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Byline: Ankush. Modi, Prabhjot. Singh, Amlesh. Seth, Rajeev. Kumar Introduction: Elevated serum prostate-specific antigen (PSA) is the most common trigger for a prostate biopsy. However, the range of normal PSA [...]

Objectives: To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM–DKI) and their machine‐learning‐based texture analysis for the detection and assessment of severity in prostate cancer (PCa). Materials and methods: Eighty‐eight patients underwent MRI on a 3 T scanner after giving informed consent. IVIM–DKI data were acquired using 13 b values (0–2000 s/mm2) and analyzed using the IVIM–DKI model with the total variation (TV) method. PCa patients were categorized into two groups: clinically insignificant prostate cancer (CISPCa) (Gleason grade ≤ 6) and clinically significant prostate cancer (CSPCa) (Gleason grade ≥ 7). One‐way analysis‐of‐variance, t test, and receiver operating characteristic analysis was performed to measure the discriminative ability to detect PCa using IVIM–DKI parameters. A chi‐square test was used to select important texture features of apparent diffusion coefficient (ADC) and IVIM–DKI parameters. These selected texture features were used in an artificial neural network for PCa detection. Results: ADC and diffusion coefficient (D) were significantly lower (p < 0.001), and kurtosis (k) was significantly higher (p < 0.001), in PCa as compared with benign prostatic hyperplasia (BPH) and normal peripheral zone (PZ). ADC, D, and k showed high areas under the curves (AUCs) of 0.92, 0.89, and 0.88, respectively, in PCa detection. ADC and D were significantly lower (p < 0.05) as compared with CISPCa versus CSPCa. D for detecting CSPCa was high, with an AUC of 0.63. A negative correlation of ADC and D with GS (ADC, ρ = −0.33; D, ρ = −0.35, p < 0.05) and a positive correlation of k with GS (ρ = 0.22, p < 0.05) were observed. Combined IVIM–DKI texture showed high AUC of 0.83 for classification of PCa, BPH, and normal PZ. Conclusion: D, f, and k computed using the IVIM–DKI model with the TV method were able to differentiate PCa from BPH and normal PZ. Texture features of combined IVIM–DKI parameters showed high accuracy and AUC in PCa detection. [ABSTRACT FROM AUTHOR]

Introduction: The blood-based inflammatory marker, neutrophil-to-lymphocyte ratio (NLR), is a reliable prognostic biomarker for several cancers. Although the literature supports the correlation between preoperative NLR, clinicopathological characteristics, and oncological outcomes in upper tract urothelial carcinoma (UTUC), the cutoff of NLR is still debated. This study aimed to determine the prognostic value of NLR in patients with UTUC. Methods: This was a retrospective analysis of prospectively collected data from July 2012 to December 2022 evaluating patients with UTUC who underwent radical nephroureterectomy (RNU). NLR was calculated using the neutrophil and lymphocyte counts obtained a day before the surgery and the cutoff value was set as 2.5. Kaplan-Meier and Cox's proportional hazards regression were used to analyze the association between NLR and the oncological outcomes. Results: The study included 91 patients (78 males, 13 females) in the final analysis with a median follow-up of 49 months (8-130). The mean age of the patients with NLR <2.5 and NLR >2.5 was 56.88 years and 56.35 years, respectively, and the pathological stage was pT1 in 48%, pT2 in 20.88%, pT3 in 27.47%, and pT4 in 3.30% of the patients. Multivariable Cox regression analysis showed that the preoperative NLR >2.5 was significantly associated (Hz = 7.17) with higher T stage, lymphovascular invasion, necrosis, nodal involvement, adjuvant chemotherapy, and worse overall survival (OS) (Hz = 9.87). The Kaplan-Meier analysis revealed an improved OS in patients with NLR <2.5, but a statistically significant difference in the recurrence-free survival was not found. Conclusions: Preoperative NLR is an easily available, inexpensive, and important prognostic biomarker of survival in patients with UTUC and has a potential role in risk stratification by predicting adverse clinicopathological characteristics. [ABSTRACT FROM AUTHOR]

Byline: Harshit. Garg, Brusabhanu. Nayak, Ashish. Kumar, Prabhjot. Singh, Rishi. Nayyar, Aashir. Kaul, Amlesh. Seth Background: Renal cell carcinoma (RCC) presents with inferior vena cava (IVC) thrombus in 10%-30% cases [...]

Byline: Biswamohan. Mishra, Ankit. Sachan, Chandrasekhar. Bal, Achal. Srivastava, Amlesh. Seth, Anubhav. Narwal, Mehar. Sharma, Seema. Kaushal, Anoop. Saraya, Awadh. Pandit Sir, A 43-year-old male without any co-morbidity presented with [...]

Byline: Prashant. Sharma, Sridhar. Panaiyadiyan, Santosh. Kurra, Raman. Kumar, Brusabhanu. Nayak, Seema. Kaushal, Alpana. Sharma, Rajeev. Kumar, Amlesh. Seth, Prabhjot. Singh We appreciate the author's interest in our recently published [...]

Byline: Harshit. Garg, Amlesh. Seth, Rajeev. Kumar Introduction: Prostate-specific antigen (PSA) >20 ng/mL in isolation is a criterion for classification as 'high-risk' prostate cancer (PCa). However, among Indian men, PSA [...]

Byline: Sumit. Saini, Brusabhanu. Nayak, Prashant. Singh, Amlesh. Seth Renal lymphangiectasia characterised by either unilocular or multilocular cystic lesion in and around the kidney is an uncommon condition. Presentation of [...]