Jonathan R. Young

Purpose: This study aimed to investigate alterations in brain white matter fiber bundle integrity among older long-term breast cancer survivors treated with chemotherapy, with a focus on identifying potential neural correlates of cancer-related cognitive impairment (CRCI). Methods: Women aged 65 years and older were prospectively enrolled and divided into three groups: breast cancer survivors 5 to 15 years after chemotherapy treatment (C+), breast cancer survivors without chemotherapy (C−), and age–sex-matched healthy controls (HC). Participants underwent brain MRI with diffusion tensor imaging and cognitive testing at time point 1 (TP1) upon enrollment and again after two years at time point 2 (TP2). White matter fiber tract integrity was assessed using fractional anisotropy-based (FA) tractography across 80 major fiber bundles in the brain. Results: Over the two-year period, both C+ and C− groups exhibited significant reductions in white matter integrity with FA reductions noted in several fiber tracts, including the left inferior fronto-occipital fasciculus (C+ group: p < 0.01; C− group: p = 0.01), right inferior fronto-occipital fasciculus (p < 0.01), left inferior longitudinal fasciculus (C+ group: p < 0.01; C− group: p = 0.04), right inferior longitudinal fasciculus (C+ group: p = 0.04; C− group: p = 0.02), right vertical occipital fasciculus (C+ group: p < 0.02; C− group: p = 0.01), left anterior corticostriatal tracts (C+ group: p < 0.01; C− group: p = 0.02), right anterior corticostriatal tracts (C+ group: p = 0.01; C− group: p = 0.02), anterior commissure (C+ group: p = 0.01; C− group: p = 0.03), and forceps minor (C+ group: p = 0.03; C− group: p = 0.01). In addition, FA reductions were noted in the left superior longitudinal fasciculus (p < 0.01), uncinate fasciculus (p = 0.01), thalamic radiation (p = 0.04), left optic radiations (p = 0.04) and right optic radiations (p = 0.03) in the C+ group only. No significant changes over time were detected in the HC group (p > 0.05). The fiber tract changes were considered statistically significant at a threshold of p < 0.05, with family-wise error (FWE) correction. Significant positive correlation was found between the longitudinal changes in the right inferior fronto-occipital fasciculus and the fluid composite cognition score in the C+ group (R = 0.65 and p = 0.03; Pearson’s correlation). Conclusions: This study showed continued white matter fiber tract alterations in the older long-term breast cancer survivors who may have cognitive difficulties years after chemotherapy. Diffusion tensor imaging may provide valuable insights into the white matter microstructural correlates of CRCI in older cancer survivors.

Background: With the development of new human epidermal growth factor 2 (HER2)‐targeting therapies, a non‐invasive method of determining the HER2 status of breast cancer brain metastases can be of great clinical value, particularly given the risks of brain biopsy and the possibility of discordance between HER2 status of the primary breast cancer and the brain metastasis. Aims: The purpose of this study was to assess whether the volume transfer constant (Ktrans) from dynamic contrast‐enhanced (DCE) perfusion brain MR could assist in identifying the HER2 status of breast cancer brain metastases. Methods: With IRB approval for this retrospective study, we searched the electronic medical record at the City of Hope Comprehensive Cancer Center to identify all histopathologically proven breast cancer brain metastases with both preoperative DCE perfusion brain MR and HER2 assessment of the resected/biopsied brain specimens at the City of Hope Comprehensive Cancer Center from 2011‐2022. Mann‐Whitney tests were used to compare the Ktrans of the breast cancer brain metastases. Results: There were 9 women in our study cohort with a mean age of 55 years. Our cohort was comprised of a total of 9 breast cancer brain metastases, 3 of which were HER2‐positive, 6 of which were HER2‐negative. The Ktrans of HER2‐positive breast cancer brain metastases was significantly greater than the Ktrans of HER2‐negative breast cancer brain metastases (0.09 min ⁻¹ vs 0.02 min ⁻¹ , U = 18.00, p = 0.024). Conclusion: Ktrans may help to differentiate HER2‐positive from HER2‐negative breast cancer brain metastases, if validated in a large prospective, multi‐center trial.

Purpose: The objective of this study was to evaluate whether uptake on ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET could help differentiate HER2-positive from HER2-negative breast cancer brain metastases. Methods: In this retrospective, cross-sectional study of a cohort of 14 histologically proven breast cancer brain metastases, we analyzed both preoperative ¹⁸F-FDG PET/CT and HER2 status of the resected/biopsied brain specimens. The maximum standardized uptake values (SUVmax) of the lesions were normalized to contralateral normal white matter and compared using Mann–Whitney U tests. Results: The study cohort was comprised of 12 women with breast cancer with a mean age of 59 years (range: 43–76 years) with a total of 14 distinct brain metastatic lesions. The SUVmax ratio of HER2-positive breast cancer brain metastases was significantly greater than that of HER2-negative lesions (3.98 vs 1.79, U = 38.00, p = 0.008). Conclusion: The SUVmax ratio may help to identify the HER2 status of breast cancer brain metastases, if validated prospectively.

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.

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.

OBJECTIVE. The purpose of this study was to determine whether qualitative MDCT features are associated with the carbonic anhydrase IX (CAIX) score of clear cell renal cell carcinoma (RCC). The CAIX score has been previously found to have prognostic significance for disease-free survival, overall survival, and lymph node involvement. MATERIALS AND METHODS. A cohort of 105 histologically proven clear cell RCCs in patients who underwent preoperative four-phase renal mass MDCT was derived from 2001 to 2013. Two genitourinary radiologists evaluated each lesion for the gross appearance of intratumoral vascularity, calcification, enhancement pattern, necrosis, margin, collecting system invasion, and renal vein invasion. Immunohistochemical analysis was used to determine the CAIX score (defined as the positive staining percentage multiplied by the staining intensity). Logistic and linear regression analyses were performed. RESULTS. In a linear regression model controlled for lesion size and stage, the gross appearance of intratumoral vascularity had a significant positive association with CAIX score (beta = 38.33, p = 0.010). In a logistic regression model controlled for lesion size and stage, the gross appearance of intratumoral vascularity had an odds ratio of 2.85 (p = 0.019) in differentiating clear cell RCCs with a CAIX score of 200-300 from clear cell RCCs with a CAIX score of 0-199. CONCLUSION. In clear cell RCCs, the gross appearance of intratumoral vascularity at MDCT was significantly associated with CAIX score, a prognostically significant molecular marker. Current assessment of CAIX score requires pathologic tissue sampling and immunohistochemical analysis. A noninvasive imaging biomarker that may help predict CAIX score may be of great clinical value.

BACKGROUND AND PURPOSE: Our aim was to evaluate whether serial administration of the macrocyclic gadolinium-based contrast agent gadoteridol in children is associated with T1-weighted hyperintensity within the dentate nucleus, an imaging surrogate for gadolinium deposition. MATERIALS AND METHODS: We identified a retrospective cohort of 10 patients younger than 18 years of age who underwent between 4 and 8 gadoteridol-enhanced MR imaging examinations of the brain from 2016 to 2017. For comparison, we identified a retrospective cohort of 9 pediatric patients who each underwent 6 gadodiamide-enhanced MR imaging examinations. For each examination, both dentate nuclei were contoured on unenhanced images and the mean dentate-to-pons signal intensity ratio was calculated. Dentate-to-pons signal intensity ratios from the first and last scans were compared using paired t tests. RESULTS: In the gadoteridol group, there was no significant change in the mean dentate-to-pons signal intensity ratio from the first to the last scan (0.99 versus 0.99, P = .59). In the gadodiamide group, there was a significant increase in the mean dentate-to-pons signal intensity ratio from the first to the last scan (0.99 versus 1.10, P = .001). CONCLUSIONS: Repeat administration of the macrocyclic gadolinium-based contrast agent gadoteridol in children was not associated with T1-weighted dentate hyperintensity, while the repeat administration of the linear gadolinium-based contrast agent gadodiamide was associated with T1-weighted dentate hyperintensity, presumably due to gadolinium deposition.