ABSTRACT
Solitary fibrous tumors are rare mesenchymal neoplasms that can range from slow-growing to aggressive tumors. This report presents a unique case of a young male patient with a solitary fibrous tumor involving the seminal vesicle, a rare location, and reinforces incidental discovery of these tumors on imaging and physical exams. Detection of these tumors is imperative to identify and treat malignancy. In our case, a 39-year-old previously healthy Asian male presents to the emergency department as a trauma admission post bicycle crash and is incidentally found to have a pelvic mass on computed tomography imaging of the pelvis. The patient underwent trans-anal biopsy which showed spindle epithelioid cells positive for CD34 and STAT6 markers, with a morphological and immunohistochemical profile consistent with a solitary fibrous tumor. The patient underwent surgery with a robotic-assisted laparoscopic pelvic mass resection and now follows up annually with imaging for observation.
ABSTRACT
OBJECTIVE: To evaluate the prevalence of financial hardship and health-related social needs (HRSNs) among outpatients undergoing advanced imaging services and assess the feasibility of screening for financial and social needs during radiology encounters. METHODS: Adult patients receiving CT, MRI, or PET/CT at outpatient imaging centers of an academic tertiary center were asked to complete a 15-minute survey with adapted validated questions inquiring about their experience of financial hardship related to imaging and HRSNs, and the appropriateness of screening for financial and social needs at radiology encounters. Logistic regression analyses were performed to assess factors associated with perceived appropriateness of screening and level of interest in meeting with financial counselors. RESULTS: A total of 430 patients responded (10.0% response rate; mean age: 57.1 years; 57.4% female; 54.5% White; 22.1% Hispanic; 19.1% Asian; 1% Black). A total of 35% reported experiencing financial hardship with imaging; 47.5% reported material hardship, 15.3% reported cost-related care nonadherence, and 5.3% reported cost-related imaging nonadherence. Overall, 35.9% had at least one HRSN, with food insecurity being the most common (28.3%). The majority (79.7%) felt that being screened for HRSNs at radiology encounters is appropriate, with those experiencing imaging hardship being more likely to feel that screening is appropriate (odds ratio [OR]: 2.93; 95% confidence interval [CI], 1.31-6.56). Overall, 29.5% were interested in meeting with a financial counselor, with those with imaging hardship (OR: 3.70; 95% CI, 1.96-6.97) and HRSNs (OR: 2.87; 95% CI, 1.32-6.24) and who felt uncomfortable with screening (OR: 2.83; 95% CI, 1.14-7.03) being more likely to be interested. DISCUSSION: Financial hardship and HRSNs are common among outpatients undergoing advanced imaging, with the majority reporting that getting screened at radiology encounters is appropriate.
ABSTRACT
Hepatosplenomegaly is commonly diagnosed by radiologists based on single dimension measurements and heuristic cut-offs. Volumetric measurements may be more accurate for diagnosing organ enlargement. Artificial intelligence techniques may be able to automatically calculate liver and spleen volume and facilitate more accurate diagnosis. After IRB approval, 2 convolutional neural networks (CNN) were developed to automatically segment the liver and spleen on a training dataset comprised of 500 single-phase, contrast-enhanced CT abdomen and pelvis examinations. A separate dataset of ten thousand sequential examinations at a single institution was segmented with these CNNs. Performance was evaluated on a 1% subset and compared with manual segmentations using Sorensen-Dice coefficients and Pearson correlation coefficients. Radiologist reports were reviewed for diagnosis of hepatomegaly and splenomegaly and compared with calculated volumes. Abnormal enlargement was defined as greater than 2 standard deviations above the mean. Median Dice coefficients for liver and spleen segmentation were 0.988 and 0.981, respectively. Pearson correlation coefficients of CNN-derived estimates of organ volume against the gold-standard manual annotation were 0.999 for the liver and spleen (P < 0.001). Average liver volume was 1556.8 ± 498.7 cc and average spleen volume was 194.6 ± 123.0 cc. There were significant differences in average liver and spleen volumes between male and female patients. Thus, the volume thresholds for ground-truth determination of hepatomegaly and splenomegaly were determined separately for each sex. Radiologist classification of hepatomegaly was 65% sensitive, 91% specific, with a positive predictive value (PPV) of 23% and an negative predictive value (NPV) of 98%. Radiologist classification of splenomegaly was 68% sensitive, 97% specific, with a positive predictive value (PPV) of 50% and a negative predictive value (NPV) of 99%. Convolutional neural networks can accurately segment the liver and spleen and may be helpful to improve radiologist accuracy in the diagnosis of hepatomegaly and splenomegaly.
ABSTRACT
CASE: Benjamin is a 9-month-old, former 36-week gestation infant who presented to the high-risk infant follow-up clinic with parental concern for developmental regression. His mother reported that Benjamin seemed to be developing typically, but over the past 2 months, he has lost the ability to visually track objects, is not as engaged with her as he once was, and now only rarely makes babbling sounds. His mother also reported episodes of intermittent "bursts" of stiffening of his extremities and brief staring spells. Benjamin's mother described him as a "good, quiet baby." She commented that he used to laugh and cry more frequently but has recently been "very peaceful and calm." Benjamin's mother recently relayed her concerns for developmental regression to his pediatrician during an audio-only telehealth visit. Benjamin was referred to a pediatric neurologist, and the consultation visit is pending.His mother is a 28-year-old single parent whose pregnancy was complicated by pre-eclampsia, gestational diabetes, and anxiety. Benjamin required admission to the neonatal intensive care unit because of initial feeding difficulties. After 1 week, Benjamin was discharged to home and was referred for early intervention services. Owing to the pandemic, there were delays with initiating intervention, but bimonthly virtual interaction with a representative from the infant development program was eventually provided.Benjamin's mother expressed significant concerns regarding the potential of exposing him to a pandemic-related illness because of bringing her son to in-person medical visits. In fact, because of her concerns, she attended only virtual well-child pediatric visits over the past 6 months. A thorough social history revealed that she is a former dance studio instructor. The studio closed and she lost her primary source of income because of the pandemic. As a result, she decided to not send Benjamin to child care and maintained isolation from extended family members.On physical examination, pertinent findings included poor truncal tone, lack of orientation toward sounds, and limited eye contact. The Bayley Scales of Infant and Toddler Development-Third Edition (Bayley-III) was administered, and the results indicated severe delays across all developmental areas, consistent with a diagnosis of global developmental delay.Benjamin's clinical presentation to the HRIF clinic and a history of developmental regression and intermittent body movements raised concerns for infantile spasms. He was transferred to the emergency department for evaluation and consideration for admission to the neurology service. An electroencephalogram confirmed epileptiform abnormalities consistent with infantile spasms, and he was immediately started on treatment.Impacts of the pandemic on the medical care of vulnerable/at-risk pediatric patients have included delayed receipt of early intervention services, parental fear regarding potential exposure to pandemic-related illness while seeking preventative care, increased use of virtual visit platforms for medical care and developmental intervention services, etc. What factors should be considered when providing support for these vulnerable/at-risk patients?
