicians' knowledge and awareness of the numerous additional genes associated with breast and ovarian cancers, such as ATM, CHEK2, and PALB2, are rapidly expanding. Radiologists have essential roles in patient management, which include developing optimal screening protocols for these patients and closely monitoring them for the development or recurrence of disease-specific malignancies. Radiologists' roles continue to increase and evolve as more mutations are identified and high-risk imaging screening recommendations expand to identify these patients. Understanding the epidemiologic, genetic, and pathophysiologic features and the cancers associated with these syndromes enables radiologists to appropriately contribute to patient management, ensure accurate and timely diagnosis, and make syndrome-specific imaging recommendations. ©RSNA, 2020.

Ligaments and Lymphatic Pathways in Gastric Adenocarcinoma.

Gastric cancer is a leading cause of cancer-related deaths worldwide and is associated with an overall 5-year survival rate of less than 20%. The most common histologic subtype of gastric cancer is adenocarcinoma. Imaging techniques for evaluating gastric adenocarcinoma include endoscopic US, fluoroscopic upper gastrointestinal imaging, CT, PET/CT, and MRI. Hydrodynamic multiphasic contrast material-enhanced CT is the imaging modality of choice for preoperative clinical staging of regional, nodal, and metastatic involvement. Radiologic manifestations of gastric adenocarcinoma at double-contrast upper gastrointestinal imaging and CT include polyps, ulceration, indistensibility, wall thickening, and abnormal enhancement. There are multiple pathways of disease spread. These pathways include lymphatic dissemination; subperitoneal dissemination along the perigastric ligaments, mesentery, or omentum; direct invasion into adjacent organs; transperitoneal seeding; and hematogenous dissemination. The spread of disease is affected by the location of the tumor in the stomach, and the ligamentous and lymphatic anatomy. Key imaging features that affect clinical staging with use of the TNM classification system for gastric adenocarcinoma, as described in the eighth edition of the AJCC Cancer Staging Manual, are briefly discussed. Accurate radiologic assessment of gastric adenocarcinoma requires identification of perigastric ligament infiltration, regional and metastatic nodal disease, and direct and metastatic organ involvement, all of which directly affect tumor staging, treatment, and prognosis. ©RSNA, 2019.

Neoplasms of the Appendix: Pictorial Review with Clinical and Pathologic Correlation.

Appendiceal neoplasms are uncommon tumors of the gastrointestinal tract that may manifest with symptoms of appendicitis, right lower quadrant pain, or palpable mass, leading to imaging or surgical intervention. The majority of appendiceal masses consist of primary epithelial neoplasms and neuroendocrine tumors (NETs). Epithelial neoplasms-mucinous and nonmucinous types-are more often detected at imaging than NETs due to their larger size and propensity for peritoneal spread and metastatic disease. Epithelial mucinous neoplasms are defined by the presence of mucin, detected at radiologic and pathologic examination. A mucocele or pseudomyxoma peritonei from epithelial mucinous tumors are the two most common cross-sectional imaging findings of appendiceal mucinous neoplasms. Nonmucinous epithelial tumors are less common and manifest as masses similar to colonic-type malignancies. NETs are often discovered incidentally at appendectomy due to their small size and nonaggressive behavior. Imaging findings of primary appendiceal tumors may overlap with those of acute appendicitis. Additionally, an appendiceal mass may cause acute appendicitis, obscuring the underlying mass. Other neoplasms including lymphoma, sarcoma, mesenchymal and nerve sheath tumors, or secondary malignant involvement of the appendix are rare. Treatment depends on the histologic subtype and extent of disease. Detailed description of organ, nodal, and peritoneal involvement informs surgical management with the goal of complete cytoreduction. Novel treatments such as hyperthermic intraperitoneal chemotherapy have increased survival for patients with mucinous tumors. ©RSNA, 2017.

MRI suggests increased tonicity of the levator ani in women with interstitial cystitis/bladder pain syndrome.

INTRODUCTION AND HYPOTHESIS: In interstitial cystitis/bladder pain syndrome (IC/BPS), pelvic floor dysfunction may contribute significantly to pelvic pain. To determine if pelvic floor hypertonicity manifests alterations on magnetic resonance imaging (MRI) in patients with IC/BPS, we retrospectively compared pelvic measurements between patients and controls. METHODS: Fifteen women with IC/BPS and 15 age-matched controls underwent pelvic MRI. Two blinded radiologists measured the pelvic musculature, including the H- and M lines, vaginal length, urethral length and cross-sectional area, levator width and length, and posterior puborectalis angle. MRI measures and clinical factors, such as age, parity, and duration of symptoms, were compared using a paired, two-tailed t test. RESULTS: There were no significant differences in age, parity, or symptom duration between groups. Patients with IC/BPS exhibited shorter levator muscles (right: 5.0 ± 0.7 vs. 5.6 ± 0.8, left: 5.0 ± 0.8 vs. 5.7 ± 0.8 cm, P < 0.002) and a wider posterior puborectalis angle (35.0 ± 8.6 vs. 26.7 ± 7.9°, P < 0.01) compared with controls. The H line was shorter in patients with IC/BPS (7.8 ± 0.8 vs. 8.6 ± 0.9 cm, P < 0.02), while M line did not differ. Total urethral length was similar, but vaginal cuff and bladder neck distances to the H line were longer in patients with IC/BPS (5.7 ± 0.6 vs. 5.1 ± 0.9 cm, P < 0.02; 1.9 ± 0.4 vs. 1.4 ± 0.2 cm, P < 0.001, respectively). CONCLUSIONS: Patients with IC/BPS have pelvic floor hypertonicity on MRI, which manifests as shortened levator, increased posterior puborectalis angles, and decreased puborectal distances. We identified evidence of pelvic floor hypertonicity in patients with IC/BPS, which may contribute to or amplify pelvic pain. Future studies are necessary to determine the MRI utility in understanding pelvic floor hypertonicity in patients with IC/BPS.

Pulmonary coccidioidomycosis: pictorial review of chest radiographic and CT findings.

Pulmonary coccidioidomycosis is a fungal disease endemic to the desert regions of the southwestern United States, Mexico, Central America, and South America. The incidence of reported disease increased substantially between 1998 and 2011, and the infection is encountered beyond the endemic areas because of a mobile society. The disease is caused by inhalation of spores of Coccidioides species. Individuals at high risk are those exposed to frequent soil aerosolization. The diagnosis is established by direct visualization of mature spherules by using special stains or cultures from biologic specimens. Serologic testing of anticoccidioidal antibodies is used for diagnosis and treatment monitoring. The infection is self-limited in 60% of cases. When the disease is symptomatic, the lung is the primary site of involvement. On the basis of clinical presentation and imaging abnormalities, pulmonary involvement is categorized into acute, disseminated, and chronic forms, each with a spectrum of imaging findings. In patients with acute disease, the most common findings are lobar or segmental consolidation, multifocal consolidation, and nodules. Adenopathy and pleural effusions are also seen, usually in association with parenchymal disease. Disseminated disease is rare and occurs in less than 1% of patients. Pulmonary findings are miliary nodules and confluent parenchymal opacities. Acute respiratory distress syndrome is an infrequent complication of disseminated disease. The acute findings resolve in most patients, with chronic changes developing in approximately 5% of patients. Manifestations of chronic disease include residual nodules, chronic cavities, persistent pneumonia with or without adenopathy, pleural effusion, and regressive changes. Unusual complications of chronic disease are mycetoma, abscess formation, and bronchopleural fistula. Patients in an immunocompromised state, those with diabetes mellitus, pregnant women, and those belonging to certain ethnic groups may show severe, progressive, or disseminated disease.