Multi-scale, domain knowledge-guided attention + random forest: a two-stage deep learning-based multi-scale guided attention models to diagnose idiopathic pulmonary fibrosis from computed tomography images.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and usually fatal lung disease of unknown reasons, generally affecting the elderly population. Early diagnosis of IPF is crucial for triaging patients' treatment planning into anti-fibrotic treatment or treatments for other causes of pulmonary fibrosis. However, current IPF diagnosis workflow is complicated and time-consuming, which involves collaborative efforts from radiologists, pathologists, and clinicians and it is largely subject to inter-observer variability. PURPOSE: The purpose of this work is to develop a deep learning-based automated system that can diagnose subjects with IPF among subjects with interstitial lung disease (ILD) using an axial chest computed tomography (CT) scan. This work can potentially enable timely diagnosis decisions and reduce inter-observer variability. METHODS: Our dataset contains CT scans from 349 IPF patients and 529 non-IPF ILD patients. We used 80% of the dataset for training and validation purposes and 20% as the holdout test set. We proposed a two-stage model: at stage one, we built a multi-scale, domain knowledge-guided attention model (MSGA) that encouraged the model to focus on specific areas of interest to enhance model explainability, including both high- and medium-resolution attentions; at stage two, we collected the output from MSGA and constructed a random forest (RF) classifier for patient-level diagnosis, to further boost model accuracy. RF classifier is utilized as a final decision stage since it is interpretable, computationally fast, and can handle correlated variables. Model utility was examined by (1) accuracy, represented by the area under the receiver operating characteristic curve (AUC) with standard deviation (SD), and (2) explainability, illustrated by the visual examination of the estimated attention maps which showed the important areas for model diagnostics. RESULTS: During the training and validation stage, we observe that when we provide no guidance from domain knowledge, the IPF diagnosis model reaches acceptable performance (AUC±SD = 0.93±0.07), but lacks explainability; when including only guided high- or medium-resolution attention, the learned attention maps are not satisfactory; when including both high- and medium-resolution attention, under certain hyperparameter settings, the model reaches the highest AUC among all experiments (AUC±SD = 0.99±0.01) and the estimated attention maps concentrate on the regions of interests for this task. Three best-performing hyperparameter selections according to MSGA were applied to the holdout test set and reached comparable model performance to that of the validation set. CONCLUSIONS: Our results suggest that, for a task with only scan-level labels available, MSGA+RF can utilize the population-level domain knowledge to guide the training of the network, which increases both model accuracy and explainability.

Effect of indacaterol/glycopyrronium on ventilation and perfusion in COPD: a randomized trial.

RATIONALE: The long-acting ß2-agonist/long-acting muscarinic antagonist combination indacaterol/glycopyrronium (IND/GLY) elicits bronchodilation, improves symptoms, and reduces exacerbations in COPD. Magnetic resonance imaging (MRI) of the lung with hyperpolarized gas and gadolinium contrast enhancement enables assessment of whole lung functional responses to IND/GLY. OBJECTIVES: The primary objective was assessment of effect of IND/GLY on global ventilated lung volume (%VV) versus placebo in COPD. Lung function, regional ventilation and perfusion in response to IND/GLY were also measured. METHODS: This double-blind, randomized, placebo-controlled, crossover study assessed %VV and pulmonary perfusion in patients with moderate-to-severe COPD after 8 days of once-daily IND/GLY treatment (110/50 µg) followed by 8 days of placebo, or vice versa, using inhaled hyperpolarized 3He gas and gadolinium contrast-enhanced MRI, respectively. Lung function measures including spirometry were performed for each treatment after 8 days. MEASUREMENTS AND MAIN RESULTS: Of 31 patients randomized, 29 completed both treatment periods. IND/GLY increased global %VV versus placebo (61.73% vs. 56.73%, respectively, least squares means treatment difference: 5.00% [90% CI 1.40 to 8.60]; P = 0.025). IND/GLY improved whole lung index of ventilation volume to perfusion volume (V/Q) ratio versus placebo; 94% (90% CI 83 to 105) versus 86% (90% CI 75 to 97; P = 0.047), respectively. IND/GLY showed a trend to improve diffusing capacity for carbon monoxide (DLCO) (+ 0.66 mL/min/mmHg; P = 0.082). By Day 8, forced expiratory volume in 1 s (FEV1) was increased by 0.32 L versus placebo (90% CI 0.26 to 0.38; P < 0.0001), substantiating earlier findings and providing evidence of assay sensitivity for this trial. CONCLUSIONS: IND/GLY improved lung ventilation assessed by 3He MRI after 1 week of treatment. This observation may provide mechanistic support for the symptomatic clinical benefit shown with IND/GLY in COPD. Clinical trial registered with www.clinicaltrials.gov (NCT02634983).

Radiographic read paradigms and the roles of the central imaging laboratory in neuro-oncology clinical trials.

Determination of therapeutic benefit in intracranial tumors is intimately dependent on serial assessment of radiographic images. The Response Assessment in Neuro-Oncology (RANO) criteria were established in 2010 to provide an updated framework to better characterize tumor response to contemporary treatments. Since this initial update a number of RANO criteria have provided some basic principles for the interpretation of changes on MR images; however, the details of how to operationalize RANO and other criteria for use in clinical trials are ambiguous and not standardized. In this review article designed for the neuro-oncologist or treating clinician, we outline essential steps for performing radiographic assessments by highlighting primary features of the Imaging Charter (referred to as the Charter for the remainder of this article), a document that describes the clinical trial imaging methodology and methods to ensure operationalization of the Charter into the workings of a clinical trial. Lastly, we provide recommendations for specific changes to optimize this methodology for neuro-oncology, including image registration, requirement of growing tumor for eligibility in trials of recurrent tumor, standardized image acquisition guidelines, and hybrid reader paradigms that allow for both unbiased measurements and more comprehensive interpretation.

Prediction of idiopathic pulmonary fibrosis progression using early quantitative changes on CT imaging for a short term of clinical 18-24-month follow-ups.

OBJECTIVE: High-resolution computed tomography (HRCT) plays an indispensable role in the diagnosis of idiopathic pulmonary fibrosis (IPF). Due to unpredictability in progression and the short median survival of 2-5 years, it is critical to delineate the patients with rapid progression. The aim is to evaluate the predictability of IPF progression using the early quantitative changes. METHODS: Automated texture-based quantitative lung fibrosis (QLF) was calculated from the anonymized HRCT. Two datasets were collected retrospectively: (1) a pilot study of 35 subjects with three sequential scans (baseline and 6 and 12 months) to obtain a threshold, where visual assessments were stable at 6 months but worsened at 12 months; (2) 157 independent subjects to test the threshold. Landmark Cox regressions were used to compare the progression-free survival (PFS) defined by pulmonary function using the threshold from the early changes in QLF. C-indexes were reported as estimations of the concordance of prediction. RESULTS: A threshold of 4% QLF change at 6 months corresponded to the mean change that worsened on HRCT visually at 12 months from the pilot study. Using the threshold, significant differences were found in the independent dataset (hazard ratio (HZ) = 5.92, p = 0.001 by Cox model, C-index = 0.71 at the most severe lobe; and HZ = 3.22, p = 0.012, C-index = 0.68 in the whole lung). Median PFS was 11.9 months for subjects with ≥ 4% changes, whereas median PFS was greater than 18 months for subjects with < 4% changes at the most severe lobe. CONCLUSION: Early structural changes on HRCT using a quantitative score can predict progression in lung function. KEY POINTS: • Changes on HRCT using quantitative texture-based scores can play a pivotal role for providing information and an aid tool for timely management decision for patients with IPF. • Quantitative changes on HRCT of 4% or more, which matched 6-month prior changes with visual assessment of worsening, can play a pivotal role for providing prediction of clinical progression by 3-5 folds higher in the next incidence, compared with those of subjects with less than 4% changes. • Early structural changes of 4% or more in a paired HRCT scans derived by quantitative scores can predict the progression in lung function in 1-2 years in subjects with IPF, which is critical information for timely management decision for subjects with IPF where the median survival is 2 to 5 years.

Association of tumor grade, enhancement on multiphasic CT and microvessel density in patients with clear cell renal cell carcinoma.

PURPOSE: Clear cell renal cell carcinoma (ccRCC) comprises nearly 90% of all diagnosed RCC subtypes and has the worst prognosis and highest metastatic potential. The strongest prognostic factors for patients with ccRCC include histological subtype and Fuhrman grade, which are incorporated into prognostic models. Since ccRCC is a highly vascularized tumor, there may be differences in enhancement patterns on multidetector CT (MDCT) due to the hemodynamics and microvessel density (MVD) of the lesions. This may provide a noninvasive method to characterize incidentally detected low- and high-grade ccRCCs on MDCT. The purpose of our study was to determine the correlation between MDCT enhancement parameters, ccRCC MVD, and Fuhrman grade to determine its utility and value in assessing tumor vascularity and grade in vivo. METHODS: In this retrospective, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low-grade (LG), and 43 high-grade (HG) ccRCCs underwent preoperative four-phase MDCT. A 3D volume of interest (VOI) was obtained for every tumor and absolute enhancement and the wash-in/wash-out of enhancement for each phase was assessed. Immunohistochemistry on resected specimens was used to quantify MVD. Linear regression and Pearson correlation were used to investigate the strength of the association between 3D VOI enhancement and MVD. Stepwise logistic regression analysis determined independent predictors of HG ccRCC. Cut-off values and odds Ratio (OR) with 95% CIs were reported. The clinical, radiomic, and pathologic features with the highest performance in the stepwise logistic regression analysis were evaluated using receiver operator characteristics (ROC) and area under the curve (AUC). RESULTS: Absolute enhancement in the nephrographic phase < 52.1 Hounsfield Units (HU) (HR 0.979, 95% CI 0.964-0.994, p value = 0.006), lesion size > 4.3 cm (HR 1.450, 95% CI 1.211-1.738, p value < 0.001), and an intratumoral MVD < 15% (HR 0.932, 95% CI 0.867-1.002, p value = 0.058) were independent predictors of HG ccRCC with an AUC of 0.818 (95% CI 0.725-0.911). HG ccRCCs had a significant association between 3D VOI enhancement and MVD in each post-contrast phase (r2 = 0.238 to 0.455, p < 0.05). CONCLUSIONS: Absolute enhancement of the entire lesion obtained from a 3D VOI in the nephrographic phase on preoperative MDCT can provide quantitative data that are a significant, independent predictor of a high-grade clear cell RCC and can be used to assess tumor vascularity and grade in vivo.

Correction to: Toward clinically usable CAD for lung cancer screening with computed tomography.

The original version of this article, published on 24 July 2014, unfortunately contained a mistake. In section "Discussion," a sentence was worded incorrectly.

Prediction of progression in idiopathic pulmonary fibrosis using CT scans at baseline: A quantum particle swarm optimization - Random forest approach.

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease characterized by an unpredictable progressive decline in lung function. Natural history of IPF is unknown and the prediction of disease progression at the time of diagnosis is notoriously difficult. High resolution computed tomography (HRCT) has been used for the diagnosis of IPF, but not generally for monitoring purpose. The objective of this work is to develop a novel predictive model for the radiological progression pattern at voxel-wise level using only baseline HRCT scans. Mainly, there are two challenges: (a) obtaining a data set of features for region of interest (ROI) on baseline HRCT scans and their follow-up status; and (b) simultaneously selecting important features from high-dimensional space, and optimizing the prediction performance. We resolved the first challenge by implementing a study design and having an expert radiologist contour ROIs at baseline scans, depending on its progression status in follow-up visits. For the second challenge, we integrated the feature selection with prediction by developing an algorithm using a wrapper method that combines quantum particle swarm optimization to select a small number of features with random forest to classify early patterns of progression. We applied our proposed algorithm to analyze anonymized HRCT images from 50 IPF subjects from a multi-center clinical trial. We showed that it yields a parsimonious model with 81.8% sensitivity, 82.2% specificity and an overall accuracy rate of 82.1% at the ROI level. These results are superior to other popular feature selections and classification methods, in that our method produces higher accuracy in prediction of progression and more balanced sensitivity and specificity with a smaller number of selected features. Our work is the first approach to show that it is possible to use only baseline HRCT scans to predict progressive ROIs at 6 months to 1year follow-ups using artificial intelligence.

Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT.

PURPOSE: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cell RCC (ccRCC) and benign oncocytoma (ONC). Radiomics has attracted increased attention for its utility in pre-operative work-up on routine clinical images. Radiomics based approaches have converted medical images into mineable data and identified prognostic imaging signatures that machine learning algorithms can use to construct predictive models by learning the decision boundaries of the underlying data distribution. The TensorFlow™ framework from Google is a state-of-the-art open-source software library that can be used for training deep learning neural networks for performing machine learning tasks. The purpose of this study was to investigate the diagnostic value and feasibility of a deep learning-based renal lesion classifier using open-source Google TensorFlow™ Inception in differentiating ccRCC from ONC on routine four-phase MDCT in patients with pathologically confirmed renal masses. METHODS: With institutional review board approval for this 1996 Health Insurance Portability and Accountability Act compliant retrospective study and a waiver of informed consent, we queried our institution's pathology, clinical, and radiology databases for histologically proven cases of ccRCC and ONC obtained between January 2000 and January 2016 scanned with a an intravenous contrast-enhanced four-phase renal mass protocol (unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases). To extract features to be used for the machine learning model, the entire renal mass was contoured in the axial plane in each of the four phases, resulting in a 3D volume of interest (VOI) representative of the entire renal mass. We investigated thirteen different approaches to convert the acquired VOI data into a set of images that adequately represented each tumor which was used to train the final layer of the neural network model. Training was performed over 4000 iterations. In each iteration, 90% of the data were designated as training data and the remaining 10% served as validation data and a leave-one-out cross-validation scheme was implemented. Accuracy, sensitivity, specificity, positive (PPV) and negative predictive (NPV) values, and CIs were calculated for the classification of the thirteen processing modes. RESULTS: We analyzed 179 consecutive patients with 179 lesions (128 ccRCC and 51 ONC). The ccRCC cohort had a mean size of 3.8 cm (range 0.8-14.6 cm) and the ONC cohort had a mean lesion size of 3.9 cm (range 1.0-13.1 cm). The highest specificity and PPV (52.9% and 80.3%, respectively) were achieved in the EX phase when we analyzed the single mid-slice of the tumor in the axial, coronal and sagittal plane, and when we increased the number of mid-slices of the tumor to three, with an accuracy of 75.4%, which also increased the sensitivity to 88.3% and the PPV to 79.6%. Using the entire tumor volume also showed that classification performance was best in the EX phase with an accuracy of 74.4%, a sensitivity of 85.8% and a PPV of 80.1%. When the entire tumor volume, plus mid-slices from all phases and all planes presented as tiled images, were submitted to the final layer of the neural network we achieved a PPV of 82.5%. CONCLUSIONS: The best classification result was obtained in the EX phase among the thirteen classification methods tested. Our proof of concept study is the first step towards understanding the utility of machine learning in the differentiation of ccRCC from ONC on routine CT images. We hope this could lead to future investigation into the development of a multivariate machine learning model which may augment our ability to accurately predict renal lesion histology on imaging.

Association of qualitative and quantitative imaging features on multiphasic multidetector CT with tumor grade in clear cell renal cell carcinoma.

PURPOSE: The purpose of the study was to determine if enhancement features and qualitative imaging features on multiphasic multidetector computed tomography (MDCT) were associated with tumor grade in patients with clear cell renal cell carcinoma (ccRCC). METHODS: In this retrospective, IRB approved, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low grade (LG) and 43 high grade (HG) ccRCCs underwent preoperative four-phase MDCT in unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases. Previously published quantitative (absolute peak lesion enhancement, absolute peak lesion enhancement relative to normal enhancing renal cortex, 3D whole lesion enhancement and the wash-in/wash-out of enhancement within the 3D whole lesion ROI) and qualitative (enhancement pattern; presence of necrosis; pattern of; tumor margin; tumor-parenchymal interface, tumor-parenchymal interaction; intratumoral vascularity; collecting system infiltration; renal vein invasion; and calcification) assessments were obtained for each lesion independently by two fellowship-trained genitourinary radiologists. Comparisons between variables included χ2, ANOVA, and student t test. p values less than 0.05 were considered to be significant. Inter-reader agreement was obtained with the Gwet agreement coefficient (AC1) and standard error (SE) was reported. RESULTS: No significant differences were observed between the LG and HG ccRCC cohorts with respect to absolute peak lesion enhancement and relative lesion enhancement ratio. There was a significant inverse correlation between low and high grade ccRCC and tumor enhancement the NP (71 HU vs. 54 HU, p < 0.001) and EX (52 HU vs. 39 HU, p < 0.001) phases using the 3D whole lesion ROI method. The percent wash-in of 3D enhancement from the UN to the CM phase was also significantly different between LG and HG ccRCCs (352% vs. 255%, p = 0.003). HG lesions showed significantly more calcification, necrosis, collecting system infiltration and ill-defined tumor margins (p < 0.05). Overall agreement between the two readers had a mean AC1 of 0.8172 (SE 0.0235). CONCLUSIONS: Quantitatively, high grade ccRCC had significantly lower whole lesion enhancement in the NP and EX phases on MDCT. Qualitatively, high grade ccRCC were significantly more likely to be associated with calcifications, necrosis, collecting system infiltration, and an ill-defined tumor margin.

Pisotriquetral Pain Treated with Bilateral Pisiform Excision in a Collegiate Diver.

Background Pisiform excision and pisotriquetral arthrodesis are two surgical options for the treatment of pisotriquetral joint pain when conservative methods fail. However, it is unclear which option is best for patients who experience substantial, repetitive loading on their wrists and wish to preserve wrist flexibility and function. Case Description We present a case of bilateral ulnar-sided wrist pain related to the pisotriquetral joint in a 19-year-old collegiate diver. The pain was exacerbated by activities specific to this sport that requires wrist hyperextension, namely full weight-bearing on the hands (handstands), and has an impact on the hands and wrists upon water entry during dives due to direct palmar pressure. There were no radiographic signs of arthritis; however, there were bone marrow changes on magnetic resonance imaging (MRI). Management with rest, splinting, and corticosteroid injection failed to relieve the pain and precluded his ability to return to full-time diving. Treatment consisted of bilateral pisiform excision. Postoperatively, the patient returned to full-time competitive diving with resolution of his painful symptoms. Literature Review Pisiform excision has been shown to have successful outcomes in terms of return to play for lower impact athletes (such as badminton) but has not been reported in athletes who experience a high degree of force repetitively (such as gymnasts or divers). There is one report of pisotriquetral arthrodesis in a young gymnast with suboptimal results. Clinical Relevance This case report demonstrates that pisiform excision is a successful treatment for elite athletes who experience repetitive, palmar force on hyperextended wrists and subsequently develop ulnar-sided wrist pain.

Building a high-resolution T2-weighted MR-based probabilistic model of tumor occurrence in the prostate.

PURPOSE: We present a method for generating a T2 MR-based probabilistic model of tumor occurrence in the prostate to guide the selection of anatomical sites for targeted biopsies and serve as a diagnostic tool to aid radiological evaluation of prostate cancer. MATERIALS AND METHODS: In our study, the prostate and any radiological findings within were segmented retrospectively on 3D T2-weighted MR images of 266 subjects who underwent radical prostatectomy. Subsequent histopathological analysis determined both the ground truth and the Gleason grade of the tumors. A randomly chosen subset of 19 subjects was used to generate a multi-subject-derived prostate template. Subsequently, a cascading registration algorithm involving both affine and non-rigid B-spline transforms was used to register the prostate of every subject to the template. Corresponding transformation of radiological findings yielded a population-based probabilistic model of tumor occurrence. The quality of our probabilistic model building approach was statistically evaluated by measuring the proportion of correct placements of tumors in the prostate template, i.e., the number of tumors that maintained their anatomical location within the prostate after their transformation into the prostate template space. RESULTS: Probabilistic model built with tumors deemed clinically significant demonstrated a heterogeneous distribution of tumors, with higher likelihood of tumor occurrence at the mid-gland anterior transition zone and the base-to-mid-gland posterior peripheral zones. Of 250 MR lesions analyzed, 248 maintained their original anatomical location with respect to the prostate zones after transformation to the prostate. CONCLUSION: We present a robust method for generating a probabilistic model of tumor occurrence in the prostate that could aid clinical decision making, such as selection of anatomical sites for MR-guided prostate biopsies.

Quantitative bone scan lesion area as an early surrogate outcome measure indicative of overall survival in metastatic prostate cancer.

A clinical validation of the bone scan lesion area (BSLA) as a quantitative imaging biomarker was performed in metastatic castration-resistant prostate cancer (mCRPC). BSLA was computed from whole-body bone scintigraphy at baseline and week 12 posttreatment in a cohort of 198 mCRPC subjects (127 treated and 71 placebo) from a clinical trial involving a different drug from the initial biomarker development. BSLA computation involved automated image normalization, lesion segmentation, and summation of the total area of segmented lesions on bone scan AP and PA views as a measure of tumor burden. As a predictive biomarker, treated subjects with baseline BSLA [Formula: see text] had longer survival than those with higher BSLA ([Formula: see text] and [Formula: see text]). As a surrogate outcome biomarker, subjects were categorized as progressive disease (PD) if the BSLA increased by a prespecified 30% or more from baseline to week 12 and non-PD otherwise. Overall survival rates between PD and non-PD groups were statistically different ([Formula: see text] and [Formula: see text]). Subjects without PD at week 12 had longer survival than subjects with PD: median 398 days versus 280 days. BSLA has now been demonstrated to be an early surrogate outcome for overall survival in different prostate cancer drug treatments.

Quantitative computer-aided diagnostic algorithm for automated detection of peak lesion attenuation in differentiating clear cell from papillary and chromophobe renal cell carcinoma, oncocytoma, and fat-poor angiomyolipoma on multiphasic multidetector computed tomography.

OBJECTIVE: To evaluate the performance of a novel, quantitative computer-aided diagnostic (CAD) algorithm on four-phase multidetector computed tomography (MDCT) to detect peak lesion attenuation to enable differentiation of clear cell renal cell carcinoma (ccRCC) from chromophobe RCC (chRCC), papillary RCC (pRCC), oncocytoma, and fat-poor angiomyolipoma (fp-AML). MATERIALS AND METHODS: We queried our clinical databases to obtain a cohort of histologically proven renal masses with preoperative MDCT with four phases [unenhanced (U), corticomedullary (CM), nephrographic (NP), and excretory (E)]. A whole lesion 3D contour was obtained in all four phases. The CAD algorithm determined a region of interest (ROI) of peak lesion attenuation within the 3D lesion contour. For comparison, a manual ROI was separately placed in the most enhancing portion of the lesion by visual inspection for a reference standard, and in uninvolved renal cortex. Relative lesion attenuation for both CAD and manual methods was obtained by normalizing the CAD peak lesion attenuation ROI (and the reference standard manually placed ROI) to uninvolved renal cortex with the formula [(peak lesion attenuation ROI - cortex ROI)/cortex ROI] × 100%. ROC analysis and area under the curve (AUC) were used to assess diagnostic performance. Bland-Altman analysis was used to compare peak ROI between CAD and manual method. RESULTS: The study cohort comprised 200 patients with 200 unique renal masses: 106 (53%) ccRCC, 32 (16%) oncocytomas, 18 (9%) chRCCs, 34 (17%) pRCCs, and 10 (5%) fp-AMLs. In the CM phase, CAD-derived ROI enabled characterization of ccRCC from chRCC, pRCC, oncocytoma, and fp-AML with AUCs of 0.850 (95% CI 0.732-0.968), 0.959 (95% CI 0.930-0.989), 0.792 (95% CI 0.716-0.869), and 0.825 (95% CI 0.703-0.948), respectively. On Bland-Altman analysis, there was excellent agreement of CAD and manual methods with mean differences between 14 and 26 HU in each phase. CONCLUSION: A novel, quantitative CAD algorithm enabled robust peak HU lesion detection and discrimination of ccRCC from other renal lesions with similar performance compared to the manual method.

Unusual Presentation of Infantile Myofibroma in the Deep Palm of a Child: A Case Report and Discussion of the Differential Diagnosis.

Infantile myofibroma or myofibromatosis is a myofibroblastic and fibroblastic proliferation that is most commonly reported in children younger than 2 years of age. It is a benign process composed histologically of a biphasic pattern of spindle-shaped cells surrounding a zone of less differentiated cells in a hemangiopericytoma-like pattern. We report this tumor in a unique presentation in the deep palm of a 2-year-old child without skin ulceration and with an intimate association with the median nerve. The well-circumscribed nature of the tumor facilitated complete excision with neural preservation. Final pathology was consistent with an unusual type of myofibroma or myofibromatosis. Conservative management with partial excision has been advocated for these masses because of potential surgical morbidity and its benign nature. This case report highlights the differential diagnosis of uncommon soft tissue tumors in the pediatric hand as well as the importance of a surgeon's surgical assessment in guiding treatment.

Mapping the superficial inferior epigastric system and its connection to the deep system: An MRA analysis.

The superficial inferior epigastric vasculature plays a critical role in free abdominal tissue transfer. However, its anatomic variations are incompletely characterized. An investigation was conducted on the preoperative imaging of patients undergoing free-flap breast reconstruction by a single surgeon between 2008 and 2013. This study included patients who underwent abdominal magnetic resonance angiogram (MRA). A coordinate system was used to draw the main trunk and primary branches from each patient's superficial inferior epigastric system. Each hemiabdomen's branching pattern was categorized as simple, complex, or absent. The number of superficial-to-deep inferior epigastric connections and the presence or absence of a superficial system crossing the midline were recorded. Interrater reliability was assessed for two raters. This analysis included 53 patients (106 hemiabdomens). A total of 80 (75%) hemiabdomens were categorized as having simple and 10 (9%) as complex branching patterns. A total of 16 (15%) hemiabdomens had no identifiable vessels. At least one superficial-to-deep connection was found among 89 hemiabdomens (84%). Superficial systems crossing the midline were found in 14 patients (26%). Our findings support the high degree of anatomic variation in the superficial inferior epigastric system, including a significant number of patients lacking superficial-to-deep connections and bilaterally communicating systems. These variations may be identified on preoperative MRA.

Timing of radiation and outcomes in implant-based breast reconstruction.

OBJECTIVE: Limited data exist regarding the effect of radiation timing on complications of tissue expander/implant-based breast reconstruction. This study seeks to compare outcomes of tissue expander/implant reconstruction in patients undergoing postmastectomy radiotherapy, those with previous radiation therapy following breast conservation therapy, and those who did not receive radiation therapy. METHODS: The records of the patients of a single surgeon were reviewed from January 2007 to July 2013. All patients undergoing tissue expander/implant breast reconstruction were placed into one of three groups based on the timing of radiation therapy: postmastectomy (Current), previously following breast conservation therapy (Prior), and no radiotherapy (No XRT). Medical records were reviewed for any reported complications, and statistical analysis was performed. RESULTS: A total of 210 patients (265 breasts) were included in the analysis. Current patients were more likely than No XRT patients to experience expander infection (20% vs. 2.6%, p = 0.001) and expander removal (26% vs. 8.3%, p = 0.007). Prior patients were more likely than No XRT patients to undergo conversion to tissue flap reconstruction (10.5% vs. 0.6%, p = 0.031). No significant differences were found between groups with respect to cellulitis, abscess formation, hematoma, seroma, skin flap necrosis, expander exposure, implant exposure, or implant infection. CONCLUSIONS: This study supports the relative safety of tissue expander/implant breast reconstruction in selected groups of patients who have received radiation therapy. Differences in rates of expander infection, expander removal, and conversion to tissue flap reconstruction represent potential areas for further research.

Three-Dimensional Changes in the Midface Following Malar Calcium Hydroxyapatite Injection in a Cadaver Model.

BACKGROUND: Three-dimensional (3D) changes in the midface following malar calcium hydroxyapatite (CaHa) injection have not been systematically analyzed. OBJECTIVES: The authors analyzed 3D volume changes in midface and naso-labial fold (NLF) volume, as well as lateral movement in the NLF/naso-labial crease (NLC) junction following malar injection of CaHa in a cadaver model. METHODS: A single surgeon injected CaHa in the supraperiosteal plane. Sequential images were obtained with the VECTRA 3D system pre- and post-1.5- and 3-cc CaHa injections. All measurements were performed by a single examiner. Injection location was verified anatomically. RESULTS: Injections were performed in 16 fresh cadaver hemi-faces. Maximal increases in projection were centered on the malar injection site, with associated decreases in projection and volume in the infero-medial locations. Relative mean increases in volume of 3.16 cc and 4.94 cc were observed following the 1.5-cc and 3-cc injections, respectively. There was a relative decrease in the volume of the NLF of -0.3 cc and -0.4 cc following the 1.5- and 3-cc injections, respectively. Injection of CaHa was associated with lateral movements of the NLF-NLC junction at the level of the nasal sill, philtral columns, and oral commissure, measuring 2.7, 2.5, and 1.9 mm and 2.8, 2.9, and 2.4 mm following the 1.5- and 3-cc injections, respectively. Anatomical dissection verified the location in the supraperiosteal space and within the middle malar fat pad. CONCLUSIONS: Following malar CaHa injection, 3D photographic analysis showed a measureable lifting effect with recruitment of ptotic tissue and lateral movement of the NLF-NLC junction in a cadaver model.

Environmental factors that contribute to upper eyelid ptosis: a study of identical twins.

BACKGROUND: Current literature provides little information about the impact of environmental exposures on the severity of acquired blepharoptosis. OBJECTIVE: The authors assessed environmental factors that may contribute to eyelid ptosis in a population of identical twins. METHODS: Photographs of 286 sets of twins from a prospectively collected database from 2008 to 2010 were reviewed. The authors identified 96 sets of identical twins (192 individual persons) who had differing severity of ptosis. Digital photographs were analyzed, and the degree of ptosis was measured in each eye of every subject. The external factors that could potentially contribute to blepharoptosis were taken into consideration. The authors then assessed the correlations of 9 different environmental risk factors with ptosis. Generalized linear mixed model were constructed to determine the associations of ptosis measurements with environmental risk factors obtained from the subject survey database. RESULTS: The mean level of upper eyelid ptosis in the study population was 1.1 mm. The mean difference in ptosis between twins was 0.5 mm. Wearing contact lenses, either hard or soft, was significantly associated with ptosis. The mean ptosis measurement among twins who did not wear contact lenses was 1.0 mm; for those who wore soft contact lenses, the mean was 1.41 mm, and for those who wore hard contact lenses, the mean was 1.84 mm. CONCLUSIONS: Acquired ptosis is not linked to body mass index, smoking behavior, sun exposure, alcohol use, work stress, or sleep. Wearing either hard or soft lenses was associated with an increased risk of ptosis. These influences are independent of genetic predisposition. LEVEL OF EVIDENCE: 3 Diagnostic.

Comparison of the quantitative CT imaging biomarkers of idiopathic pulmonary fibrosis at baseline and early change with an interval of 7 months.

RATIONALE AND OBJECTIVES: Median survival of patients with idiopathic pulmonary fibrosis (IPF) is 2-5 years. Sensitive imaging metrics can play a role in detecting early changes in therapeutic development. The aim of the present study was to compare known computed tomography (CT) histogram kurtosis and a classifier-based quantitative score to assess baseline severity and change over time in patients with IPF. MATERIALS AND METHODS: A total of 57 patients with at least baseline and paired follow-up scans were selected from an imaging database of standardized CT scans obtained from patients with IPF. CT histogram measurement of kurtosis and quantitative lung fibrosis (QLF) and quantitative interstitial lung disease (QILD) scores from a classification algorithm were calculated. Spearman rank correlations were used to assess associations between baseline severity and changes for all CT-derived measures compared to forced vital capacity (FVC) and carbon monoxide diffusion capacity (DLCO) (percent predicted). RESULTS: At baseline, mean (±SD) of kurtosis was 2.43 (±1.83). Mean (±SD) values of QLF and QILD scores were 20.7% (±13.4) and 43.3% (±20.0), respectively. All baseline histogram indices and QLF and QILD scores were correlated well with baseline FVC and DLCO. When assessing associations with changes in FVC and DLCO over time, only QLF score was statistically significant (ρ = -0.57; P < .0001 for FVC and ρ = -0.34; P = .025 for DLCO), whereas kurtosis was not. CONCLUSIONS: Classifier-model-derived scores (QLF and QILD), based on a set of texture features, are associated with baseline disease extent and are also a sensitive measure of change over time. A QLF score can be used for measuring the extent of disease severity and longitudinal changes.

Toward clinically usable CAD for lung cancer screening with computed tomography.

OBJECTIVES: The purpose of this study was to define clinically appropriate, computer-aided lung nodule detection (CAD) requirements and protocols based on recent screening trials. In the following paper, we describe a CAD evaluation methodology based on a publically available, annotated computed tomography (CT) image data set, and demonstrate the evaluation of a new CAD system with the functionality and performance required for adoption in clinical practice. METHODS: A new automated lung nodule detection and measurement system was developed that incorporates intensity thresholding, a Euclidean Distance Transformation, and segmentation based on watersheds. System performance was evaluated against the Lung Imaging Database Consortium (LIDC) CT reference data set. RESULTS: The test set comprised thin-section CT scans from 108 LIDC subjects. The median (±IQR) sensitivity per subject was 100 (±37.5) for nodules ≥ 4 mm and 100 (±8.33) for nodules ≥ 8 mm. The corresponding false positive rates were 0 (±2.0) and 0 (±1.0), respectively. The concordance correlation coefficient between the CAD nodule diameter and the LIDC reference was 0.91, and for volume it was 0.90. CONCLUSIONS: The new CAD system shows high nodule sensitivity with a low false positive rate. Automated volume measurements have strong agreement with the reference standard. Thus, it provides comprehensive, clinically-usable lung nodule detection and assessment functionality. KEY POINTS: • CAD requirements can be based on lung cancer screening trial results. • CAD systems can be evaluated using publically available annotated CT image databases. • A new CAD system was developed with a low false positive rate. • The CAD system has reliable measurement tools needed for clinical use.